PV_LIB Toolbox

The PV_LIB Toolbox provides a set of well-documented functions for simulating the performance of photovoltaic energy systems. Currently there are two distinct versions (pvlib-python and PVILB for Matlab) that differ in both structure and content. Both versions were initially developed at Sandia National Laboratories but have since been offered as open-source software projects and have grown significantly from contributions from an active community of users (see list of papers that cite the packages below).

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Documentation Links:

To cite pvlib-python please reference this 2018 Publication of PVLIB in Journal of Open Source Software: pvlib python: a python package for modeling solar energy systems (19285 downloads)

Holmgren, W., C. Hansen and M. Mikofski (2018). “pvlib Python: A python package for modeling solar energy systems.” Journal of Open Source Software 3(29): 884.

Partial List of References that cite PVLIB (obtained from Google Scholar):

2022 (updated February 8, 2022)

Hu, W, Cervone, G, Merzky, A, Turilli, M, & Jha, S (2022). A New Hourly Dataset for Photovoltaic Energy Production for the Continental USA. Data in Brief, Elsevier, https://www.sciencedirect.com/science/article/pii/S2352340922000361
Smith, DE, Hughes, MD, & Borca-Tasciuc, DA (2022). Towards a standard approach for annual energy production of concentrator-based building-integrated photovoltaics. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148121018759
Riaz, MH, Imran, H, Alam, H, Alam, MA, & … (2022). Crop-Specific Optimization of Bifacial PV Arrays for Agrivoltaic Food-Energy Production: The Light-Productivity-Factor Approach. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9674806/
Yang, D, Wang, W, & Xia, X (2022). A Concise Overview on Solar Resource Assessment and Forecasting. Advances in Atmospheric Sciences, Springer, https://doi.org/10.1007/s00376-021-1372-8
Wijeratne, WMPU, Samarasinghalage, TI, Yang, RJ, & … (2022). Multi-objective optimisation for building integrated photovoltaics (BIPV) roof projects in early design phase. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261921016998
Bell, C (2022). Fluids Documentation., media.readthedocs.org, https://media.readthedocs.org/pdf/fluids/latest/fluids.pdf
Arens, S, Schlüters, S, Hanke, B, Maydell, K von, & … (2022). Multi-unit Japanese auction for device agnostic energy management. International Journal of …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0142061521005895
Hu, W, Cervone, G, Turilli, M, Merzky, A, & Jha, S (2022). A Scalable Solution for Running Ensemble Simulations for Photovoltaic Energy. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/2201.06962
Lorenz, E, Guthke, P, Dittmann, A, Holland, N, & … (2022). High resolution measurement network of global horizontal and tilted solar irradiance in southern Germany with a new quality control scheme. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21009828
Cañadillas-Ramallo, D, Moutaoikil, A, Shephard, LE, & … (2022). The influence of extreme dust events in the current and future 100% renewable power scenarios in Tenerife. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S096014812101733X
Nespoli, A, Niccolai, A, Ogliari, E, Perego, G, Collino, E, & … (2022). Machine Learning techniques for solar irradiation nowcasting: Cloud type classification forecast through satellite data and imagery. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261921011600
Romero-Fiances, I, Livera, A, Theristis, M, Makrides, G, & … (2022). Impact of duration and missing data on the long-term photovoltaic degradation rate estimation. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S096014812101404X
Habte, A (2022). Solar Radiometer Instrumentation Evaluation: Cooperative Research and Development Final Report, CRADA Number CRD-16-00619., osti.gov, https://www.osti.gov/biblio/1841135
Oh, M, Kim, CK, Kim, B, Yun, C, Kim, JY, Kang, Y, & Kim, HG (2022). Analysis of minute-scale variability for enhanced separation of direct and diffuse solar irradiance components using machine learning algorithms. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544221031704
Feng, C, Zhang, J, Zhang, W, & Hodge, BM (2022). Convolutional neural networks for intra-hour solar forecasting based on sky image sequences. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261921016639
Visser, L, AlSkaif, T, & Sark, W van (2022). Operational day-ahead solar power forecasting for aggregated PV systems with a varying spatial distribution. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148121015688
Brandi, S, Gallo, A, & Capozzoli, A (2022). A predictive and adaptive control strategy to optimize the management of integrated energy systems in buildings. Energy Reports, Elsevier, https://www.sciencedirect.com/science/article/pii/S2352484721014979
Yang, D, Yagli, GM, & Srinivasan, D (2022). Sub-minute probabilistic solar forecasting for real-time stochastic simulations. Renewable and Sustainable Energy …, Elsevier, https://www.sciencedirect.com/science/article/pii/S1364032121010078
Eggimann, S, Vulic, N, Rüdisüli, M, Mutschler, R, & … (2022). Spatiotemporal upscaling errors of building stock clustering for energy demand simulation. Energy and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0378778822000159
Paul, D, Michele, G De, Najafi, B, & Avesani, S (2022). Benchmarking clear sky and transposition models for solar irradiance estimation on vertical planes to facilitate glazed facade design. Energy and Buildings, Elsevier, https://www.sciencedirect.com/science/article/pii/S0378778821009063
Dab, K, Agbossou, K, Henao, N, Dubé, Y, Kelouwani, S, & … (2022). A compositional kernel based gaussian process approach to day-ahead residential load forecasting. Energy and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S037877882100743X
Beebe, NHF (2022). A Bibliography of Publications about the Python Scripting and Programming Language., ctan.math.utah.edu.
Blum, NB, Wilbert, S, Nouri, B, Lezaca, J, Huckebrink, D, & … (2022). Measurement of diffuse and plane of array irradiance by a combination of a pyranometer and an all-sky imager. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21010240
Zhang, G, Yang, D, Galanis, G, & Androulakis, E (2022). Solar forecasting with hourly updated numerical weather prediction. Renewable and Sustainable …, Elsevier, https://www.sciencedirect.com/science/article/pii/S1364032121010364

2021

Theristis, M., A. Livera, L. Micheli, J. Ascencio-Vásquez, G. Makrides, G. E. Georghiou and J. S. Stein (2021). “Comparative Analysis of Change-Point Techniques for Nonlinear Photovoltaic Performance Degradation Rate Estimations.” IEEE Journal of Photovoltaics 11(6): 1511-1518.
Driesse, A., M. Theristis and J. S. Stein (2021). “A New Photovoltaic Module Efficiency Model for Energy Prediction and Rating.” IEEE Journal of Photovoltaics 11(2): 527-534.
Holmgren, W, Lorenzo, T, Hansen, C, Mikofski, M, Krien, U, & … (2021). pvlib/pvlib-python: v0. 8.1., Jan
Ransome, S. (2021), VIRTUAL PVPearl Training School Brasov, Romania, http://www.steveransome.com/pubs/2021_07_PVCOST_Romania_Ransome_210706t11tobepresented.pdf
Khari, S, Ismail, ALİ, Lokman, H, & … (2021). Power loss calculation of Photovoltaics using Python. Computers and …, dergipark.org.tr, https://dergipark.org.tr/en/pub/ci/issue/64530/952567
Sinha, A, Kumar, A, Tiwari, A, & Yadav, K (2021). Analysis of Combined Effect of Temperature and Wind on Solar Power Production. Renewable Power for Sustainable …, Springer, https://doi.org/10.1007/978-981-33-4080-0_57
Ziyoitdinova, M (2021). THE ROLE OF PROBABILITY THEORY IN THE MODELING OF SEMICONDUCTOR DEVICES. Deutsche Internationale Zeitschrift für …, cyberleninka.ru, https://cyberleninka.ru/article/n/the-role-of-probability-theory-in-the-modeling-of-semiconductor-devices
Polo, J, Martín-Chivelet, N, Sanz-Saiz, C, & … (2021). Modeling soiling losses for rooftop PV systems in suburban areas with nearby forest in Madrid. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148121009514
Ismoilov, U (2021). THE ROLE OF THE PYTHON PROGRAMMING LANGUAGE IN MODELING PHYSICAL PROCESSES. Deutsche Internationale Zeitschrift für zeitgenössische …, cyberleninka.ru, https://cyberleninka.ru/article/n/the-role-of-the-python-programming-language-in-modeling-physical-processes
Rinio, M (2021). PVcheck—A Software to Check Your Photovoltaic System. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/20/6757
Gündogdu, H, & Demirc, A (2021). Performance Comparison of Grey Wolf and Perturb&Observe MPPT Algorithms in Different Weather Conditions. 2021 13th International Conference on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9677791/
Sivapriyan, R, Elangovan, D, & Lekhana, KSN (2021). Review of Python for Solar Photovoltaic Systems. Evolutionary Computing and …, Springer, https://doi.org/10.1007/978-981-15-5258-8_12
Øgaard, MB, Riise, HN, & Selj, JH (2021). Modeling Snow Losses in Photovoltaic Systems. 2021 IEEE 48th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518886/
Velosa, N, & Pereira, L (2021). Towards pro-social load balancing in energy communities. Proceedings of the 8th ACM International …, dl.acm.org, https://doi.org/10.1145/3486611.3492235
Kempe, MD, Holsapple, D, Whitfield, K, & … (2021). Standards development for modules in high temperature micro‐environments. Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.3389
Mandal, RK, & Kale, PG (2021). Assessment of different multiclass SVM strategies for fault classification in a PV system. Proceedings of the 7th International Conference on …, Springer, https://doi.org/10.1007/978-981-15-5955-6_70
Jose, S, & Itagi, RL (2021). Data Analytics in Solar Photovoltaics Power Forecasting for Smart Grid Applications. 2021 International Conference on Intelligent …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9498299/
Fonteijn, R, Nguyen, PH, Morren, J, & Slootweg, JG (2021). Baselining Flexibility from PV on the DSO-Aggregator Interface. Applied Sciences, mdpi.com, https://www.mdpi.com/1018516
Macías, J, Herrero, R, Núñez, R, & … (2021). On the effect of cell interconnection in Vehicle Integrated Photovoltaics: modelling energy under different scenarios. 2021 IEEE 48th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518935/
Chen, S, & Li, M (2021). Improved Turbidity Estimation from Local Meteorological Data for Solar Resourcing and Forecasting Applications. Available at SSRN 3946170, papers.ssrn.com, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3946170
Prinsloo, FC, Schmitz, P, & Lombard, A (2021). Sustainability assessment framework and methodology with trans-disciplinary numerical simulation model for analytical floatovoltaic energy system planning …. Sustainable Energy Technologies and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S2213138821005269
Florio, P, Peronato, G, Perera, ATD, Blasi, A Di, & … (2021). Designing and assessing solar energy neighborhoods from visual impact. Sustainable Cities and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S2210670721002468
Hofmann, F, Hampp, J, Neumann, F, Brown, T, & … (2021). Atlite: a lightweight Python package for calculating renewable power potentials and time series. Journal of Open Source …, joss.theoj.org, https://doi.org/10.21105/joss.03294
Mikofski, MA, & Kharait, R (2021). Comparison of Predicted PV System Performance with SURFRAD versus TMY. 2021 IEEE 48th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9519024/
Bright, JM (2021). Introduction to synthetic solar irradiance., aip.scitation.org, https://doi.org/10.1063/9780735421820_001
Kaaya, I, & Ascencio-Vásquez, J (2021). Photovoltaic Power Forecasting Methods. Solar Radiation-Measurements …, intechopen.com, https://www.intechopen.com/online-first/photovoltaic-power-forecasting-methods
David, AY, Scott, J, Montgomery, W, & … (2021). Cloud Coverage Prediction to Improve Solar Power Management. …, scholarworks.calstate.edu, https://scholarworks.calstate.edu/downloads/xw42nf32n
Shuvro, RA, Xiong, J, & Deng, Y (2021). Spectral Correction Model Validation Using Spectroradiometer Measurements for CdTe Modules. 2021 IEEE 48th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518893/
Anderson, K, Downs, C, Aneja, S, & … (2021). A Method for Estimating Time-Series PV Production Loss From Solar Tracking Failures. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9627163/
Øgaard, M, Riise, HN, & Selj, JHK (2021). Estimation of snow loss for photovoltaic plants in Norway. Proceedings of the European …, duo.uio.no, https://www.duo.uio.no/handle/10852/89488
Comfort, AFOOT (2021). Modelling Perimeter Heating Demand: A Function Of Occupant Thermal Comfort., kpmb.com, https://www.kpmb.com/wp-content/uploads/2021/10/KPMB-LAB_Modelling-Perimeter-Thermal-Energy.pdf
Øgaard, MB, Aarseth, BL, Skomedal, ÅF, Riise, HN, & … (2021). Identifying snow in photovoltaic monitoring data for improved snow loss modeling and snow detection. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21003868
Johnson, J, Jencka, L, Ortiz, T, Jones, C, Chavez, A, & … (2021). Design Considerations for Distributed Energy Resource Honeypots and Canaries.., osti.gov, https://www.osti.gov/biblio/1821540
Noord, M van, Landelius, T, & Andersson, S (2021). Snow-Induced PV Loss Modeling Using Production-Data Inferred PV System Models. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/6/1574
Schardt, J, & Heesen, H te (2021). Performance of roof-top PV systems in selected European countries from 2012 to 2019. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21001006
Montoya, JF Dávila (2021). Diseño y evaluación mediante modelamiento de un sistema solar fotovoltaico comercial., repositorio.uniandes.edu.co, https://repositorio.uniandes.edu.co/handle/1992/51594
Wright, D, Liu, L, Parvan, L, Majumdar, Z, & … (2021). Economic analysis of a novel design of microtracked concentrating photovoltaic modules. Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.3379
Anderson, K, Kemnitz, J, & Boyd, M (2021). Evaluating cell temperature models and the effect of wind speed in PV system capacity testing. 2021 IEEE 48th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9519077/
Deline, C, Anderson, K, Jordan, D, Walker, A, Desai, J, & … (2021). PV Fleet Performance Data Initiative: Performance Index-Based Analysis., osti.gov, https://www.osti.gov/biblio/1766838
Nardin, G, Domínguez, C, Aguilar, ÁF, & … (2021). Industrialization of hybrid Si/III–V and translucent planar micro‐tracking modules. Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.3387
Smith, LD, & Kirschen, DS (2021). Impacts of Time-of-Use Rate Changes on the Electricity Bills of Commercial Consumers. 2021 IEEE Power & Energy Society …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9638125/
Lyden, A, Flett, G, & Tuohy, PG (2021). PyLESA: A Python modelling tool for planning-level Local, integrated, and smart Energy Systems Analysis. SoftwareX, Elsevier, https://www.sciencedirect.com/science/article/pii/S2352711021000443
Mendoza, H, Hopwood, M, & … (2021). pvOps: Improving operational assessments through data fusion. 2021 IEEE 48th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518439/
Choné, T, Richaud, L, Rigal, B, Pellerej, R, & … (2021). New planning tool for Low Voltage photovoltaic connection-large scale experimentation. CIRED 2021-The …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9692730/
Wang, K, & Clow, GD (2021). Newly collected data across Alaska reveal remarkable biases in solar radiation products. International Journal of Climatology, Wiley Online Library, https://doi.org/10.1002/joc.6634
Кардаш, ДО, Любименко, ОМ, Кондратенко, ВГ, & … (2021). Дослідження моделі передбачення потужності, що генерується сонячною електростанцією., ea.donntu.edu.ua, http://ea.donntu.edu.ua/bitstream/123456789/33275/1/2074-2630-2021-1-73-76.pdf
Maghami, I, Sobral, VAL, Morsy, MM, Lach, JC, & … (2021). Exploring the complementary relationship between solar and hydro energy harvesting for self-powered water monitoring in low-light conditions. … Modelling & Software, Elsevier, https://www.sciencedirect.com/science/article/pii/S136481522100075X
Ernst, M, Conechado, GEJ, & Asselineau, CA (2021). Accelerating the simulation of annual bifacial illumination of real photovoltaic systems with ray tracing. Iscience, Elsevier, https://www.sciencedirect.com/science/article/pii/S2589004221016680
Westbrook, O (2021). Your P Values Are Wrong. 2021 IEEE 48th Photovoltaic Specialists …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9519076/
Bacry, E, Soares, D de Barros, Andrieux, F, & … (2021). Predicting the solar potential of rooftops using image segmentation and structured data. NIPS …, hal.archives-ouvertes.fr, https://hal.archives-ouvertes.fr/hal-03438761/file/2106.15268.pdf
Riise, HN, Øgaard, M, Zhu, J, You, CC, & … (2021). Performance analysis of a BAPV bifacial system in Norway. 2021 IEEE 48th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518963/
Plessis, AA Du, Strauss, JM, & Rix, AJ (2021). Short-term solar power forecasting: Investigating the ability of deep learning models to capture low-level utility-scale Photovoltaic system behaviour. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261920317657
Pierce, BG, Braid, JL, Stein, JS, & … (2021). Solar Transposition Modeling via Deep Neural Networks With Sky Images. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9623380/
Costa, TAC (2021). Sistema de regras para acompanhamento de performance em usinas fotovoltaicas empregando técnicas de aprendizagem de máquina., repositorio.ufc.br, https://repositorio.ufc.br/handle/riufc/61916
Jost, N, Askins, S, Dixon, R, Ackermann, M, & … (2021). Novel Interconnection Method for Micro-CPV Solar Cells. 2021 IEEE 48th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518837/
Livera, A, Theristis, M, Koumpli, E, & … (2021). Data processing and quality verification for improved photovoltaic performance and reliability analytics. Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.3349
Smith, LJ (2021). Power Output Modeling and Optimization for a Single Axis Tracking Solar Farm on Skewed Topography Causing Extensive Shading., digitalcommons.calpoly.edu, https://digitalcommons.calpoly.edu/theses/2293/
Soares, DB, Andrieux, F, Hell, B, Lenhardt, J, & … (2021). Predicting the solar potential of rooftops using image segmentation and structured data. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/2106.15268
Larson, DP, & Hobbs, WB (2021). Fleet-Level PV Modeling with Realistic Sub-Hourly Solar Power Variability. 2021 IEEE 48th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518684/
Riaz, MH, Imran, H, Younas, R, & … (2021). Module technology for agrivoltaics: vertical bifacial versus tilted monofacial farms. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9330760/
Patel, MT, Wickramaarachchi, GT, & … (2021). Machine Learning allows Synthesis and Functional Interpolation of Computational and Field-Data for Worldwide Utility-Scale PV Systems. 2021 IEEE 48th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518432/
Azaioud, H, Knockaert, J, Vandevelde, L, & Desmet, J (2021). RE/SOURCED PILOT PROJECT: DESIGN AND POWER FLOWANALYSIS OF A LVDC BACKBONE WITH HYBRID ENERGY SYSTEM., IET, https://doi.org/10.1049/icp.2021.1737
Mahdavi, A, Wolosiuk, D, & Berger, C (2021). A bi-directional approach to building-integrated PV systems configuration. Journal of Physics …, iopscience.iop.org, https://doi.org/10.1088/1742-6596/2069/1/012114
Yao, T, Wang, J, Wu, H, Zhang, P, Li, S, Wang, Y, Chi, X, & … (2021). A photovoltaic power output dataset: Multi-source photovoltaic power output dataset with Python toolkit. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21008070
Deline, C, Pelaez, SA, Anderson, K, Jordan, D, Perry, K, & … (2021). PV Field Performance Including Fleet and Bifacial Field Data., osti.gov, https://www.osti.gov/biblio/1778188
Chiodetti, M, Lafont, T, Gherardi, CM, & Radvanyi, E (2021). THE ROAD TOWARDS A 100% RENEWABLE ELECTRICITY MIX IN THE FRENCH ISLAND OF MIQUELON., IET, https://doi.org/10.1049/icp.2021.1754
Oh, M, Kim, JY, Kim, B, Yun, CY, Kim, CK, Kang, YH, & … (2021). Tolerance angle concept and formula for practical optimal orientation of photovoltaic panels. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148120318486
Dumlao, SMG, & Ishihara, KN (2021). Weather-Driven Scenario Analysis for Decommissioning Coal Power Plants in High PV Penetration Grids. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/9/2389
Routhier, AF, Bowden, SG, Goodnick, SM, & … (2021). What is the LCOE of residential solar+ battery in the face on increasingly complex utlity rate plans?. 2021 IEEE 48th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9519070/
Deline, C, Anderson, K, Jordan, D, & … (2021). Performance Index Assessment for the PV Fleet Performance Data Initiative. 2021 IEEE 48th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518760/
Voicu, V, Petreus, D, Cebuc, E, & … (2021). An IoT Photovoltaic Sensing System. 2021 20th RoEduNet …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9638286/
Libralato, M, Angelis, A De, D’Agaro, P, & … (2021). Multiyear hygrothermal performance simulation of historic building envelopes. … Series: Earth and …, iopscience.iop.org, https://doi.org/10.1088/1755-1315/863/1/012045
Coppitters, D, Paepe, W De, & … (2021). Robust design optimization of a renewable-powered demand with energy storage using imprecise probabilities. E3S Web of …, search.proquest.com, https://search.proquest.com/openview/491a305a63cdc9f19e54496658935319/1?pq-origsite=gscholar&cbl=2040555
Parikh, A, Perry, K, Anderson, K, & … (2021). Validation of Subhourly Clipping Loss Error Corrections. 2021 IEEE 48th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518564/
Nair, DS, & Rajeev, T (2021). Investigation on Impact of Solar PV penetration on the Operation of Protective Relays in a Distribution System using Python. 2021 IEEE Conference on Technologies …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9467474/
Claeys, R, Azaioud, H, & Desmet, J (2021). Peak demand dynamics of low-voltage consumers under aggregation and its impact on upstream PV injection. CIRED 2021-The 26th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9692842/
Micheli, L, Smestad, GP, Bessa, JG, & … (2021). Tracking Soiling Losses: Assessment, Uncertainty, and Challenges in Mapping. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9576825/
Meyer, D, Grimmond, S, Dueben, P, Hogan, R, & … (2021). Machine Learning Emulation of Urban Land Surface Processes. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/2112.11429
Marion, B (2021). Evaluation of clear-sky and satellite-derived irradiance data for determining the degradation of photovoltaic system performance. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21004412
Mayer, MJ, & Gróf, G (2021). Extensive comparison of physical models for photovoltaic power forecasting. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261920316330
Scheidt, F vom, Dong, X, Bartos, A, Staudt, P, & … (2021). Probabilistic Forecasting of Household Loads: Effects of Distributed Energy Technologies on Forecast Quality. Proceedings of the …, dl.acm.org, https://doi.org/10.1145/3447555.3464861
Pimienta, B (2021). Total Electricity Demand Coverage with Solar Energy Systems in La Guajira-Colombia. A techno-economic case study.
Kazmi, H, Munné-Collado, Í, Mehmood, F, & … (2021). Towards data-driven energy communities: A review of open-source datasets, models and tools. … and Sustainable Energy …, Elsevier, https://www.sciencedirect.com/science/article/pii/S1364032121005773
Matthiss, B, Momenifarahani, A, & Binder, J (2021). Storage placement and sizing in a distribution grid with high PV generation. Energies, mdpi.com, https://www.mdpi.com/953196
Kull, T, Zeilmann, B, & Fischerauer, G (2021). PLC implementation of economic model predictive control for scheduling and dispatch in energy systems. ETG Congress 2021, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9469613/
Гузевич, СН (2021). УСЛОВИЯ ДОСТОВЕРНЫХ ИЗМЕРЕНИЙ В ПРОСТРАНСТВЕ. Deutsche Internationale Zeitschrift für zeitgenössische …, cyberleninka.ru, https://cyberleninka.ru/article/n/usloviya-dostovernyh-izmereniy-v-prostranstve
Kosmadakis, IE, Elmasides, C, Koulinas, G, & … (2021). Energy unit cost assessment of six photovoltaic-battery configurations. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148121003645
Kosmadakis, IE, & Elmasides, C (2021). A sizing method for PV–battery–generator systems for off-grid applications based on the LCOE. Energies, mdpi.com, https://www.mdpi.com/1059344
Salmon, N, & Bañares-Alcántara, R (2021). Impact of grid connectivity on cost and location of green ammonia production: Australia as a case study. Energy & Environmental Science, pubs.rsc.org, https://pubs.rsc.org/en/content/articlehtml/2021/ee/d1ee02582a
Schmid, F, & Behrendt, F (2021). Optimal sizing of Solar Home Systems: Charge controller technology and its influence on system design. Sustainable Energy Technologies and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S2213138821002083
Pun, K, Basnet, SMS, & Jewell, W (2021). Solar Power Prediction in Different Forecasting Horizons Using Machine Learning and Time Series Techniques. 2021 IEEE Conference on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9467464/
Coppitters, D, Paepe, W De, & Contino, F (2021). Robust design optimization of a photovoltaic-battery-heat pump system with thermal storage under aleatory and epistemic uncertainty. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544221009403
Timplalexis, C, Bezas, N, Bintoudi, AD, Zyglakis, L, & … (2021). A hybrid physical/statistical day-ahead direct PV forecasting engine., IET, https://doi.org/10.1049/icp.2021.1233
Bintoudi, AD, Zyglakis, L, Tsolakis, AC, Gkaidatzis, PA, & … (2021). OptiMEMS: An Adaptive Lightweight Optimal Microgrid Energy Management System Based on the Novel Virtual Distributed Energy Resources in Real-Life …. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/10/2752
Noord, M van, Landelius, T, & Andersson, S (2021). Utveckling av prognosmodeller och–verktyg för snöpåverkan på solelproduktion via fjärrmätning., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1595697
Zhao, C, Xiao, J, Yu, Y, & Jaubert, JN (2021). Accurate shading factor and mismatch loss analysis of bifacial HSAT systems through ray-tracing modeling. Solar Energy Advances, Elsevier, https://www.sciencedirect.com/science/article/pii/S2667113121000048
Vivian, J, Zarrella, A, Besagni, G, & … (2021). Experimental tests on the optimal management of all-electric dwellings. Building Simulation 2021 …, re.public.polimi.it, https://re.public.polimi.it/handle/11311/1188780
Miller, J, & Uludag, S (2021). Energy-Efficiency Framework for Fixed-Wing UAV Communications With Variable Altitude. 2021 IEEE International Conference on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9473819/
Gilletly, SD, Jackson, ND, & Staid, A (2021). Quantifying Wildfire-Induced Impacts to Photovoltaic Energy Production in the western United States. 2021 IEEE 48th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518514/
Matthiss, B, Momenifarahani, A, & Binder, J (2021). Storage Placement and Sizing in a Distribution Grid with High PV Generation. Energies 2021, 14, 303., search.proquest.com, https://search.proquest.com/openview/317e9e58e619bf084f22a29ba58b17b5/1?pq-origsite=gscholar&cbl=2032402
Micheli, L, Fernandez, EF, Aguilera, JT, & Almonacid, F (2021). Economics of seasonal photovoltaic soiling and cleaning optimization scenarios. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544220321253
Khudoynazarov, A (2021). EXPLORING SOLAR CELLS BY PROGRAMMING LANGUAGES AND SSTANDART PROGRAMS. Deutsche Internationale Zeitschrift für …, cyberleninka.ru, https://cyberleninka.ru/article/n/exploring-solar-cells-by-programming-languages-and-sstandart-programs
Schindler, M, Pfeiffer, C, Millendorfer, M, Rabelhofer, M, & … (2021). An interdisciplinary approach of a local peer-to-peer energy trading model for a more sustainable power grid., people.fh-burgenland.at, https://people.fh-burgenland.at/handle/20.500.11790/1699
Götz-Köhler, M, Meddeb, H, Gehrke, K, & … (2021). Ultrathin Solar Cell With Magnesium-Based Optical Switching for Window Applications. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9546836/
Azzolini, JA, & Reno, MJ (2021). The Effects of Inverter Clipping and Curtailment-Inducing Grid Support Functions on PV Planning Decisions. 2021 IEEE 48th Photovoltaic Specialists …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518416/
Bromley-Dulfano, I, Florez, J, & Craig, MT (2021). Reliability benefits of wide-area renewable energy planning across the Western United States. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148121011009
Walker, L, Kuhn, A, Hischier, I, & … (2021). Comparing Metrics for Scenario-based Robustness Assessment of Building Performance. Journal of Physics …, iopscience.iop.org, https://doi.org/10.1088/1742-6596/2042/1/012150
Sneezer, S (2021). Modeling & Optimization of a Renewable Energy Supply Chain with a Focus on Energy Storage., oaktrust.library.tamu.edu, https://oaktrust.library.tamu.edu/handle/1969.1/195151
Dhyani, A, Pike, C, Braid, JL, Whitney, E, & … (2021). Facilitating Large‐Scale Snow Shedding from In‐Field Solar Arrays using Icephobic Surfaces with Low‐Interfacial Toughness. Advanced Materials …, Wiley Online Library, https://doi.org/10.1002/admt.202101032
Matsunobu, LM, Pedro, HTC, & Coimbra, CFM (2021). Cloud detection using convolutional neural networks on remote sensing images. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21009294
Song, Z, Liu, J, & Yang, H (2021). Air pollution and soiling implications for solar photovoltaic power generation: A comprehensive review. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S030626192100667X
Simeunovic, J, Schubnel, B, Alet, PJ, & … (2021). Spatio-temporal graph neural networks for multi-site PV power forecasting. IEEE Transactions on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9601234/
Мовчанюк, ОМ (2021). ВИГОТОВЛЕННЯ ПЛОСКИХ АЦЕТАТЦЕЛЮЛОЗНИХ МЕМБРАН. Deutsche Internationale Zeitschrift für …, cyberleninka.ru, https://cyberleninka.ru/article/n/vigotovlennya-ploskih-atsetattselyuloznih-membran
Yu, Z, Yang, Z, Frank, F, Rao, H, & Song, W Wie (2021). Power Generation Prediction of Residential Photovoltaic Equipment Based on Online Transfer Learning Model-A Case Study of a Residential Solar Power System. 2021 4th International …, dl.acm.org, https://doi.org/10.1145/3490322.3490332
Peinado-Guerrero, MA, Villalobos, JR, Phelan, PE, & … (2021). Stochastic framework for peak demand reduction opportunities with solar energy for manufacturing facilities. Journal of Cleaner …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0959652621021090
Smith, T, Rheinwalt, A, & Bookhagen, B (2021). Topography and climate in the upper Indus Basin: Mapping elevation-snow cover relationships. Science of The Total Environment, Elsevier, https://www.sciencedirect.com/science/article/pii/S0048969721024347
Holweger, J (2021). Flexibility for large-scale deployment of PV systems in low-voltage grids., infoscience.epfl.ch, https://infoscience.epfl.ch/record/287073
Micheli, L, Fernández, EF, & Almonacid, F (2021). Photovoltaic cleaning optimization through the analysis of historical time series of environmental parameters. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21007465
Masson, TM, Zondag, SDA, Kuijpers, KPL, & … (2021). Development of an Off‐Grid Solar‐Powered Autonomous Chemical Mini‐Plant for Producing Fine Chemicals. …, Wiley Online Library, https://doi.org/10.1002/cssc.202102011
Cavadini, GB, & Cook, LM (2021). Green and cool roof choices integrated into rooftop solar energy modelling. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261921005341
Brown, J, Abate, A, & Rogers, A (2021). Disaggregation of household solar energy generation using censored smart meter data. Energy and Buildings, Elsevier, https://www.sciencedirect.com/science/article/pii/S0378778820334034
Leitão, J, Fonseca, CM, Gil, P, Ribeiro, B, & … (2021). A Compressive Receding Horizon Approach for Smart Home Energy Management. IEEE Access, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9467369/
Braga, M (2021). Nataly Horner Hoe de Castro., researchgate.net, https://www.researchgate.net/profile/Nataly-Horner/publication/357836358_MASTER_THESIS_NATALY_HORNER_final_version/links/61e1df845779d35951abe4fc/MASTER-THESIS-NATALY-HORNER-final-version.pdf
Fairbrother, A, Quest, H, Özkalay, E, Wälchli, P, & … (2021). Long‐Term Performance and Shade Detection in Building Integrated Photovoltaic Systems. Solar Rrl, Wiley Online Library, https://doi.org/10.1002/solr.202100583
Ansari, D, & Hoffmann, MM (2021). Simulating the potential of swarm grids for pre-electrified communities–A case study from Yemen., d-nb.info, https://d-nb.info/123859882X/34
Merema, B, Carton, Q, Saelens, D, & … (2021). Implementation of MPC for an all-air system in an educational building. E3S Web of …, e3s-conferences.org, https://www.e3s-conferences.org/articles/e3sconf/abs/2021/22/e3sconf_hvac2021_11007/e3sconf_hvac2021_11007.html
Αλεξάκος, Α (2021). Πρόβλεψη παραγωγής ενέργειας και ανίχνευση βλαβών σε φωτοβολταϊκά πάρκα., nemertes.library.upatras.gr, http://nemertes.library.upatras.gr/jspui/handle/10889/15580
Liu, Z, Romagnoli, A, Sapin, P, & … (2021). Dynamic control strategies for a solar-ORC system using first-law dynamic and data-driven machine learning models. Proceedings of the …, mediatum.ub.tum.de, https://mediatum.ub.tum.de/doc/1633138/1633138.pdf
Khan, MR, Patel, MT, Asadpour, R, Imran, H, & … (2021). A review of next generation bifacial solar farms: predictive modeling of energy yield, economics, and reliability. Journal of Physics D …, iopscience.iop.org, https://doi.org/10.1088/1361-6463/abfce5
Micheli, L (2021). Energy and economic assessment of floating photovoltaics in Spanish reservoirs: cost competitiveness and the role of temperature. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21007222
Kumar, R, Rajoria, CS, Sharma, A, & Suhag, S (2021). Design and simulation of standalone solar PV system using PVsyst Software: A case study. Materials Today: Proceedings, Elsevier, https://www.sciencedirect.com/science/article/pii/S2214785320366700
Mathiesen, P, Stadler, M, Kleissl, J, & Pecenak, Z (2021). Techno-economic optimization of islanded microgrids considering intra-hour variability. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261921011144
David, CG, Kohl, N, Casella, E, Rovere, A, Ballesteros, P, & … (2021). Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry. Coral Reefs, Springer, https://doi.org/10.1007/s00338-021-02088-9
Woude, MR van der (2021). An exploratory study on the integration of a renewable-powered electrolyser in a local energy system.
Li, Y, Song, L, Zhang, S, Kraus, L, Adcox, T, & … (2021). A TCN-based Spatial-Temporal PV Forecasting Framework with Automated Detector Network Selection. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/2111.08809
Driesse, A, Gotseff, P, & Sengupta, M (2021). PV Reference Cells for Outdoor Use: An Investigation of Calibration Factors; March 26, 2019-July 31, 2021., osti.gov, https://www.osti.gov/biblio/1823768
Villena, MM de, Gautier, A, Ernst, D, Glavic, M, & … (2021). Modelling and assessing the impact of the DSO remuneration strategy on its interaction with electricity users. International Journal of …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0142061520321542
Ghotge, R, Wijk, A van, & Lukszo, Z (2021). Off-grid solar charging of electric vehicles at long-term parking locations. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544221006058
Radet, H, Roboam, X, Sareni, B, & … (2021). A multi-stage design framework for the investment and operation of a simple microgrid: a comprehensive approach. Symposium du Génie …, hal.archives-ouvertes.fr, https://hal.archives-ouvertes.fr/hal-03294283/
Eig, PYD van (2021). End-user economics of PV-coupled residential battery systems in the Netherlands.
Ranalli, J, & Peerlings, EEM (2021). Cloud advection model of solar irradiance smoothing by spatial aggregation. Journal of Renewable and Sustainable …, aip.scitation.org, https://doi.org/10.1063/5.0050428
Huva, R, Song, G, Zhong, X, & … (2021). Comprehensive physics testing and adaptive weather research and forecasting physics for day‐ahead solar forecasting. Meteorological …, Wiley Online Library, https://doi.org/10.1002/met.2017
Braat, M, Tsafarakis, O, Lampropoulos, I, Besseling, J, & … (2021). Cost-Effective Increase of Photovoltaic Electricity Feed-In on Congested Transmission Lines: A Case Study of The Netherlands. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/10/2868
Merema, B, Saelens, D, & Breesch, H (2021). Analysing modelling challenges of smart controlled ventilation systems in educational buildings. Journal of Building …, Taylor & Francis, https://doi.org/10.1080/19401493.2020.1867639
Julien, S, Sajadi, A, & Hodge, BM (2021). Hierarchical Control of Utility-Scale Solar PV Plants for Mitigation of Generation Variability and Ancillary Service Provision. arXiv preprint arXiv:2107.00160, arxiv.org, https://arxiv.org/abs/2107.00160
Martinez, B, & Vilajosana, X (2021). Exploiting the Solar Energy Surplus for Edge Computing. IEEE Transactions on Sustainable …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9352548/
Yang, D, Li, W, Yagli, GM, & Srinivasan, D (2021). Operational solar forecasting for grid integration: Standards, challenges, and outlook. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21002826
Čus, P (2021). Strujno-naponska karakterizacija solarnih ćelija., repozitorij.pmf.unizg.hr, https://repozitorij.pmf.unizg.hr/islandora/object/pmf:10232
Hashemi, B, Taheri, S, & Cretu, AM (2021). Systematic Analysis and Computational Intelligence Based Modeling of Photovoltaic Power Generation in Snow Conditions. IEEE Journal of Photovoltaics, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9616374/
Micheli, L, Fernández, EF, & … (2021). Analysis and mitigation of nonuniform soiling distribution on utility‐scale photovoltaic systems. Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.3477
Lindig, S, Moser, D, Curran, AJ, Rath, K, & … (2021). International collaboration framework for the calculation of performance loss rates: Data quality, benchmarks, and trends (towards a uniform methodology). Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.3397
Ransome, S, & Sutterlueti, J (2021). Accurate module performance characterisation using novel outdoor matrix methods. 2021 IEEE 48th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9518849/
Martinez, S, Machard, A, Pellegrino, A, Touili, K, & … (2021). A practical approach to the evaluation of local urban overheating–A coastal city case-study. Energy and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0378778821008069
Danner, P, & Meer, H de (2021). Location and solar system parameter extraction from power measurement time series. Energy Informatics, Springer, https://doi.org/10.1186/s42162-021-00176-2
Pfeifer, P, Tran, J, Fendri, A, Krahl, S, & … (2021). Accuracy of load and generation forecasts for the operational planning of power distribution systems. CIRED 2021-The …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9692151/
David, M, Boland, J, Cirocco, L, Lauret, P, & Voyant, C (2021). Value of deterministic day-ahead forecasts of PV generation in PV+ Storage operation for the Australian electricity market. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21004862
Patel, MT (2021). SYSTEM-LEVEL PERFORMANCE AND RELIABILITY OF SOLAR PHOTOVOLTAIC FARMS: LOOKING AHEAD AND BACK., hammer.purdue.edu, https://hammer.purdue.edu/articles/thesis/SYSTEM-LEVEL_PERFORMANCE_AND_RELIABILITY_OF_SOLAR_PHOTOVOLTAIC_FARMS_LOOKING_AHEAD_AND_BACK/17131502/1/files/31682171.pdf
Dimara, A, Triantafyllidis, D, Krinidis, S, & … (2021). District energy optimization based on mlp simulation. 2021 IEEE 11th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9375990/
Lewis, C, Strauss, JM, & Rix, AJ (2021). A solar resource classification algorithm for global horizontal irradiance time series based on frequency domain analysis. Journal of Renewable and …, aip.scitation.org, https://doi.org/10.1063/5.0045032
Hoog, J De, Perera, M, Ilfrich, P, & … (2021). Characteristic profile: improved solar power forecasting using seasonality models. ACM SIGENERGY Energy …, dl.acm.org, https://doi.org/10.1145/3508467.3508476
Kakodkar, R (2021). An Integrated Framework and Software Prototype for Multi-scale Energy Systems Engineering., oaktrust.library.tamu.edu, https://oaktrust.library.tamu.edu/handle/1969.1/195121
Yuan, H, Tang, G, Guo, D, Wu, K, Shao, X, Yu, K, & … (2021). BESS Aided Reconfigurable Energy Supply using Deep Reinforcement Learning for 5G and Beyond. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/2108.06091
Liu, X, Hua, Y, Liu, X, Yang, L, & … (2021). Design and Implementation of Smooth Renewable Power in Cloud Data Centers. IEEE Transactions on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9420320/
Singh, R, Hines, PD, Howerter, SE, & Reilly, JT (2021). Beyond DERMS: Platform Development, Flexibility, Prediction, and Value Measurements., osti.gov, https://www.osti.gov/biblio/1825329
Sendner, FM (2021). Towards Energy-Autonomous Unmanned Aerial System: A Bionic Approach on Solar-Electric, Multi-Vehicle Aerial Platforms for Waterborne Operations. IOP Conference Series: Materials Science and …, iopscience.iop.org, https://doi.org/10.1088/1757-899X/1024/1/012055
Nygren, A, & Sundström, E (2021). Modelling bifacial photovoltaic systems: Evaluating the albedo impact on bifacial PV systems based on case studies in Denver, USA and Västerås, Sweden., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1572661
Kull, T, Zeilmann, B, & Fischerauer, G (2021). Field-ready implementation of linear economic model predictive control for microgrid dispatch in small and medium enterprises. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/13/3921
Devi, AS, Maragatham, G, Boopathi, K, & … (2021). Short-term solar power forecasting using satellite images. International Journal …, inderscienceonline.com, https://doi.org/10.1504/IJPT.2021.117457
Arens, S, Schlueters, S, Hanke, B, & … (2021). Device Type Independent Energy Management of Sector-Coupled Residential Energy Systems. … 2021; Conference on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9698260/
Viduruwan, G, & Induranga, DKA (2021). Validation of Meteonorm 8 for energy estimation of Solar Power Plants in Sri Lanka, Using PVsyst Software. 2021 3rd International …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9580960/
Krapf, S, Kemmerzell, N, Uddin, S Khawaja Haseeb, & … (2021). Towards Scalable Economic Photovoltaic Potential Analysis Using Aerial Images and Deep Learning. Energies, mdpi.com, https://www.mdpi.com/1162650
Azaioud, H, Claeys, R, Knockaert, J, Vandevelde, L, & … (2021). A Low-Voltage DC Backbone with Aggregated RES and BESS: Benefits Compared to a Traditional Low-Voltage AC System. Energies, mdpi.com, https://www.mdpi.com/1021384
Lin, ASJ, Monson, A, Mahadevan, S, Ninan, JP, & … (2021). Observing the Sun as a star: Design and early results from the NEID solar feed. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/2112.05711
Kim, T, & Kim, J (2021). A Regional Day-Ahead Rooftop Photovoltaic Generation Forecasting Model Considering Unauthorized Photovoltaic Installation. Energies, mdpi.com, https://www.mdpi.com/1188798
Hofer, D (2021). Proactive Energy Management Through Forecasting in Off-Grid Homes/eingereicht von Daniel Hofer., epub.jku.at, https://epub.jku.at/obvulihs/id/6809982
Polo, J, Martín-Chivelet, N, Alonso-Abella, M, & … (2021). Photovoltaic generation on vertical façades in urban context from open satellite-derived solar resource data. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21005806
Waller, R (2021). Explorations in the Food-Energy Nexus: Organic Photovoltaics Applications to Greenhouse Crop Production Systems., search.proquest.com, https://search.proquest.com/openview/7f29732357c781c451db04a8d8bb41fc/1?pq-origsite=gscholar&cbl=18750&diss=y
Villegas-Mier, CG, Rodriguez-Resendiz, J, & … (2021). Artificial neural networks in MPPT algorithms for optimization of photovoltaic power systems: A review. Micromachines, mdpi.com, https://www.mdpi.com/2072-666X/12/10/1260
Buresh, K (2021). Impacts of electric vehicle charging in South Africa and photovoltaic carports as a mitigation technique., scholar.sun.ac.za, http://scholar.sun.ac.za/handle/10019.1/109807
Groissböck, M (2021). Energy hub optimization framework based on open-source software & data-review of frameworks and a concept for districts & industrial parks. International Journal of Sustainable Energy Planning …, 130.225.53.24.
Ascencio-Vásquez, J, Osorio-Aravena, JC, Brecl, K, & … (2021). Typical Daily Profiles, a novel approach for photovoltaics performance assessment: Case study on large-scale systems in Chile. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21005764
Garreau, E, Abdelouadoud, Y, Herrera, E, Keilholz, W, & … (2021). District MOdeller and SIMulator (DIMOSIM)–A dynamic simulation platform based on a bottom-up approach for district and territory energetic assessment. Energy and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0378778821006381
Tina, GM, Ventura, C, Ferlito, S, & Vito, S De (2021). A state-of-art-review on machine-learning based methods for PV. Applied Sciences, mdpi.com, https://www.mdpi.com/1232264
Barta, G, Pasztor, B, & Prava, V (2021). Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/22/7794
French, RH, Bruckman, LS, Moser, D, Lindig, E, & … (2021). Assessment of Performance Loss Rate of PV Power Systems., dspace.library.uu.nl, https://dspace.library.uu.nl/bitstream/handle/1874/415412/IEA_PVPS_T13_22_2021_Assessment_of_Performance_Loss_Rate_of_PV_Power_Systems_report.pdf?sequence=1
Rayati, M, Falco, PD, Proto, D, Bozorg, M, & Carpita, M (2021). Generation data of synthetic high frequency solar irradiance for data-driven decision-making in electrical distribution grids. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/16/4734
Song, G, Huva, R, Xing, Y, & Zhong, X (2021). WRF Model Moisture Adjustment Method: A Case Study with Wintertime Cloudy Biases in Xinjiang, China. Weather and Forecasting, journals.ametsoc.org, https://journals.ametsoc.org/view/journals/wefo/36/2/WAF-D-20-0117.1.xml
Pawluk, RE, Rezvanpour, M, Chen, Y, & She, Y (2021). A sensitivity analysis on effective parameters for sliding/melting prediction of snow cover on solar photovoltaic panels. Cold Regions Science and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0165232X21000434
Stein, J, Reise, C, Friesen, G, Maugeri, G, Urrejola, E, & … (2021). Bifacial Photovoltaic Modules and Systems: Experience and Results from International Research and Pilot Applications.., osti.gov, https://www.osti.gov/servlets/purl/1779379
Yu, MG, & Pavlak, G (2021). Assessing the Value of Uncertainty-Aware Transactive Control Framework for Commercial and Residential Buildings., docs.lib.purdue.edu, https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1379&context=ihpbc
Miller, J (2021). Evaluation of Direct Search Algorithms to Trajectory Optimization for a Perpetually Flying Fixed-Wing Solar UAV Providing Network Coverage., search.proquest.com, https://search.proquest.com/openview/7c74c4f88a2f5ac8ebf5fdeb7dcd9b74/1?pq-origsite=gscholar&cbl=18750&diss=y
Sendner, FM (2021). An energy-autonomous UAV swarm concept to support sea-rescue and maritime patrol missions in the Mediterranean sea. Aircraft Engineering and Aerospace Technology, emerald.com, https://doi.org/10.1108/AEAT-12-2020-0316
Mallapragada, DS, Junge, C, Wang, CX, Pfeifenberger, J, & … (2021). Electricity Price Distributions in Future Renewables-Dominant Power Grids and Policy Implications., nber.org, https://www.nber.org/papers/w29510
Polleux, L, Schuhler, T, Guerassimoff, G, Marmorat, JP, & … (2021). On the relationship between battery power capacity sizing and solar variability scenarios for industrial off-grid power plants. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261921009314
Keeratimahat, K, Copper, J, Bruce, A, & … (2021). Generation of synthetic 4 s utility-scale PV output time series from hourly solar irradiance data. Journal of Renewable …, aip.scitation.org, https://doi.org/10.1063/5.0033855
Lefranc, O (2021). Développement d’un outil de conception de micro-réseaux énergétiques mixtes électricité/hydrogène: prise en compte de l’impact écologique par analyse de cycle de .
Balderrama, S, Lombardi, F, Stevanato, N, Peña, G, & … (2021). Surrogate models for rural energy planning: Application to Bolivian lowlands isolated communities. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544221013566
Bruche, S (2021). Optimierung der Konfigurationen von Fernwärmeversorgungsanlagen unter Berücksichtigung der Einsatzpläne., depositonce.tu-berlin.de.
O’Donnel, ET (2021). A Comparison of the Performance and Degradation of the c-Si and a-Si Photovoltaic Systems on the NCSU Solar House., search.proquest.com, https://search.proquest.com/openview/f7906e0ae72fc21f48f14929cdcf56c0/1?pq-origsite=gscholar&cbl=18750&diss=y
Björklund, M (2021). Simulation Tool for Design of Multiple Photovoltaic Systems: Estimation of System Sizes, Grid Interaction, and Area Requirements., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1578124
Gualteros, S, & Rousse, DR (2021). Solar water pumping systems: A tool to assist in sizing and optimization. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X21005387
Stid, JT (2021). Detection and Assessment of Food, Energy, and Water Impacts of Solar Photovoltaic Co-Location in the California’s Central Valley., search.proquest.com, https://search.proquest.com/openview/0c2d284527d373371e0d7c8876eddd61/1?pq-origsite=gscholar&cbl=18750&diss=y
Mabasa, B, Lysko, MD, & Moloi, SJ (2021). Validating Hourly Satellite Based and Reanalysis Based Global Horizontal Irradiance Datasets over South Africa. Geomatics, mdpi.com, https://www.mdpi.com/2673-7418/1/4/25
Mabasa, B, Lysko, MD, Tazvinga, H, Zwane, N, & Moloi, SJ (2021). The performance assessment of six global horizontal irradiance clear sky models in six climatological regions in South Africa. Energies, mdpi.com, https://www.mdpi.com/1094838
Bansal, AS, Bansal, T, & Irwin, D (2021). A Moment in the Sun: Solar Nowcasting from Multispectral Satellite Data using Self-Supervised Learning. arXiv preprint arXiv:2112.13974, arxiv.org, https://arxiv.org/abs/2112.13974
Selga, A Gili (2021). Modelling photovoltaic system for a home energy management control., upcommons.upc.edu, https://upcommons.upc.edu/handle/2117/344904
Pillot, B, Al-Kurdi, N, Gervet, C, & Linguet, L (2021). Optimizing operational costs and PV production at utility scale: An optical fiber network analogy for solar park clustering. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261921005912
Bruck, A, Ruano, S Díaz, & Auer, H (2021). A Critical Perspective on Positive Energy Districts in Climatically Favoured Regions: An Open-Source Modelling Approach Disclosing Implications and Possibilities. Energies, mdpi.com, https://www.mdpi.com/1996-1073/14/16/4864
Mabasa, B, Lysko, MD, & Moloi, SJ (2021). Validating hourly satellite based and reanalysis based global horizontal irradiance datasets over South Africa. Geomatics 2021, 1, Firstpage–Lastpage., researchgate.net, https://www.researchgate.net/profile/Brighton-Mabasa/publication/355983262_Validating_Hourly_Satellite_Based_and_Reanalysis_Based_Global_Horizontal_Irradiance_Datasets_over_South_Africa/links/618a02f807be5f31b75b611f/Validating-Hourly-Satellite-Based-and-Reanalysis-Based-Global-Horizontal-Irradiance-Datasets-over-South-Africa.pdf
Feng, M, Bashir, N, Shenoy, P, Irwin, D, & … (2021). Model-driven Per-panel Solar Anomaly Detection for Residential Arrays. ACM Transactions on …, dl.acm.org, https://doi.org/10.1145/3460236
Murphy, CA, Schleifer, A, & Eurek, K (2021). A taxonomy of systems that combine utility-scale renewable energy and energy storage technologies. Renewable and Sustainable Energy …, Elsevier, https://www.sciencedirect.com/science/article/pii/S1364032121000083
Deng, Y (2021). Investigating Occupants’ Hold Behaviours on Smart Thermostats using Data Mining and Machine Learning., search.proquest.com, https://search.proquest.com/openview/b02fcb88a4ed28129b0c3dd0a774987a/1?pq-origsite=gscholar&cbl=18750&diss=y
Laaksonlaita, T (2021). Modelling, Identification and Control of a Renewable Hydrogen Production System for Mobility Application., research-collection.ethz.ch, https://www.research-collection.ethz.ch/handle/20.500.11850/484976
Coimbra, C, & Pedro, H (2021). HAIMOS Ensemble Forecasts for Intra-Day and Day-Ahead GHI, DNI and Ramps., osti.gov, https://www.osti.gov/biblio/1837014
Ledesma, G, Pons-Valladares, O, & Nikolic, J (2021). Real-reference buildings for urban energy modelling: A multistage validation and diversification approach. Building and Environment, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360132321004601
Rincon, JM Triana (2021). SEGUIMIENTO SOLAR PARA UN SISTEMA FOTOVOLTAICO DE PEQUEÑA ESCALA., repositorio.uniandes.edu.co, https://repositorio.uniandes.edu.co/handle/1992/53880
Stadler, K (2021). Incorporating Metadata Into the Active Learning Cycle for 2D Object Detection., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1616677
Vliet, L Van (2021). Twenty-first century wind and solar energy potential in northern Canada., dspace.library.uvic.ca, http://dspace.library.uvic.ca/handle/1828/13324
Hu, W (2021). Uncertainty Quantification for Photovoltaic Energy Production Using Analog Ensemble., search.proquest.com, https://search.proquest.com/openview/f49fe274e4c514a5ed6aec7f30be07ab/1?pq-origsite=gscholar&cbl=18750&diss=y
Ghosh, R (2021). Data-Driven Stochastic Reliability Assessment of the US Electricity Grid Under Large Penetration of Variable Renewable Energy Resources., search.proquest.com, https://search.proquest.com/openview/58144455fbd28a071dec50a7e5480759/1?pq-origsite=gscholar&cbl=18750&diss=y
Merema, B, & Saelens, D (2021). MPC framework for all-air systems in non-residential buildings., lirias.kuleuven.be, https://lirias.kuleuven.be/retrieve/637263
Plessis, A Du (2021). Short-term power output forecasting for large multi-megawatt photovoltaic systems with an aggregated low-level forecasting methodology., scholar.sun.ac.za, https://scholar.sun.ac.za/bitstream/handle/10019.1/109884/duplessis_power_2021.pdf?sequence=1
Basulto, GA Farias (2021). CIGSSe thin film photovoltaic yield improvement for operating conditions.

2020

Ransome, S. (2020). “How to use the Loss Factors and Mechanistic Performance Models effectively with PVPMC/PVLIB”, PVPMC Webinar on PV Performance Modeling Methods,
https://pvpmc.sandia.gov/download/7879/
Ильичев, ВЮ, & Юрик, ЕА (2020). расчЁт характеристик соЛНечНЫх ЭЛектростаНЦиЙ с приМеНеНиеМ проГраММНоГо МоДуЛЯ PVLIB. Научное обозрение. Технические науки, elibrary.ru, https://elibrary.ru/item.asp?id=44585467
Carballo, A González (2020). Modelado y análisis del recurso solar disponible en la superficie de un vehículo con la librería PVLIB-Python., oa.upm.es, https://oa.upm.es/id/eprint/63249
Nicolás-Martín, C, Eleftheriadis, P, & Santos-Martín, D (2020). Validation and self-shading enhancement for SoL: A photovoltaic estimation model. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20303455
Curran, AJ, Burleyson, TL, Rath, K, Xin, AS, & … (2020). Pvplr: R package implementation of multiple filters and algorithms for time-series performance loss rate analysis. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300807/
Shultz, W, Rajakaruna, M, Hites, Z, Keita, S, & … (2020). Computation of Solar Reflections from Photovoltaic Arrays. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300656/
Pelaez, S Ayala, & Deline, C (2020). pySMARTS: SMARTS Python Wrapper (Simple Model of the Atmospheric Radiative Transfer of Sunshine)., osti.gov, https://www.osti.gov/biblio/1813558
Heusinger, J, Broadbent, AM, Sailor, DJ, & Georgescu, M (2020). Introduction, evaluation and application of an energy balance model for photovoltaic modules. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X19311454
Kallio-Myers, V, Riihelä, A, Lahtinen, P, & Lindfors, A (2020). Global horizontal irradiance forecast for Finland based on geostationary weather satellite data. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20300141
Guerrero, F Tamayo (2020). Modelamiento de un sistema solar fotovoltaico a nivel utility., repositorio.uniandes.edu.co, https://repositorio.uniandes.edu.co/handle/1992/51620
Ransome, S (2020). Improvements to the IEC 61853 matrix energy rating methodology, validated with the NREL dataset. 2020 47th IEEE Photovoltaic Specialists …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300683/
Grubbs, EK, Imran, H, Agrawal, R, & … (2020). Coproduction of solar energy on maize farms—experimental validation of recent experiments. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300459/
Stein, J (2020). 2020 Q3 Project Report: PV Performance Modeling and Stakeholder Engagement.., osti.gov, https://www.osti.gov/servlets/purl/1647906
Anderson, K (2020). Maximizing yield with improved single-axis backtracking on cross-axis slopes. 2020 47th IEEE Photovoltaic Specialists …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300438/
Patel, SS, & Rix, AJ (2020). The impact of water surface albedo on incident solar insolation of a collector surface. 2020 International SAUPEC/RobMech …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9041116/
Ospina-Metaute, CC, Betancur, E, & … (2020). Optimization of the orientation of vertical surfaces based on geographic parameters for solar energy harvesting. Workshop on …, Springer, https://doi.org/10.1007/978-3-030-61834-6_39
Hansen, C, Jordan, D, Deceglie, M, Gunda, T, & … (2020). Data Cleaning for Degradation Analyses.., osti.gov, https://www.osti.gov/servlets/purl/1821842
Li, X, Mauzerall, DL, & Bergin, MH (2020). Global reduction of solar power generation efficiency due to aerosols and panel soiling. Nature Sustainability, nature.com, https://www.nature.com/articles/s41893-020-0553-2
Oh, S, Figgis, BW, & Rashkeev, S (2020). Effects of thermophoresis on dust accumulation on solar panels. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20310069
Lunel, TR, & Rousse, DR (2020). pvpumpingsystem: A Python package for modeling and sizing photovoltaic water pumping systems. Journal of Open Source Software, joss.theoj.org, https://doi.org/10.21105/joss.02637
Salani, M, Derboni, M, Rivola, D, & … (2020). Non intrusive load monitoring for demand side management. Energy …, energyinformatics.springeropen.com, https://doi.org/10.1186/s42162-020-00128-2
Adler, SW, Wiig, MS, Skomedal, Å, & … (2020). Degradation analysis of utility-scale PV plants in different climate zones. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9305229/
Landman, C, & Rix, AJ (2020). Using cloud cover forecasts for estimating a solar powered vehicles’ range. 2020 International SAUPEC/RobMech …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9041040/
Rinio, M (2020). PVCheck., pvcheck.hotell.kau.se.
Fregosi, D, Bolen, M, & Paudyal, B (2020). Analysis of Variability in Calculated Performance Loss Rates of Large-Scale PV Plants. 2020 47th IEEE Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300710/
Marion, B (2020). Clear Sky Irradiance Year-to-Year Variations and Trends. 2020 47th IEEE Photovoltaic Specialists Conference …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300858/
Fregosi, D, Libby, C, Smith, M, & … (2020). Guidance on PV Module Replacement. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300867/
Ramde, EW, Rummeny, S, Schneiders, T, & … (2020). Planning of sustainable and stable micro grids for Ghanaian hospitals with photovoltaics., researchgate.net, https://www.researchgate.net/profile/Silvan-Rummeny/publication/355477173_Planning_of_sustainable_and_stable_micro_grids_for_Ghanaian_hospitals_with_photovoltaics/links/6172b9b60be8ec17a90e24e4/Planning-of-sustainable-and-stable-micro-grids-for-Ghanaian-hospitals-with-photovoltaics.pdf
Theristis, M, Livera, A, Micheli, L, & … (2020). Modeling nonlinear photovoltaic degradation rates. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300388/
Aissaoui, A, Belhaouas, N, Hadjrioua, F, Bakria, K, & … (2020). Parameter Extraction of Two-Diode Solar PV Model Using ANN–GA Approach. … Conference in Artificial …, Springer, https://doi.org/10.1007/978-3-030-63846-7_56
Sreenath, S, Sudhakar, K, Yusop, AF, Solomin, E, & … (2020). Energy Reports.
Alvarado-M, JF, Betancur, E, & … (2020). Optimization of Single-Axis Discrete Solar Tracking. 2020 9th International …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9242726/
Theristis, M, Livera, A, Jones, CB, & … (2020). Nonlinear photovoltaic degradation rates: Modeling and comparison against conventional methods. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9095267/
Pelaez, SA, & Deline, C (2020). Bifacial_radiance: a python package for modeling bifacial solar photovoltaic systems. Journal of Open Source Software, joss.theoj.org, https://doi.org/10.21105/joss.01865
Anderson, K, & Perry, K (2020). Estimating Subhourly Inverter Clipping Loss From Satellite-Derived Irradiance Data. 2020 47th IEEE Photovoltaic Specialists …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300750/
Melo, KB, Moreira, HS, & Villalva, MG (2020). Influence of Solar Position Calculation Methods Applied to Horizontal Single-Axis Solar Trackers on Energy Generation. Energies, mdpi.com, https://www.mdpi.com/779496
Luján, E, Otero, A, Valenzuela, S, Mocskos, E, & … (2020). An integrated platform for smart energy management: the CC-SEM project. Revista Facultad de …, scielo.org.co, http://www.scielo.org.co/pdf/rfiua/n97/0120-6230-rfiua-97-41.pdf
Pouchain, F, Peronato, G, & Meunier, G (2020). A Flexible GIS-based Computational Framework for the Early-Design of District Energy Networks., proceedings.ises.org, http://proceedings.ises.org/paper/eurosun2020/eurosun2020-0100-Peronato.pdf
Willockx, B, Herteleer, B, & Cappelle, J (2020). Combining photovoltaic modules and food crops: first agrovoltaic prototype in Belgium. Renewable Energy & Power …, lirias.kuleuven.be, https://lirias.kuleuven.be/3183062?limo=0
Deceglie, MG, Silverman, TJ, & … (2020). Light and elevated temperature induced degradation (LeTID) in a utility-scale photovoltaic system. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9097396/
Dahowski, R, Newman, S, Sood, V, & … (2020). EVALUATING FACILITY ENERGY EFFICIENCY AND RESILIENCE OPPORTUNITIES WITH FEDS AND MCOR. ASHRAE Topical …, search.proquest.com, https://search.proquest.com/openview/1e19c616a6e488e0c317bc4b5d4b3f15/1?pq-origsite=gscholar&cbl=5014767
Rivera, M, & Reise, C (2020). SILICON SENSORS VS. PYRANOMETERS–REVIEW OF DEVIATIONS AND CONVERSION OF MEASURED VALUES. Presented at the 37th European PV Solar …, researchgate.net, https://www.researchgate.net/profile/Mariella-Rivera-Aguilar/publication/345726741_SILICON_SENSORS_VS_PYRANOMETERS_-REVIEW_OF_DEVIATIONS_AND_CONVERSION_OF_MEASURED_VALUES/links/5fabe2b2a6fdcc331b947718/SILICON-SENSORS-VS-PYRANOMETERS-REVIEW-OF-DEVIATIONS-AND-CONVERSION-OF-MEASURED-VALUES.pdf
Neves, LA, Leite, GC, & … (2020). ANÁLISE DO DESEMPENHO DE CÉLULAS FOTOVOLTAICAS ORGÂNICAS E INORGÂNICAS SOB DIFERENTES MASSAS DE AR UTILIZANDO SIMULAÇÃO …. … de Energia Solar …, anaiscbens.emnuvens.com.br, https://anaiscbens.emnuvens.com.br/cbens/article/view/730
Buresh, KM, Apperley, MD, & Booysen, MJ (2020). Three shades of green: Perspectives on at-work charging of electric vehicles using photovoltaic carports. Energy for Sustainable …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0973082620302441
Tsolakis, AC, Bintoudi, AD, Zyglakis, L, & … (2020). Design and real-life deployment of a smart nanogrid: a greek case study. … on Power and …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9314396/
Wu, D, Ma, X, Huang, S, Fu, T, & Balducci, P (2020). Stochastic optimal sizing of distributed energy resources for a cost-effective and resilient Microgrid. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544220303911
Øgaard, MB, Riise, HN, Haug, H, Sartori, S, & Selj, JH (2020). Photovoltaic system monitoring for high latitude locations. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20307751
Salat, A Bové (2020). Data acquisition pipeline design and HEMS integration for prosumers’ economic savings., upcommons.upc.edu, https://upcommons.upc.edu/handle/2117/334124
Mahmoudi, M, Afsharchi, M, & … (2020). Demand response management in smart homes using robust optimization. … Power Components and …, Taylor & Francis, https://doi.org/10.1080/15325008.2020.1821831
Mason, K, Reno, MJ, Blakely, L, Vejdan, S, & Grijalva, S (2020). A deep neural network approach for behind-the-meter residential PV size, tilt and azimuth estimation. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X19312101
山形裕貴, 野中尋史, & 山田昇 (2020). 深層強化学習による追尾式両面受光太陽電池アレイの最適制御. 北陸信越支部総会·講演会講演論文集 …, jstage.jst.go.jp, https://www.jstage.jst.go.jp/article/jsmehs/2020.57/0/2020.57_D031/_article/-char/ja/
Bahnmüller, LC (2020). Investigating the variability of the Utrecht Science Park PV System.
Bashir, N, Irwin, D, & Shenoy, P (2020). DeepSnow: Modeling the impact of snow on solar generation. Proceedings of the 7th ACM International …, dl.acm.org, https://doi.org/10.1145/3408308.3427620
Theristis, M, King, BH, & Stein, J (2020). CHALLENGES ASSOCIATED WITH INCONSISTENT PHOTOVOLTAIC DEGRADATION RATE ESTIMATIONS.., osti.gov, https://www.osti.gov/servlets/purl/1820292
Ranalli, J, Peerlings, EEM, & … (2020). Cloud Advection and Spatial Variability of Solar Irradiance. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300700/
Skeie, K, & Gustavsen, A (2020). Predicting solar radiation using a parametric cloud model. 12th Nordic Symposium on Building …, ntnuopen.ntnu.no, https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/2680143
Bansal, A Singh, & Irwin, D (2020). See the light: Modeling solar performance using multispectral satellite data. Proceedings of the 7th ACM International …, dl.acm.org, https://doi.org/10.1145/3408308.3427610
Byrne, RH, Nguyen, TA, Headley, A, & … (2020). Opportunities and Trends for Energy Storage Plus Solar in CAISO: 2014-2018. 2020 IEEE Power & …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9281883/
Voinov, P, Huber, P, Calatroni, A, Rumsch, A, & Paice, A (2020). Effect of Sampling Rate on Photovoltaic Self-Consumption in Load Shifting Simulations. Energies, mdpi.com, https://www.mdpi.com/857618
Lindig, S, Louwen, A, & Moser, D (2020). Outdoor PV system monitoring—input data quality, data imputation and filtering approaches. Energies, mdpi.com, https://www.mdpi.com/844338
Sánchez, H, Meza, C, Dittmann, S, & … (2020). The effect of clearance height, albedo, tilt and azimuth angle in bifacial PV energy estimation using different existing algorithms. Proceeding of the III …, researchgate.net, https://www.researchgate.net/profile/Hugo-Sanchez-Ortiz/publication/346039220_The_effect_of_clearance_height_albedo_tilt_and_azimuth_angle_in_bifacial_PV_energy_estimation_using_different_existing_algorithms/links/602bd9ee4585158939ac0bfd/The-effect-of-clearance-height-albedo-tilt-and-azimuth-angle-in-bifacial-PV-energy-estimation-using-different-existing-algorithms.pdf
Duan, J, Kooten, GC van, & Liu, X (2020). Renewable electricity grids, battery storage and missing money. Resources, Conservation and Recycling, Elsevier, https://www.sciencedirect.com/science/article/pii/S0921344920303189
Mont, S Neven-du, Heinrich, M, Pfreundt, A, & … (2020). Energy Yield Modelling of 2D and 3D Curved Photovoltaic Modules. Presented at the 37th …, ise.fraunhofer.de, https://www.ise.fraunhofer.de/content/dam/ise/de/documents/publications/conference-paper/37th-eupvsec-2020/Neven-du_Mont_4BO136.pdf
Willockx, B, Herteleer, B, & Cappelle, J (2020). Techno-economic study of agrovoltaic systems focusing on orchard crops. EU PVSEC Proceedings, lirias.kuleuven.be, https://lirias.kuleuven.be/3183068?limo=0
Huang, J, Rikus, L, & Qin, Y (2020). Probabilistic solar irradiance forecasting using numerical weather prediction ensembles over Australia. 2020 47th IEEE Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300836/
Huang, J, Jones, B, Thatcher, M, & … (2020). Temperature impacts on utility-scale solar photovoltaic and wind power generation output over Australia under RCP 8.5. Journal of Renewable …, aip.scitation.org, https://doi.org/10.1063/5.0012711
Zimmerman, R, Panda, A, & Bulović, V (2020). Techno-economic assessment and deployment strategies for vertically-mounted photovoltaic panels. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261920306619
Maitanova, N, Telle, JS, Hanke, B, Grottke, M, Schmidt, T, & … (2020). A machine learning approach to low-cost photovoltaic power prediction based on publicly available weather reports. energies, mdpi.com, https://www.mdpi.com/635914
Yang, D (2020). Choice of clear-sky model in solar forecasting. Journal of Renewable and Sustainable Energy, aip.scitation.org, https://doi.org/10.1063/5.0003495
Jones, CB, Theristis, M, Stein, JS, & … (2020). Feature selection of photovoltaic system data to avoid misclassification of fault conditions. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300786/
Refat, KH, & Sajjad, RN (2020). Prospect of achieving net-zero energy building with semi-transparent photovoltaics: A device to system level perspective. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S030626192031271X
UCHIDA, T, TOBISAKA, R, & YAMADA, N (2020). Optimal Control of Tracking Bifacial Photovoltaic System by Using Deep Reinforcement Learning. … 学会講演論文集 (CD-ROM), jglobal.jst.go.jp, https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002267076536014
Berardi, U, & Graham, J (2020). Investigation of the impacts of microclimate on PV energy efficiency and outdoor thermal comfort. Sustainable Cities and Society, Elsevier, https://www.sciencedirect.com/science/article/pii/S2210670720306235
Orazi, T (2020). Analysis of fault performanceof heat pump-PV systems., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1507663
Liu, C, Shi, J, Chen, H, & Chen, L (2020). Estimating Aggregated Behind-the-Meter Photovoltaic Generation Using Smart Meter Data. 2020 IEEE Power & Energy …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9281564/
Prilliman, M, Stein, JS, Riley, D, & … (2020). Transient Weighted Moving Average Model of Photovoltaic Module Back-Surface Temperature. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300872/
Kunaifi, K, Reinders, A, Lindig, S, Jaeger, M, & Moser, D (2020). Operational performance and degradation of PV systems consisting of six technologies in three climates. Applied Sciences, mdpi.com, https://www.mdpi.com/789854
Brown, PR, & O’Sullivan, FM (2020). Spatial and temporal variation in the value of solar power across United States electricity markets. Renewable and Sustainable Energy Reviews, Elsevier, https://www.sciencedirect.com/science/article/pii/S1364032119308020
Feng, C, & Zhang, J (2020). SolarNet: A sky image-based deep convolutional neural network for intra-hour solar forecasting. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20303285
Javu, L, Winkler, H, & Roro, KT (2020). Validating clear-sky irradiance models in five South African locations., 146.64.81.179, http://146.64.81.179/dspace/handle/10204/11889
Landman, C (2020). GHI forecasting to extend the range of a solar powered vehicle., scholar.sun.ac.za, http://scholar.sun.ac.za/handle/10019.1/107956
Sreenath, S, Sudhakar, K, Yusop, AF, Solomin, E, & … (2020). Solar PV energy system in Malaysian airport: Glare analysis, general design and performance assessment. Energy Reports, Elsevier, https://www.sciencedirect.com/science/article/pii/S2352484719304603
Shivam, K, Tzou, JC, & Wu, SC (2020). Multi-Objective Sizing Optimization of a Grid-Connected Solar–Wind Hybrid System Using Climate Classification: A Case Study of Four Locations in Southern Taiwan. Energies, mdpi.com, https://www.mdpi.com/717668
Ripalda, JM, Chemisana, D, Llorens, JM, & … (2020). Impact of spectral effects on photovoltaic energy production: A case study in the United States. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/2003.08871
Carpintero-Rentería, M, Santos-Martín, D, & … (2020). Photovoltaic electric power estimation with a machine learning algorithm based on neural networks and validated with deterministic approaches. … on Environment and …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9160751/
Claeys, R, Protopapadaki, C, Saelens, D, & … (2020). A Data-Driven Approach to Assessing and Improving Stochastic Residential Load Modeling for District-Level Simulations and PV Integration. … Methods Applied to …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9183420/
Kempe, MD, Holsapple, D, & Miller, DC (2020). Using Meteorological Data to Evaluate Worldwide PV Degradation Rates., osti.gov, https://www.osti.gov/biblio/1606134
Newman, S, Shiozawa, K, Follum, J, Barrett, E, & … (2020). A comparison of PV resource modeling for sizing microgrid components. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148120313197
Azaioud, H, Desmet, J, & Vandevelde, L (2020). Benefit Evaluation of PV Orientation for Individual Residential Consumers. Energies, mdpi.com, https://www.mdpi.com/845582
Hafez, AA, Nassar, YF, Hammdan, MI, & … (2020). Technical and economic feasibility of utility-scale solar energy conversion systems in Saudi Arabia. Iranian Journal of Science …, Springer, https://doi.org/10.1007/s40998-019-00233-3
Mabasa, B, Lysko, MD, Tazvinga, H, Mulaudzi, ST, & … (2020). The ångström–prescott regression coefficients for six climatic zones in South Africa. Energies, mdpi.com, https://www.mdpi.com/858630
Catalina, A, Torres-Barrán, A, Alaíz, CM, & … (2020). Machine learning nowcasting of PV energy using satellite data. Neural Processing …, Springer, https://doi.org/10.1007/s11063-018-09969-1
Byrne, RH, Nguyen, TA, Headley, A, & … (2020). Opportunities and Trends for Energy Storage Plus Solar in the CAISO Real-Time Market: 2014-2018. … Symposium on Power …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9161956/
Razo, DE Guzman, Müller, B, Madsen, H, & Wittwer, C (2020). A genetic algorithm approach as a self-learning and optimization tool for PV power simulation and digital twinning. Energies, mdpi.com, https://www.mdpi.com/930134
Meng, B, Loonen, RCGM, & Hensen, JLM (2020). Data-driven inference of unknown tilt and azimuth of distributed PV systems. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20310306
Cavagnaro, RJ, Copping, AE, Green, R, & … (2020). Powering the blue economy: progress exploring marine renewable energy integration with ocean observations. Marine Technology …, ingentaconnect.com, https://www.ingentaconnect.com/content/mts/mtsj/2020/00000054/00000006/art00012
Bansal, AS, & Irwin, D (2020). Exploiting satellite data for solar performance modeling. 2020 IEEE International Conference on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9302984/
Lorente, JL, Liu, X, & Morrow, DJ (2020). Worldwide evaluation and correction of irradiance measurements from personal weather stations under all-sky conditions. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20306873
Skomedal, ÅF, Aarseth, BL, Haug, H, Selj, J, & Marstein, ES (2020). How much power is lost in a hot-spot? A case study quantifying the effect of thermal anomalies in two utility scale PV power plants. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20311245
Flett, GH, Tuohy, PG, & Lyden, A (2020). Towards a smart community evaluation and implementation toolkit-low-cost mini-district predictive controls with flexible tariffs. uSIM2020 Building to …, strathprints.strath.ac.uk, https://strathprints.strath.ac.uk/74792/
Skomedal, Å, Deceglie, M, Haug, H, & Marstein, ES (2020). ITERATIVE AND SELF-CONSISTENT ESTIMATION OF DEGRADATION AND SOILING LOSS IN PV SYSTEMS–A CASE STUDY., researchgate.net, https://www.researchgate.net/profile/Asmund_Skomedal2/publication/344930548_Iterative_and_Self-Consistent_Estimation_of_Degradation_and_Soiling_Loss_in_PV_Systems_-_a_Case_Study/links/5f997aefa6fdccfd7b84e488/Iterative-and-Self-Consistent-Estimation-of-Degradation-and-Soiling-Loss-in-PV-Systems-a-Case-Study.pdf
Kooten, GC van, Withey, P, & Duan, J (2020). How big a battery?. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148119309553
Englmair, G, Larsen, AS, Kong, W, & Vajda, B (2020). Reuse of brine from desalination (NoBriner)., orbit.dtu.dk, https://orbit.dtu.dk/files/232267303/Byg_R_446_final.pdf
Cros, S, Badosa, J, Szantaï, A, & Haeffelin, M (2020). Reliability predictors for solar irradiance satellite-based forecast. Energies, mdpi.com, https://www.mdpi.com/867950
Gupta, R, Sossan, F, & Paolone, M (2020). Grid-aware distributed model predictive control of heterogeneous resources in a distribution network: Theory and experimental validation. IEEE Transactions on Energy …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9163265/
Jones, CB, Lave, M, Reno, MJ, Darbali-Zamora, R, & … (2020). Volt-var curve reactive power control requirements and risks for feeders with distributed roof-top photovoltaic systems. Energies, mdpi.com, https://www.mdpi.com/802456
Uribe, D Rueda (2020). Short-term solar power forecasting using different machine learning models., repositorio.uniandes.edu.co, https://repositorio.uniandes.edu.co/handle/1992/48972
Liu, S, Maldonado, DA, & Constantinescu, EM (2020). Probabilistic analysis of masked loads with aggregated photovoltaic production. Electric Power Systems …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0378779620304739
Micheli, L, Theristis, M, Talavera, DL, Almonacid, F, & … (2020). Photovoltaic cleaning frequency optimization under different degradation rate patterns. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148120317870
Simpson, L (2020). Addressing Soiling: From Interface Chemistry to Practicality., osti.gov, https://www.osti.gov/biblio/1659855
PATIL, PR, DHAMALE, K, PERIS, SL, REDDY, BUK, & … (2020). ENERGY SYSTEM MODELLING OF DENMARK USING OEMOF., researchgate.net, https://www.researchgate.net/profile/Parag-Patil/project/Energy-Systems-Modelling-of-Denmark-for-the-year-2030/attachment/5eb3e79a4f9a520001e4f0e5/AS:888509321711616@1588848538242/download/Energy+System+Modelling+Denmark.pdf
Taufiqurrahman, A, Putrada, AG, & … (2020). Decision Tree Regression with AdaBoost Ensemble Learning for Water Temperature Forecasting in Aquaponic Ecosystem. 2020 6th International …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9339669/
Coppitters, D, Paepe, W De, & Contino, F (2020). Robust design optimization and stochastic performance analysis of a grid-connected photovoltaic system with battery storage and hydrogen storage. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544220319058
Mallapragada, DS, Gençer, E, Insinger, P, & … (2020). Can industrial-scale solar hydrogen supplied from commodity technologies Be cost competitive by 2030?. Cell Reports Physical …, Elsevier, https://www.sciencedirect.com/science/article/pii/S2666386420301855
Feng, C, & Zhang, J (2020). SolarNet: A Deep Convolutional Neural Network for Solar Forecasting via Sky Images. 2020 IEEE Power & Energy Society …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9087703/
Pistellato, M, Traviglia, A, & Bergamasco, F (2020). Geolocating Time: Digitisation and Reverse Engineering of a Roman Sundial. European Conference on …, Springer, https://doi.org/10.1007/978-3-030-66096-3_11
Schubnel, B, Carrillo, RE, Taddeo, P, & … (2020). State-space models for building control: how deep should you go?. Journal of Building …, Taylor & Francis, https://doi.org/10.1080/19401493.2020.1817149
Ghotge, R, Snow, Y, Farahani, S, Lukszo, Z, & Wijk, A van (2020). Optimized scheduling of EV charging in solar parking lots for local peak reduction under EV demand uncertainty. Energies, mdpi.com, https://www.mdpi.com/661080
Guariso, G, Nunnari, G, & Sangiorgio, M (2020). Multi-step solar irradiance forecasting and domain adaptation of deep neural networks. Energies, mdpi.com, https://www.mdpi.com/787066
Awara, S, Lynch, M, Pfenninger, S, Schell, K, & … (2020). Capacity Value of Solar Power and Other Variable Generation. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/2007.09015
Carrillo, RE, Leblanc, M, Schubnel, B, Langou, R, & … (2020). High-Resolution PV Forecasting from Imperfect Data: A Graph-Based Solution. Energies, mdpi.com, https://www.mdpi.com/879112
Toquica, D, Agbossou, K, Malhamé, R, Henao, N, & … (2020). Adaptive machine learning for automated modeling of residential prosumer agents. Energies, mdpi.com, https://www.mdpi.com/707624
Li, M, Liao, Z, & Coimbra, CFM (2020). Spectral solar irradiance on inclined surfaces: A fast Monte Carlo approach. Journal of Renewable and …, aip.scitation.org, https://doi.org/10.1063/5.0011635
Salamanis, AI, Xanthopoulou, G, Bezas, N, Timplalexis, C, & … (2020). Benchmark Comparison of Analytical, Data-Based and Hybrid Models for Multi-Step Short-Term Photovoltaic Power Generation Forecasting. Energies, mdpi.com, https://www.mdpi.com/891658
Villena, MM De, Boukas, I, Mathieu, S, & … (2020). A framework to integrate flexibility bids into energy communities to improve self-consumption. 2020 IEEE Power & …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9282036/
Hendrikx, NY (2020). Short term solar irradiance time-series forecasting with machine learning.
Deline, C, White, R, Muller, M, Anderson, K, & … (2020). PV fleet performance data initiative program and methodology. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300583/
Alam, SMS, Florita, AR, & Hodge, BM (2020). Distributed PV generation estimation using multi-rate and event-driven Kalman kriging filter. IET Smart Grid, ieeexplore.ieee.org.
KHAN, MA, & NAVEEN, F (2020). Performance Evaluation of distributed Solar PV Installations., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1503695
Summers, A, Johnson, J, Darbali-Zamora, R, Hansen, C, & … (2020). A comparison of DER voltage regulation technologies using real-time simulations. Energies, mdpi.com, https://www.mdpi.com/765662
Nespoli, A, & Niccolai, A (2020). Solar position identification on sky images for photovoltaic nowcasting applications. 2020 IEEE International Conference on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9160490/
Böök, H, Poikonen, A, Aarva, A, Mielonen, T, & … (2020). Photovoltaic system modeling: A validation study at high latitudes with implementation of a novel DNI quality control method. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20304540
Swaminathan, S, Pavlak, GS, & Freihaut, J (2020). Sizing and dispatch of an islanded microgrid with energy flexible buildings. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261920308679
Heery, EC, Lian, KY, Loke, LHL, Tan, HTW, & … (2020). Evaluating seaweed farming as an eco-engineering strategy for ‘blue’shoreline infrastructure. Ecological Engineering, Elsevier, https://www.sciencedirect.com/science/article/pii/S0925857420301452
Oliva, Á Benito (2020). Estudio comparativo de distintas estrategias de seguimiento del punto de máxima potencia de un generador fotovoltaico., oa.upm.es, https://oa.upm.es/id/eprint/64320
Troitzsch, S, Sreepathi, BK, Huynh, TP, Moine, A, Hanif, S, & … (2020). Optimal electric-distribution-grid planning considering the demand-side flexibility of thermal building systems for a test case in Singapore. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261920304293
Booij, D (2020). Techno-economic analysis of self-consumption in the residential sector and the associated effect on the electricity network.
Yoshizawa, S, & Hayashi, Y (2020). Advanced voltage control based on short-time ahead voltage fluctuation estimation in distribution system. Electric Power Systems Research, Elsevier, https://www.sciencedirect.com/science/article/pii/S0378779620303631
Yang, D, & Gueymard, CA (2020). Ensemble model output statistics for the separation of direct and diffuse components from 1-min global irradiance. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X2030582X
Feng, M, Bashir, N, Shenoy, P, Irwin, D, & … (2020). Sundown: Model-driven per-panel solar anomaly detection for residential arrays. Proceedings of the 3rd …, dl.acm.org, https://doi.org/10.1145/3378393.3402257
Bekirov, EA, Asanov, MM, & … (2020). Algorithm and program for calculating the facility’s power supply system based on photovoltaic modules. IOP Conference Series …, iopscience.iop.org, https://doi.org/10.1088/1757-899X/791/1/012053
Siemenn, AE, Looney, EE, & … (2020). Does Energy Yield Increase when Conjoining a PV Module with a Thermoelectric Device?. 2020 47th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9300359/
Spiliotis, K, Gonçalves, JE, Saelens, D, Baert, K, & … (2020). Electrical system architectures for building-integrated photovoltaics: A comparative analysis using a modelling framework in Modelica. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919319348
BARALIS, E, & Talakoobi, T (2020). Solar Power Forecast Using Artificial Neural Network Techniques., webthesis.biblio.polito.it, https://webthesis.biblio.polito.it/15873/1/tesi.pdf
Yadavally, A (2020). An Exploration of Machine Learning Based Day-Ahead Solar Irradiance Forecasting Methodologies., search.proquest.com, https://search.proquest.com/openview/8b4b7f72a584e4cde06e6434e572f211/1?pq-origsite=gscholar&cbl=44156
Louw, J (2020). Modelling and simulation of bifacial PV modules by implementing the ray tracing technique., scholar.sun.ac.za, http://scholar.sun.ac.za/handle/10019.1/107857
Refat, KH (2020). Performance estimate of semi transparent photovoltaics through modeling and characterization., lib.buet.ac.bd, http://lib.buet.ac.bd:8080/xmlui/handle/123456789/5840
Yang, D, & Liu, L (2020). Solar project financing, bankability, and resource assessment. Sustainable Energy Solutions for Remote Areas in the …, Springer, https://doi.org/10.1007/978-3-030-41952-3_8
Padey, P, Goulouti, K, Saint-Pierre, D Beloin, & … (2020). Dynamic Life Cycle Assessment of the building electricity demand. Proceedings of 21 …, researchgate.net, https://www.researchgate.net/profile/Sebastien-Lasvaux/publication/349139291_Dynamic_Life_Cycle_Assessment_of_the_building_electricity_demand/links/60225b5445851589399073e0/Dynamic-Life-Cycle-Assessment-of-the-building-electricity-demand.pdf
Prilliman, M (2020). Moving-Average Transient Model for Predicting the Back-surface Temperature of Photovoltaic Modules., search.proquest.com, https://search.proquest.com/openview/899282f03b31c818657463002da2dcc3/1?pq-origsite=gscholar&cbl=18750&diss=y
Riedel-Lyngskær, N, Berrian, D, Mira, D Alvarez, & … (2020). Validation of Bifacial Photovoltaic Simulation Software against Monitoring Data from Large-Scale Single-Axis Trackers and Fixed Tilt Systems in Denmark. Applied Sciences, mdpi.com, https://www.mdpi.com/904962
Kelly, NB (2020). Grid edge system simulation and evaluation tool (GESSO): Development of a tool for the modelling and design of distributed cooperating microgrids., researchcommons.waikato.ac.nz, https://researchcommons.waikato.ac.nz/handle/10289/13420
Walch, A, Castello, R, Mohajeri, N, & Scartezzini, JL (2020). Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919320914
Kim, M, Song, H, & Kim, Y (2020). Direct short-term forecast of photovoltaic power through a comparative study between COMS and Himawari-8 meteorological satellite images in a deep neural …. Remote Sensing, mdpi.com, https://www.mdpi.com/776500
Rust, C, Smit, MA, & Schoeman, D (2020). Benefits of a photo voltaic solar system in a private dwelling., 146.64.81.179, http://146.64.81.179/dspace/handle/10204/11706
Komrit, S (2020). Comparative analyses of solar photovoltaic, wind, and hybrid energy systems: case study of Thailand., scholarworks.calstate.edu, https://scholarworks.calstate.edu/downloads/8910k0440
Pillot, B, Al-Kurdi, N, Gervet, C, & Linguet, L (2020). An integrated GIS and robust optimization framework for solar PV plant planning scenarios at utility scale. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919319440
Pun, KB (2020). Short term forecasting of solar power with machine learning and time series techniques., soar.wichita.edu, https://soar.wichita.edu/handle/10057/19764
Kirchsteiger, H, & Steinmaurer, G (2020). Optimal Energy Management of Residential Solar PV with Battery Storage: Effects of Fast Load and Generation Transients. 2020 7th International …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9263853/
Niccolai, A, & Nespoli, A (2020). Sun Position Identification in Sky Images for Nowcasting Application. Forecasting, mdpi.com, https://www.mdpi.com/891152
Shaffery, P, Habte, A, Netto, M, Andreas, A, & Krishnan, V (2020). Automated construction of clear-sky dictionary from all-sky imager data. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20311117
Jiménez, JR Pungil (2020). Flujos de potencia probabilísticos considerando centrales fotovoltaicas empleando el método de montecarlo., bibdigital.epn.edu.ec, http://bibdigital.epn.edu.ec/handle/15000/21218
Freitas, J de Sousa, Cronemberger, J, Soares, RM, & … (2020). Modeling and assessing BIPV envelopes using parametric Rhinoceros plugins Grasshopper and Ladybug. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148120308417
Zambrano, AF, & Giraldo, LF (2020). Solar irradiance forecasting models without on-site training measurements. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148120301142
Kong, W, Jia, Y, Dong, ZY, Meng, K, & Chai, S (2020). Hybrid approaches based on deep whole-sky-image learning to photovoltaic generation forecasting. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261920313465
Copping, AE, Green, RE, Cavagnaro, RJ, Jenne, DS, & … (2020). Powering the Blue Economy-Ocean Observing Use Cases Report., osti.gov, https://www.osti.gov/biblio/1700536
Stainsby, W, Zimmerle, D, & Duggan, GP (2020). A method to estimate residential PV generation from net-metered load data and system install date. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261920304074
Bloch, LB (2020). Optimal path to a high share of distributed PV in low-voltage distribution grids., infoscience.epfl.ch, https://infoscience.epfl.ch/record/279521
Dimanchev, E, Hodge, J, & Parsons, J (2020). Two-Way Trade in Green Electrons: Deep Decarbonization of the Northeastern US and the Role of Canadian Hydropower., dspace.mit.edu, https://dspace.mit.edu/handle/1721.1/130577
Júnior, EFM, & Rüther, R (2020). The influence of the solar radiation database and the photovoltaic simulator on the sizing and economics of photovoltaic-diesel generators. Energy Conversion and Management, Elsevier, https://www.sciencedirect.com/science/article/pii/S0196890420302752
Pinna, A, & Massidda, L (2020). A procedure for complete census estimation of rooftop photovoltaic potential in urban areas. Smart Cities, mdpi.com, https://www.mdpi.com/795944
Hoyo, M Del, Rondanelli, R, & Escobar, R (2020). Significant decrease of photovoltaic power production by aerosols. The case of Santiago de Chile. Renewable Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S096014811931496X
Rougerie-Durocher, S, Philion, V, & Szalatnay, D (2020). Measuring and modelling of apple flower stigma temperature as a step towards improved fire blight prediction. Agricultural and Forest …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0168192320302732
Yang, D, Alessandrini, S, Antonanzas, J, & … (2020). Verification of deterministic solar forecasts. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X20303947
Besio, A Inzunza (2020). Distributional effects of net metering policies and residential solar plus behind-the-meter storage adoption., oastats.mit.edu, http://oastats.mit.edu/handle/1721.1/127171
Möller, C (2020). Speicherbedarf und Systemkosten in der Stromversorgung für energieautarke Regionen und Quartiere., dokumente.ub.tu-clausthal.de, https://dokumente.ub.tu-clausthal.de/servlets/MCRFileNodeServlet/clausthal_derivate_00001343/Db114514.pdf
Guambaña, GF Chávez (2020). Máxima transferencia de potencia de un sistema de micro generación fotovoltaica por medio de PSO y modelación dinámica por medio de Vensim., dspace.ups.edu.ec, https://dspace.ups.edu.ec/handle/123456789/19272
Nespoli, L, & Medici, V (2020). Multivariate Boosted Trees and Applications to Forecasting and Control. arXiv preprint arXiv:2003.03835, arxiv.org, https://arxiv.org/abs/2003.03835
Golubev, T (2020). Multi-physics modeling and simulation of photovoltaic devices and systems., search.proquest.com, https://search.proquest.com/openview/63ac993f14fbbab09d4adeb08d823a68/1?pq-origsite=gscholar&cbl=18750&diss=y
Tong, X, Liu, S, Yan, J, Broesicke, OA, Chen, Y, & … (2020). Thermolytic osmotic heat engine for low-grade heat harvesting: Thermodynamic investigation and potential application exploration. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919318793
Durusoy, B (2020). Description and verification of a model to calculate the efficiency of a bifacial PV module using theoretical and experimental observations., open.metu.edu.tr, https://open.metu.edu.tr/bitstream/handle/11511/45370/index.pdf
Pravettoni, M (2020). Module Deployment and Energy Rating. Solar Cells and Modules, Springer, https://doi.org/10.1007/978-3-030-46487-5_10
Balderrama, JGP, Subieta, SB, Lombardi, F, & … (2020). Incorporating high-resolution demand and techno-economic optimization to evaluate micro-grids into the Open Source Spatial Electrification Tool (OnSSET). Energy for Sustainable …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0973082620302180
Muschner, C (2020). An Open Source Energy Modelling Framework Comparison of OSeMOSYS and oemof., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1444892
Ganchala, JD Campoverde (2020). Gestión de la demanda eléctrica mediante modelos bipartitos para una óptima respuesta a la demanda en usuarios residenciales., dspace.ups.edu.ec, https://dspace.ups.edu.ec/handle/123456789/18351
Johansson, K, & Ljungek, F (2020). ADDRESSING GRID CAPACITY THROUGH TIME SERIES: Deriving a data driven and scenario-based method for long-term planning of local grids.., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1441742
Silva, M (2020). Modelado y estudio del impacto de sombras sobre paneles solares fotovoltaicos., rinfi.fi.mdp.edu.ar, http://rinfi.fi.mdp.edu.ar/handle/123456789/441
Ruiz, G Matas (2020). Desarrollo de una plataforma de datos abiertos para la estación meteorológica del Instituto de Energía Solar., oa.upm.es, https://oa.upm.es/id/eprint/63112
Brüls, M (2020). FAULT DETECTION FOR SMALL-SCALE PHOTOVOLTAIC POWER INSTALLATIONS: A Case Study of a Residential Solar Power System., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1525224
Kam, MJ (2020). Driving solar: Integrating photovoltaic systems, electric vehicles, and consumer behaviour in models of smart energy systems., dspace.library.uu.nl, https://dspace.library.uu.nl/handle/1874/391795
Ismail, Y (2020). Model-based Fault Detection for Grid Connected Photovoltaic Plants from Monitoring Data., elib.dlr.de, https://elib.dlr.de/130907/1/Master_s_thesis_final.pdf
Wu, Y (2020). System Design Strategy & Energy Yield Analysis for Solar PV Application in an Urban Community with Constrained Rooftop Area., search.proquest.com, https://search.proquest.com/openview/581482703a727923afd467d575cc3e79/1?pq-origsite=gscholar&cbl=18750&diss=y
Júnior, EF Moscardini (2020). A influência do banco de dados solarimétricos e do simulador fotovoltaico no dimensionamento e na economia de combustível em usinas fotovoltaico-diesel., repositorio.ufsc.br, https://repositorio.ufsc.br/handle/123456789/215893

2019

Holmgren, W, Lorenzo, T, Krien, U, Mikofski, M, & Hansen, C (2019). Pvlib/pvlib-python: V0. 6.3. Zenodo
Holmgren, W, Lorenzo, T, Krien, U, Mikofski, M, Hansen, C, & … (2019). pvlib/pvlib-python v0. 7.0.
Hansen, C, & Riley, D (2019). Open-source Software for Solar Power: Update.., osti.gov, https://www.osti.gov/servlets/purl/1640607
Ransome, S. (2019). “Quantifying Long Term PV Performance and Degradation under Real Outdoor and IEC 61853 Test Conditions Using High Quality Module IV Measurements 5CV.4.35”, 36th EU PVSEC Sep 2019 Marseille, http://www.steveransome.com/PUBS/1909_5CV4_35_PVSEC36_Marseille_Ransome_PPT.pdf
Perna, A, Grubbs, EK, Agrawal, R, & … (2019). Design considerations for agrophotovoltaic systems: maintaining PV area with increased crop yield. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981324/
González, M Moreno (2019). Modelado de sistemas fotovoltaicos de concentración para la biblioteca de código abierto PVLIB-Python., oa.upm.es, https://oa.upm.es/id/eprint/63168
Dyamond, WP, & Rix, AJ (2019). Detecting Anomalous Events for a Grid Connected PV Power Plant Using Sensor Data. 2019 Southern African Universities …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8704812/
DeFreitas, Z, Ramirez, A, Huang, B, & … (2019). Evaluating the accuracy of various irradiance models in detecting soiling of irradiance sensors. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981194/
Landelius, T, Andersson, S, & … (2019). Modelling and forecasting PV production in the absence of behind‐the‐meter measurements. Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.3117
Holmgren, WF, Lorenzo, AT, & … (2019). Benchmark Solar Power Forecasts. 99th American …, solarforecastarbiter.org, https://solarforecastarbiter.org/assets/posters/AMS%202019%20Benchmark%20Solar%20Power%20Forecasts.pdf
Abuella, M (2019). Wind and Solar Energy Resources Modeling and Analysis., researchgate.net, https://www.researchgate.net/profile/Mohamed-Abuella/publication/335653075_Wind_and_Solar_Energy_Resources_Modeling_and_Analysis/links/5d85571592851ceb791fbb60/Wind-and-Solar-Energy-Resources-Modeling-and-Analysis.pdf
Nascimento, M, Avila, AB de, Reiser, R, Pilla, ML, & … (2019). Towards Memory Access Optimization in Quantum Computing.. EUSFLAT …, researchgate.net, https://www.researchgate.net/profile/Renata-Reiser/publication/335807320_Towards_Memory_Access_Optimization_in_Quantum_Computing/links/5ff4ade345851553a0227092/Towards-Memory-Access-Optimization-in-Quantum-Computing.pdf
Bashir, N, Chen, D, Irwin, D, & … (2019). Solar-TK: A Data-driven Toolkit for Solar PV Performance Modeling and Forecasting. 2019 IEEE 16th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9077525/
Ellis, BH, Deceglie, M, & Jain, A (2019). Automatic Detection of Clear-Sky Periods From Irradiance Data. IEEE Journal of Photovoltaics, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8727494/
Oliveira, TP, Narvaez, DI, & Villalva, MG (2019). Comparison of Irradiance Decomposition and Energy Production Methods in a Solar Photovoltaic System. International Journal of …, researchgate.net, https://www.researchgate.net/profile/Shukla-Poddar/post/How_can_I_calculate_the_solar_power_output_using_irradiance/attachment/6141a8d0181c2e4f4a886163/AS%3A1068212053610496%401631693008346/download/comparison-of-irradiance-decomposition-and-energy-production-methods-in-a-solar-photovoltaic-system.pdf
Deceglie, MG, Jordan, DC, Nag, A, & … (2019). Fleet-scale energy-yield degradation analysis applied to hundreds of residential and nonresidential photovoltaic systems. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8598843/
Driesse, A, & Patel, N (2019). Cross-validation of PV System Simulation Software. … of the 36th European Photovoltaic Solar …, researchgate.net, https://www.researchgate.net/profile/Anton-Driesse/publication/335842590_Cross-validation_of_PV_System_Simulation_Software/links/5d84d422a6fdcc8fd6ff3180/Cross-validation-of-PV-System-Simulation-Software.pdf
Meyers, B, Tabone, M, & Kara, EC (2019). Statistical clear sky fitting algorithm. arXiv preprint arXiv:1907.08279, arxiv.org, https://arxiv.org/abs/1907.08279
Curran, AJ, Jones, CB, Lindig, S, Stein, J, & … (2019). Performance loss rate consistency and uncertainty across multiple methods and filtering criteria. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8980928/
Freeman, JM, DiOrio, N, Blair, N, Guittet, D, Gilman, P, & … (2019). Improvement and validation of the system advisor model., osti.gov, https://www.osti.gov/biblio/1495693
Patel, SS, & Rix, AJ (2019). Water surface albedo modelling for floating PV plants. Europe, sasec.org.za, https://sasec.org.za/papers2019/8.pdf
Carmignani, CK (2019). CO School of Mines-Sandia-PV & Materials Tech-Python.., osti.gov, https://www.osti.gov/servlets/purl/1644475
Silva, MK (2019). Estudo de modelos matemáticos para análise da radiação solar e desenvolvimento de ferramenta para modelagem e simulação de sistemas fotovoltaicos., [sn]
Whitmire, C, Rokad, B, & Crumley, C (2019). Origami Inspired Solar Panel Design. arXiv preprint arXiv:1905.06012, arxiv.org, https://arxiv.org/abs/1905.06012
Khan, B (2019). Assessment of statistical relationship between cloud indices and relative photovoltaic (PV) production data., lutpub.lut.fi, https://lutpub.lut.fi/handle/10024/160174
Gunda, T, & Cai, M (2019). Foresee the Future: Using Machine Learning, Climate, and Site Characteristics to Predict PV Solar Plant Generation., osti.gov, https://www.osti.gov/biblio/1592882
Vivian, J, & Mazzi, N (2019). An algorithm for the optimal management of air-source heat pumps and PV systems. Journal of Physics: Conference Series, iopscience.iop.org, https://doi.org/10.1088/1742-6596/1343/1/012069
Zuiker, A (2019). A comparative study of PV simulation and machine learning models on a macrolevel and microlevel.
Camargo, L Ramirez, Nitsch, F, Gruber, K, Valdes, J, & … (2019). Potential analysis of hybrid renewable energy systems for self-sufficient residential use in Germany and the Czech Republic. Energies, mdpi.com, https://www.mdpi.com/565836
Pelaez, SA, Deline, C, Greenberg, P, & … (2019). Model and validation of single-axis tracking with bifacial PV. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8644027/
Hansen, CW, Holmgren, WF, Tuohy, A, & … (2019). The Solar Forecast Arbiter: An Open Source Evaluation Framework for Solar Forecasting. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8980713/
Kosmadakis, I, & Elmasides, C (2019). Towards performance enhancement of hybrid power supply systems based on renewable energy sources. Energy Procedia, Elsevier, https://www.sciencedirect.com/science/article/pii/S1876610218312384
Bruckman, LS (2019). Transformative Opportunities from Data Science and Big Data Analytics: Applied to Photovoltaics. The Electrochemical Society Interface, iopscience.iop.org, https://doi.org/10.1149/2.F07191if
Kim, T, Ko, W, & Kim, J (2019). Analysis and impact evaluation of missing data imputation in day-ahead PV generation forecasting. Applied Sciences, mdpi.com, https://www.mdpi.com/391836
Cormode, D, Croft, N, Hamilton, R, & … (2019). A method for error compensation of modeled annual energy production estimates introduced by intra-hour irradiance variability at PV power plants with a high DC to …. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981206/
Øgaard, MB, Skomedal, Å, & Selj, JHK (2019). Performance evaluation of monitoring algorithms for photovoltaic systems., ife.brage.unit.no, https://ife.brage.unit.no/ife-xmlui/bitstream/handle/11250/2632573/5CV.4.30_paper_MB%25C3%25982019.pdf?sequence=2
Razo, DEG, Müller, B, & Wittwer, C (2019). Ein Modellansatz zur Bestimmung von Direkt-und Diffusanteil der Einstrahlung auf die PV-Modulebene., researchgate.net, https://www.researchgate.net/profile/Dorian-Esteban-Guzman-Razo/publication/333293000_Ein_Modellansatz_zur_Bestimmung_von_Direkt-und_Diffusanteil_der_Einstrahlung_auf_die_PV-Modulebene/links/5ce56fe5458515712ebb66e6/Ein-Modellansatz-zur-Bestimmung-von-Direkt-und-Diffusanteil-der-Einstrahlung-auf-die-PV-Modulebene.pdf
Huang, J, Khan, MM, Qin, Y, & … (2019). Hybrid Intra-hour Solar PV Power Forecasting using Statistical and Skycam-based Methods. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8980732/
Lee, KH, Daisuke, S, Araki, K, Yamada, N, & … (2019). Demonstration of the performance static low-concentration module using hybrid lens arrays. AIP Conference …, aip.scitation.org, https://doi.org/10.1063/1.5124208
Kosmadakis, IE, Elmasides, C, Eleftheriou, D, & … (2019). A techno-economic analysis of a pv-battery system in Greece. Energies, mdpi.com, https://www.mdpi.com/442214
Barbier, T, Blanc, P, & Saint-Drenan, YM (2019). Software correction of angular misalignments of tilted reference solar cells using clear-sky satellite open data. EU PVSEC 2019, core.ac.uk, https://core.ac.uk/download/pdf/231946055.pdf
Polo, J, Martín-Chivelet, N, Alonso-García, MC, & … (2019). Modeling IV curves of photovoltaic modules at indoor and outdoor conditions by using the Lambert function. Energy Conversion and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0196890419306405
Younas, R, Imran, H, Riaz, MH, & … (2019). Agrivoltaic farm design: Vertical bifacial vs. tilted monofacial photovoltaic panels. arXiv preprint arXiv …, researchgate.net, https://www.researchgate.net/profile/Rehan-Younas/publication/336230450_Agrivoltaic_Farm_Design_Vertical_Bifacial_vs_Tilted_Monofacial_Photovoltaic_Panels/links/5d9ad464299bf1c363fd045a/Agrivoltaic-Farm-Design-Vertical-Bifacial-vs-Tilted-Monofacial-Photovoltaic-Panels.pdf
Catalina, A, Alaíz, CM, & … (2019). Combining numerical weather predictions and satellite data for PV energy nowcasting. IEEE Transactions on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8865555/
Chaudhari, C, Lance, T, Kimball, GM, & … (2019). PVOPEL: A Scalable Opto-Electrical Performance Model of PV systems using Ray Tracing and PVMismatch. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981230/
Coppitters, D, Paepe, W De, & Contino, F (2019). DOES THE INCLUSION OF A HYDROGEN-BASED ENERGY SYSTEM IMPROVES THE ROBUSTNESS OF THE LEVELIZED COST OF ELECTRICITY FOR AN …., energy-proceedings.org, https://www.energy-proceedings.org/wp-content/uploads/2020/02/272_Paper_0621030436.pdf
Lee, KH, Sato, D, Araki, K, Yamada, N, & … (2019). Demonstration of High Efficiency Static Low-Concentration Photovoltaic Module Using Hybrid Lens Arrays. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981268/
Camargo, LR, Gruber, K, Nitsch, F, & Dorner, W (2019). Hybrid renewable energy systems to supply electricity self-sufficient residential buildings in Central Europe. Energy Procedia, Elsevier, https://www.sciencedirect.com/science/article/pii/S1876610219301067
Headley, A, Hansen, C, & Nguyen, T (2019). Maximizing revenue from electrical energy storage paired with community solar projects in NYISO markets. 2019 North American Power …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9000262/
Braun, C (2019). A SCALABLE APPROACH FOR SPATIO-TEMPORAL ASSESSMENT OF PHOTOVOLTAIC ELECTRICITY POTENTIALS FOR BUILDING FAÇADES OF ENTIRE …. … of the Photogrammetry, Remote Sensing & …, pdfs.semanticscholar.org, https://pdfs.semanticscholar.org/1c9e/8a95ed9963b87d4dad1bd5ad2d228b25658d.pdf
Dzurick, M, Potter, BG, Holmgren, WF, & … (2019). Enhanced Photovoltaic Power Model Fidelity Using On-Site Irradiance and Degradation-Informed Performance Input. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8980708/
Peláez, SA, Deline, C, Stein, JS, Marion, B, & … (2019). Effect of torque-tube parameters on rear-irradiance and rear-shading loss for bifacial PV performance on single-axis tracking systems. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9198975/
Méndez, JC Julio (2019). Refinamiento e implementación de modelo computacional para predicción del comportamiento de parques solares fotovoltaicos., repositorio.uniandes.edu.co, https://repositorio.uniandes.edu.co/handle/1992/44827
Waters, M, Deline, C, Kemnitz, J, & … (2019). Suggested modifications for bifacial capacity testing. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9198974/
Haakana, J, Haapaniemi, J, Lassila, J, Partanen, J, & … (2019). Electricity demand profile for residential customer 2030., cired-repository.org, https://www.cired-repository.org/handle/20.500.12455/573
Driesse, A, & Stein, J (2019). Making the Most of Module Matrix Measurements: IEC 61853-1.., osti.gov, https://www.osti.gov/servlets/purl/1641920
Kuppannagari, S, Kannan, R, & Prasanna, VK (2019). Approximate Scheduling of DERs with Discrete Complex Injections. Proceedings of the Tenth …, dl.acm.org, https://doi.org/10.1145/3307772.3328311
Stein, J, Prilliman, MJ, Stark, CT, Pelaez, SA, & Deline, C (2019). Bifacial Performance Optimization Studies using Bifacial Radiance and High Performance Computing.., osti.gov, https://www.osti.gov/servlets/purl/1641769
Platonova, EV, Toropov, AS, & … (2019). Simulation of energy input to solar panels. 2019 International Ural …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8877633/
Mikofski, MA, Darawali, R, Hamer, M, & … (2019). Bifacial performance modeling in large arrays. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8980572/
Headley, A, Hansen, C, & Nguyen, TA (2019). Energy Storage Paired with Community Solar in NYISO.., osti.gov, https://www.osti.gov/servlets/purl/1642814
Headley, A, Nguyen, TA, & Byrne, RH (2019). Energy Storage Analysis for Regional Demonstration Projects.., osti.gov, https://www.osti.gov/servlets/purl/1642175
Headley, A (2019). Maximizing Storage Value in Regional Markets and the QuESt App.., osti.gov, https://www.osti.gov/servlets/purl/1645595
Shinn, A, & Browne, B (2019). Measuring Degradation of Fielded Systems on an Ongoing Basis with RdTools., osti.gov, https://www.osti.gov/biblio/1507571
Holland, N, Pang, X, Herzberg, W, & … (2019). Solar and PV forecasting for large PV power plants using numerical weather models, satellite data and ground measurements. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8980496/
Meunier, S, Queval, L, Heinrich, M, & … (2019). Effect of irradiance data on the optimal sizing of photovoltaic water pumping systems. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981282/
Dyamond, WP (2019). Fault Detection and performance visualisation for a grid-connected Photovoltaic Power Plant using sensor data., scholar.sun.ac.za, http://scholar.sun.ac.za/handle/10019.1/107181
Εμμανουηλίδου, ΙΚ, & Τόλης, ΑΝ (2019). Ανάλυση επιχειρηματικών σχεδίων φωτοβολταϊκών εφαρμογών: δεδομένα εγκαταστάσεων και εκτίμηση απόδοσης., ir.lib.uth.gr, https://ir.lib.uth.gr/xmlui/bitstream/handle/11615/50027/18849.pdf?sequence=1
Heesen, H te, Herbort, V, & Rumpler, M (2019). Performance of roof-top PV systems in Germany from 2012 to 2018. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X19310023
Razo, DEG, Killinger, S, Müller, B, & Wittwer, C (2019). A Comparison of Two Models for the Separation of Direct and Diffuse Irradiance in Plane of Array., researchgate.net, https://www.researchgate.net/profile/Dorian-Esteban-Guzman-Razo/publication/336775672_A_Comparison_of_Two_Models_for_the_Separation_of_Direct_and_Diffuse_Irradiance_in_Plane_of_Array/links/5db1bf9d92851c577eba869d/A-Comparison-of-Two-Models-for-the-Separation-of-Direct-and-Diffuse-Irradiance-in-Plane-of-Array.pdf
Bennett, JA, Fuhrman, J, Brown, T, Andrews, N, Fittro, R, & … (2019). Feasibility of using sCO2 turbines to balance load in power grids with a high deployment of solar generation. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544219310254
Ye, LC, Lin, HX, & Tukker, A (2019). Future scenarios of variable renewable energies and flexibility requirements for thermal power plants in China. Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0360544218321716
Miskin, CK, Li, Y, Perna, A, Ellis, RG, Grubbs, EK, & … (2019). Sustainable co-production of food and solar power to relax land-use constraints. Nature …, nature.com, https://www.nature.com/articles/s41893-019-0388-x
Jones, CB, Karin, T, Jain, A, Hobbs, WB, & … (2019). Geographic assessment of photovoltaic module environmental degradation stressors. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8980741/
Jones, CB, & Hansen, CW (2019). Single diode parameter extraction from in-field photovoltaic IV curves on a single board computer. 2019 IEEE 46th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981330/
Camargo, LR, Valdes, J, Macia, YM, & Dorner, W (2019). Assessment of on-site steady electricity generation from renewable energy sources in Chile. Energy Procedia, Elsevier, https://www.sciencedirect.com/science/article/pii/S1876610219302772
Skomedal, Å, Øgaard, MB, Selj, J, Haug, H, & … (2019). General, robust, and scalable methods for string level monitoring in utility scale PV systems. 36th European …, researchgate.net, https://www.researchgate.net/profile/Asmund_Skomedal2/publication/337113457_General_Robust_and_Scalable_Methods_for_String_Level_Monitoring_in_Utility_Scale_PV_Systems/links/5dc5abdf4585151435f7da0c/General-Robust-and-Scalable-Methods-for-String-Level-Monitoring-in-Utility-Scale-PV-Systems.pdf
Lorenz, E, Holland, N, Dittmann, A, Herzberg, W, & … (2019). Minute resolution measurement network for global horizontal and tilted solar irradiance for a transmission System Control Area in Southern Germany. …, ise.fraunhofer.de, https://www.ise.fraunhofer.de/content/dam/ise/de/documents/publications/conference-paper/37th-eupvsec-2020/Lorenz_5BO74.pdf
Brown, PR, & O’Sullivan, FM (2019). Shaping photovoltaic array output to align with changing wholesale electricity price profiles. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919314217
Braga, M, Nascimento, LR do, & … (2019). Spectral Impacts on the Performance of mc-Si and New-Generation CdTe Photovoltaics in the Brazilian Northeast. 2019 IEEE 46th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981152/
Ascencio-Vásquez, J, Brecl, K, & Topič, M (2019). Methodology of Köppen-Geiger-Photovoltaic climate classification and implications to worldwide mapping of PV system performance. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X19308527
Dickeson, G, McLeod, L, Dobb, A, Frearson, L, & … (2019). Ramp Rate Control For Pv Plant Integration: Experience From Karratha Airport’s Hybrid Power Station. 36th European …, arena.gov.au, https://arena.gov.au/assets/2017/02/ramp-rate-control-for-pv-plant-integration-experience-from-karratha-airports-hybrid-power-station.pdf
Feng, C, Yang, D, Hodge, BM, & Zhang, J (2019). OpenSolar: Promoting the openness and accessibility of diverse public solar datasets. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X19306693
Jurack, A, Mamari, J Al, Al-Riyami, S, Scheuren, J, & … (2019). Investigation of Soiling Effects on Solar Glass Covers in the Climate of Muscat, Oman., proceedings.ises.org, http://proceedings.ises.org/paper/swc2019/swc2019-0014-Jurack.pdf
Leitão, J, Gil, P, Ribeiro, B, & … (2019). Smart Home Energy Management Supported by Cloud Computing. 2019 5th Experiment …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8876531/
Patel, MT, Khan, MR, Sun, X, & Alam, MA (2019). A worldwide cost-based design and optimization of tilted bifacial solar farms. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919305604
Sánchez, C, Bloch, L, Holweger, J, Ballif, C, & Wyrsch, N (2019). Optimised heat pump management for increasing photovoltaic penetration into the electricity grid. Energies, mdpi.com, https://www.mdpi.com/451692
Nagel, J (2019). Modeling in OEMOF. Optimization of Energy Supply Systems, Springer, https://doi.org/10.1007/978-3-319-96355-6_4
Pedro, HTC, Larson, DP, & … (2019). A comprehensive dataset for the accelerated development and benchmarking of solar forecasting methods. Journal of Renewable and …, aip.scitation.org, https://doi.org/10.1063/1.5094494
Dakir, S, Boukas, I, Lemort, V, & … (2019). Sizing and operation of an isolated microgrid with cold storage. 2019 IEEE Milan …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8810700/
Camargo, LR, Valdes, J, Macia, YM, & Dorner, W (2019). Assessment of on-site steady electricity generation from hybrid renewable energy systems in Chile. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919308591
Hoffmann, MM, & Ansari, D (2019). Simulating the potential of swarm grids for pre-electrified communities–A case study from Yemen. Renewable and Sustainable Energy Reviews, Elsevier, https://www.sciencedirect.com/science/article/pii/S1364032119301819
Lyden, A, & Tuohy, P (2019). A methodology for designing decentralised energy systems with predictive control for heat pumps and thermal storage. E3S Web of Conferences, e3s-conferences.org, https://www.e3s-conferences.org/articles/e3sconf/abs/2019/37/e3sconf_clima2019_06014/e3sconf_clima2019_06014.html
Lyden, A, & Tuohy, P (2019). Heat pump and thermal storage sizing with time-of-use electricity pricing., strathprints.strath.ac.uk, https://strathprints.strath.ac.uk/71085/
Nassar, YF, & Alsadi, SY (2019). Assessment of solar energy potential in Gaza Strip-Palestine. Sustainable Energy Technologies and Assessments, Elsevier, https://www.sciencedirect.com/science/article/pii/S221313881830331X
Iovine, A, Rigaut, T, Damm, G, Santis, E De, & … (2019). Power management for a DC MicroGrid integrating renewables and storages. Control Engineering …, Elsevier, https://www.sciencedirect.com/science/article/pii/S0967066119300048
Qi, B, Rashedi, M, & Ardakanian, O (2019). Energyboost: Learning-based control of home batteries. Proceedings of the Tenth ACM …, dl.acm.org, https://doi.org/10.1145/3307772.3328279
Château, PA, Wunderlich, RF, Wang, TW, Lai, HT, & … (2019). Mathematical modeling suggests high potential for the deployment of floating photovoltaic on fish ponds. Science of the total …, Elsevier, https://www.sciencedirect.com/science/article/pii/S004896971932474X
Walker, L, Hofer, J, & Schlueter, A (2019). High-resolution, parametric BIPV and electrical systems modeling and design. Applied energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261918319044
Al-Kurdi, N, Pillot, B, Gervet, C, & Linguet, L (2019). Towards robust scenarios of spatio-temporal renewable energy planning: A GIS-RO approach. International Conference on …, Springer, https://doi.org/10.1007/978-3-030-30048-7_42
Peronato, G (2019). Urban planning support based on the photovoltaic potential of buildings: a multi-scenario ranking system., infoscience.epfl.ch, https://infoscience.epfl.ch/record/262890
Niño, LP Oñate (2019). Desarrollo de un modelo computacional para analizar el comportamiento de parques de generación de energía solar fotovoltaica., repositorio.uniandes.edu.co, https://repositorio.uniandes.edu.co/handle/1992/45218
Joshi, B, Kay, M, Copper, JK, & Sproul, AB (2019). Evaluation of solar irradiance forecasting skills of the Australian Bureau of Meteorology’s ACCESS models. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X19305778
Sala, S, Amendola, A, Leva, S, Mussetta, M, Niccolai, A, & … (2019). Comparison of data-driven techniques for nowcasting applied to an industrial-scale photovoltaic plant. Energies, mdpi.com, https://www.mdpi.com/583314
Lane, R (2019). The design and simulation in Python of a model predictive control system to maximise use of local renewables in a heat network with thermal storage.., esru.strath.ac.uk, http://www.esru.strath.ac.uk/Documents/MSc_2019/Lane.pdf
Paudyal, B, Bolen, M, & Fregosi, D (2019). PV plant performance loss rate assessment: Significance of data filtering and aggregation. 2019 IEEE 46th Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8981247/
Terlouw, T, AlSkaif, T, Bauer, C, & Sark, W van (2019). Optimal energy management in all-electric residential energy systems with heat and electricity storage. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919312541
Alatawi, H (2019). Determining an Optimal Level of Power System Investments Under Large Scale Penetration of Solar Power in Saudi Arabia., diva-portal.org, https://www.diva-portal.org/smash/get/diva2:1414138/FULLTEXT01.pdf
Gamarro, H, Gonzalez, JE, & … (2019). On the assessment of a numerical weather prediction model for solar photovoltaic power forecasts in cities. Journal of Energy …, asmedigitalcollection.asme.org, https://asmedigitalcollection.asme.org/energyresources/article-abstract/141/6/061203/725725
Sossan, F, Scolari, E, Gupta, R, & … (2019). Solar irradiance estimations for modeling the variability of photovoltaic generation and assessing violations of grid constraints: A comparison between satellite and …. Journal of Renewable and …, aip.scitation.org, https://doi.org/10.1063/1.5109076
Auer, S, Liße, J, Mandha, SR, & … (2019). Power-flow-constrained asset optimization for off-grid power systems using selected Open-Source frameworks. Proceedings of the 4th …, hybridpowersystems.org, https://hybridpowersystems.org/crete2019/wp-content/uploads/sites/13/2020/03/6B_2_HYB19_029_paper_Auer_Sabine.pdf
Kam, M Van Der, Peters, A, Sark, W Van, & Alkemade, F (2019). Agent-based modelling of charging behaviour of electric vehicle drivers. JASSS, dspace.library.uu.nl, https://dspace.library.uu.nl/handle/1874/387983
Zhou, Z, Wang, Z, & Bermel, P (2019). Radiative cooling for low-bandgap photovoltaics under concentrated sunlight. Optics express, osapublishing.org, https://www.osapublishing.org/abstract.cfm?uri=oe-27-8-A404
Pelaez, SA (2019). Bifacial solar panels system design, modeling, and performance., search.proquest.com, https://search.proquest.com/openview/6c20a34c4344792b7b84254ba44e4a8f/1?pq-origsite=gscholar&cbl=18750&diss=y
Lovati, M, Salvalai, G, Fratus, G, Maturi, L, & … (2019). New method for the early design of BIPV with electric storage: A case study in northern Italy. Sustainable Cities and …, Elsevier, https://www.sciencedirect.com/science/article/pii/S2210670718313167
Gueymard, CA, Bright, JM, Lingfors, D, Habte, A, & … (2019). A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers. … and Sustainable Energy …, Elsevier, https://www.sciencedirect.com/science/article/pii/S1364032119302382
Kraus, P, Massué, C, Heumann, S, & … (2019). Reliable long-term performance assessment of commercial photovoltaic modules tested under field conditions over 5 years. Journal of Renewable …, aip.scitation.org, https://doi.org/10.1063/1.5128171
Vrettos, E, Kara, EC, Stewart, EM, & … (2019). Estimating PV power from aggregate power measurements within the distribution grid. Journal of Renewable …, aip.scitation.org, https://doi.org/10.1063/1.5094161
Blaga, R (2019). The impact of temporal smoothing on the accuracy of separation models. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X19308709
Zapata, MZ, Wu, E, & Kleissl, J (2019). Irradiance enhancement events in the coastal Stratocumulus dissipation process. Santiago, proceedings.ises.org, http://proceedings.ises.org/paper/swc2019/swc2019-0199-ZamoraZapata.pdf
Gašparović, I, Gašparović, M, Medak, D, & Zrinjski, M (2019). Analysis of Solar Potential Spatial Data for Croatia. Geodetski list, hrcak.srce.hr, https://hrcak.srce.hr/clanak/319451
Carpentier, P, Chancelier, JP, Lara, M De, & Rigaut, T (2019). Algorithms for two-time scales stochastic optimization with applications to long term management of energy storage., hal.archives-ouvertes.fr, https://hal.archives-ouvertes.fr/hal-02013969/
Hertsberg, A (2019). A statistical approach for assessing cloud conditions using photovoltaic solar electricity production data., aaltodoc.aalto.fi, https://aaltodoc.aalto.fi/bitstream/handle/123456789/41704/master_Hertsberg_Axel_2019.pdf?sequence=1
Gašparović, I, Gašparović, M, Medak, D, & … (2019). Analiza prostornih podataka o solarnom potencijalu za Hrvatsku. Geodetski list …, researchgate.net, https://www.researchgate.net/profile/Mateo-Gasparovic/publication/332415521_Analysis_of_Solar_Potential_Spatial_Data_for_Croatia/links/5cb4670792851c8d22ec533e/Analysis-of-Solar-Potential-Spatial-Data-for-Croatia.pdf
Souza, BM (2019). Algoritmo de Projeto e Gestão de Subsistema de Alimentação Baseado em Energia Solar para Redes de Sensores Sem Fios., recipp.ipp.pt, https://recipp.ipp.pt/handle/10400.22/15778
Kannengießer, T, Hoffmann, M, Kotzur, L, Stenzel, P, & … (2019). Reducing computational load for mixed integer linear programming: an example for a district and an island energy system. Energies, mdpi.com, https://www.mdpi.com/501302
Leedy, AW, & Abdelraziq, M (2019). Modeling PV Modules Using Simulink/MATLAB under Varying Conditions. 2019 SoutheastCon, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9020537/
Bird, J (2019). Atmospherically Aware Aircraft Guidance Using In Situ Observations., search.proquest.com, https://search.proquest.com/openview/19bbb87b2d8568b57e0b5655fa3aaf96/1?pq-origsite=gscholar&cbl=44156
Mathe, J, Miolane, N, Sebastien, N, & Lequeux, J (2019). PVNet: A LRCN architecture for spatio-temporal photovoltaic PowerForecasting from numerical weather prediction. arXiv preprint arXiv …, arxiv.org, https://arxiv.org/abs/1902.01453
Meunier, S, Heinrich, M, Quéval, L, Cherni, JA, Vido, L, & … (2019). A validated model of a photovoltaic water pumping system for off-grid rural communities. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261919304349
Jordan, DC, Deline, C, Deceglie, MG, & … (2019). Reducing interanalyst variability in photovoltaic degradation rate assessments. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8876837/
Bidikar, N, Rajitha, K, & Supriya, PU (2019). A Novel Universal Solar Energy Predictor. arXiv preprint arXiv:1902.06660, arxiv.org, https://arxiv.org/abs/1902.06660
Lucas, C, Guemri, M, & Tran, QT (2019). Impact of consumer profiles and forecast accuracy on day-ahead scheduling of household appliances. 2019 IEEE International …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8783899/
Suk, H, & Hall, J (2019). Integrating quality of life in sociotechnical design: a review of microgrid design tools and social indicators. International Design Engineering …, asmedigitalcollection.asme.org, https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2019/V02BT03A047/1069848
Brady, J, Chu, C, Colter, E, & … (2019). Methodology for Climate Central’s WeatherPowerTM (Wind and Solar Electricity Forecaster), version 2.0. Climate …, wp-static-prod.s3.amazonaws.com, http://wp-static-prod.s3.amazonaws.com/WeatherPower_v2.0_Methodology_20Sep2019.pdf
Bruck, A (2019). Artificial Intelligence in rural offgrid Polygeneration Systems:: A Case Study with RVE. Sol focusing on Electricity Supply & Demand Balancing., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1372646
Fonseca, JA, Hanif, S, Sreepathi, BK, Troitzsch, S, & … (2019). Connecting District Energy and Power Systems for Future Singaporean New Towns (CONCEPT)., research-collection.ethz.ch, https://www.research-collection.ethz.ch/handle/20.500.11850/401217
Prinsloo, FC (2019). Development of a GIS-based decision support tool for environmental impact assessment and due-diligence analyses of planned agricultural floating solar …. University of South Africa, agrisolarclearinghouse.org, https://www.agrisolarclearinghouse.org/wp-content/uploads/2021/11/DEVELOPMENT-OF-A-GIS-BASED-DECISION-SUPPORT.pdf
Gong, J (2019). Optimisation of charging strategies and energy storage operation for a solar driven charging station., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1423614
Memmel, E, Peters, D, Völker, R, Schuldt, F, & … (2019). Simulation of vertical power flow at MV/HV transformers for quantification of curtailed renewable power. IET Renewable …, ieeexplore.ieee.org.
Schniewind, BSM (2019). Tackling challenges in a decentralised multi-agent smart grid with biomimetic stability mechanisms and unsupervised control–A first approach., researchgate.net, https://www.researchgate.net/profile/Matthias-Schniewind-2/publication/332029214_Tackling_challenges_in_a_decentralised_multi-agent_smart_grid_with_biomimetic_stability_mechanisms_and_unsupervised_control_-_A_first_approach/links/5c9b91c6a6fdccd4603f15f8/Tackling-challenges-in-a-decentralised-multi-agent-smart-grid-with-biomimetic-stability-mechanisms-and-unsupervised-control-A-first-approach.pdf
Peet, BJA (2019). Accurate estimation of temperature distributions for IR signature monitoring with a dynamic thermal model and data assimilation. Target and Background Signatures V, spiedigitallibrary.org
Bird, JJ, Richardson, SJ, & Langelaan, JW (2019). Estimating the vertical structure of weather-induced mission costs for small UAS. Sensors, mdpi.com, https://www.mdpi.com/482974
Baumann, VAR (2019). Viabilidade econômico-financeira de sistemas fotovoltaicos conectados à rede em Florianópolis-SC utilizando dados monitorados e simulados do primeiro ano., repositorio.ifsc.edu.br, https://repositorio.ifsc.edu.br/bitstream/handle/123456789/1281/TCC%20-%20Victor%20A%20R%20Baumann.pdf?sequence=1
Bloch, L, Holweger, J, Ballif, C, & Wyrsch, N (2019). Impact of advanced electricity tariff structures on the optimal design, operation and profitability of a grid-connected PV system with energy storage. Energy Informatics, Springer, https://doi.org/10.1186/s42162-019-0085-z
Qi, B (2019). Learning to Control Home Batteries in the Smart Grid., era.library.ualberta.ca, https://era.library.ualberta.ca/items/58d6cb74-6652-4c18-be88-ff83630d10d9
Toledo, C, Serrano-Lujan, L, Abad, J, Lampitelli, A, & … (2019). Measurement of thermal and electrical parameters in photovoltaic systems for predictive and cross-correlated monitorization. Energies, mdpi.com, https://www.mdpi.com/414352
Yang, J (2019). Designing Deployment Policies to Maximize the Co-benefits of China’s Clean Energy Transition., search.proquest.com, https://search.proquest.com/openview/02ef8875db78344e045b7e5c7087ccda/1?pq-origsite=gscholar&cbl=18750&diss=y
Brolese, RR (2019). Previsão de geração de energia fotovoltaica utilizando método de aprendizado de máquina., repositorio.ucs.br, https://repositorio.ucs.br/xmlui/handle/11338/6132
Castillo, A, Flicker, J, Hansen, CW, & … (2019). Stochastic optimisation with risk aversion for virtual power plant operations: a rolling horizon control. IET Generation …, ieeexplore.ieee.org.
Less, B, Walker, I, Slack, J, Rainer, L, & Levinson, R (2019). Sealed and Insulated Attic Hygrothermal Performance in New California Homes Using Vapor and Air Permeable Insulation—Field Study and Simulation., escholarship.org, https://escholarship.org/uc/item/5m0052v8
Arias, CA Toledo, Luján, L Serrano, López, J Abad, & … (2019). Measurement of thermal and electrical parameters in photovoltaic systems for predictive and cross-correlated monitorization., repositorio.upct.es, https://repositorio.upct.es/handle/10317/9710
French, R, Braid, JL, & Liu, JQ (2019). Module Level Exposure and Evaluation Test (MLEET) for Real-world and Laboratory-based PV Modules: Common Data and Analytics for Quantitative Cross …., osti.gov, https://www.osti.gov/biblio/1529093
Stainsby, WJ (2019). Disaggregation of net-metered advanced metering infrastructure data to estimate photovoltaic generation., search.proquest.com, https://search.proquest.com/openview/978297252d3c3d422e52c61bf3d64328/1?pq-origsite=gscholar&cbl=51922&diss=y
Li, D (2019). Micro optics for micro hybrid concentrator photovoltaics., dspace.mit.edu, https://dspace.mit.edu/handle/1721.1/123563
Edington, ANC (2019). The role of long duration energy storage in decarbonizing power systems., dspace.mit.edu, https://dspace.mit.edu/handle/1721.1/122095
Gonzalez-Cruz, JE, Arend, M, Legbandt, T, & … (2019). Method for forecasting energy demands that incorporates urban heat island. US Patent App. 16 …, Google Patents, https://patents.google.com/patent/US20190139163A1/en
Nyirenda, E (2019). Conjunctive Operation of Hydro and Solar PV Power with Pumped Storage at Kafue Gorge Power Station (Zambia)., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1334218
Pujol, R Colom (2019). Estudi de diferents opcions d’integració de generació fotovoltaica en edificis., upcommons.upc.edu, https://upcommons.upc.edu/handle/2117/128705
Besseau, R (2019). Analyse de cycle de vie de scénarios énergétiques intégrant la contrainte d’adéquation temporelle production-consommation., theses.fr, https://www.theses.fr/2019PSLEM068

2018

Holmgren, WF, Hansen, CW, & … (2018). pvlib python: A python package for modeling solar energy systems. Journal of Open Source …, joss.theoj.org, https://doi.org/10.21105/joss.00884
Hansen, C (2018). What? s new in PVLib and pvlib-python?.., osti.gov, https://www.osti.gov/servlets/purl/1513354
PVLIB-Python, API (2018). reference [WWW Document], 2018. … //pvlib-python. readthedocs. io/en/latest/generated/pvlib …
Collaborative, PVPM (2018). PVLIB toolbox.
Kallio, V, & Riihelä, A (2018). Comparative Validation of Clear Sky Irradiance Models over Finland. IGARSS 2018-2018 IEEE International …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8519270/
Holmgren, WF, Hansen, CW, Stein, JS, & … (2018). Review of open source tools for PV modeling. 2018 IEEE 7th World …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8548231/
Riley, D, Stein, J, & Hansen, C (2018). 2018 IEEE PVSC Tutorial PV System Modeling.., osti.gov, https://www.osti.gov/servlets/purl/1511110
Ellis, BH, Deceglie, M, & Jain, A (2018). Automatic detection of clear-sky periods using ground and satellite based solar resource data. … )(A Joint Conference of 45th IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8547877/
김태영, & 김진호 (2018). 서포트 벡터 회귀와 파이썬 라이브러리를 활용한 태양광 발전량 예측. 대한전기학회학술대회논문집, dbpia.co.kr, https://www.dbpia.co.kr/Journal/articleDetail?nodeId=NODE07532390
Stein, JS, & Lavrova, O (2018). Final Project Report: PV Stakeholder Engagement Initiatives., osti.gov, https://www.osti.gov/biblio/1481543
Klise, KA (2018). Pecos-Open Source Software for PV System Monitoring.., osti.gov, https://www.osti.gov/servlets/purl/1525601
Hansen, C (2018). Photovoltaic And Renewable Energy Systems Research.., osti.gov, https://www.osti.gov/servlets/purl/1806947
John, JJ, Alnuaimi, A, Elnosh, A, & … (2018). Estimating degradation rates from 27 different PV modules installed in desert conditions using the NREL/Rdtools. 2018 IEEE 7th World …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8547283/
Potter, BG, Simmons-Potter, K, & … (2018). Broad-Time-Horizon Solar Power Prediction and PV Performance Degradation Research at the University of Arizona. 2018 IEEE 7th World …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8547422/
Berrueta, A, Heck, M, Jantsch, M, Ursúa, A, & Sanchis, P (2018). Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic …. Applied energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261918309279
Ho, CK (2018). Solar Technology Research at Sandia: PV and CSP (presentation).., osti.gov, https://www.osti.gov/servlets/purl/1592672
Luo, W, Khoo, YS, Hacke, P, Jordan, D, & … (2018). Analysis of the long-term performance degradation of crystalline silicon photovoltaic modules in tropical climates. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8520911/
Bhattacharya, S, Leopold, U, Braun, C, & Bongiovanni, F (2018). Solar Energy Potential Assessment for entire Cities-a reusable and scalable approach., scholarsarchive.byu.edu, https://scholarsarchive.byu.edu/iemssconference/2018/Stream-A/62/
Litjens, G, Worrell, E, & Sark, W Van (2018). Assessment of forecasting methods on performance of photovoltaic-battery systems. Applied Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261918305014
Luján, E, Otero, A, Valenzuela, S, Mocskos, E, & … (2018). Cloud computing for smart energy management (CC-SEM project). … -American Congress of …, Springer, https://doi.org/10.1007/978-3-030-12804-3_10
Rognan, LMH (2018). Photovoltaic Power Prediction and Control Strategies of the Local Storage Unit at Campus Evenstad., ntnuopen.ntnu.no, https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/2570005
Yang, D (2018). SolarData: An R package for easy access of publicly available solar datasets. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X18306583
Camargo, LR, Nitsch, F, Gruber, K, & Dorner, W (2018). Electricity self-sufficiency of single-family houses in Germany and the Czech Republic. Applied energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261918309875
Alonso-Álvarez, D, Wilson, T, Pearce, P, Führer, M, & … (2018). Solcore: a multi-scale, Python-based library for modelling solar cells and semiconductor materials. Journal of …, Springer, https://doi.org/10.1007/s10825-018-1171-3
Craig, MT, Jaramillo, P, Hodge, BM, Williams, NJ, & … (2018). A retrospective analysis of the market price response to distributed photovoltaic generation in California. Energy policy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0301421518303781
Moreno, S Aguacil, Peronato, G, Lufkin, S, & … (2018). Assessment of the building-integrated photovoltaic potential in urban renewal processes in the Swiss context: complementarity of urban-and architectural-scale …. Smart and Healthy …, upcommons.upc.edu, https://upcommons.upc.edu/handle/2117/130986
Lee, KH, Araki, K, Kojima, N, & … (2018). Achieving wide-acceptance angle and high on-axis performance static low-concentration module using hybrid lens arrays. AIP Conference …, aip.scitation.org, https://doi.org/10.1063/1.5053514
Stein, J (2018). Opportunities for New and Innovative Photovoltaic Modules and Systems.., osti.gov, https://www.osti.gov/servlets/purl/1514776
Ascencio-Vásquez, J, Brecl, K, & … (2018). Köppen-Geiger-photovoltaic climate classification. 2018 IEEE 7th World …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8547952/
Chen, D, Breda, J, & Irwin, D (2018). Staring at the sun: a physical black-box solar performance model. Proceedings of the 5th Conference on …, dl.acm.org, https://doi.org/10.1145/3276774.3276782
Smithpeter, I (2018). ASES National Solar Conference 2018 A Low-Cost IoT Approach to Real-Time Cloud Motion Detection., proceedings.ises.org, http://proceedings.ises.org/paper/solar2018/solar2018-0012-Smithpeter.pdf
Dallapiccola, M, Ingenhoven, P, Moser, D, & … (2018). Simplified Method for Partial Shading Losses Calculation for Series Connected PV Modules with Experimental Validation. 35th Eur. Photovolt. Sol …, researchgate.net, https://www.researchgate.net/profile/Mattia-Dallapiccola/publication/330307560_SIMPLIFIED_METHOD_FOR_PARTIAL_SHADING_LOSSES_CALCULATION_FOR_SERIES_CONNECTED_PV_MODULES_WITH_EXPERIMENTAL_VALIDATION/links/5c38486e299bf12be3be484c/SIMPLIFIED-METHOD-FOR-PARTIAL-SHADING-LOSSES-CALCULATION-FOR-SERIES-CONNECTED-PV-MODULES-WITH-EXPERIMENTAL-VALIDATION.pdf
Irigoyen, A Berrueta, Heck, M, & … (2018). Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants. … Energy, 228 (2018 …, academica-e.unavarra.es, https://academica-e.unavarra.es/handle/2454/33235
Bognár, Á, Loonen, R, Valckenborg, RME, & Hensen, JLM (2018). An unsupervised method for identifying local PV shading based on AC power and regional irradiance data. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X18309873
Mountain, B, & Kars, A (2018). Using electricity bills to shine a light on rooftop solar photovoltaics in Australia: A comparison of prices, volumes and socio-economic rank of households with …., vuir.vu.edu.au, https://vuir.vu.edu.au/41864/1/Solar_Citizens_FINAL_Report_23_NOVEMBER_2018.pdf
Hilpert, S, Kaldemeyer, C, Krien, U, Günther, S, & … (2018). The Open Energy Modelling Framework (oemof)-A new approach to facilitate open science in energy system modelling. Energy strategy …, Elsevier, https://www.sciencedirect.com/science/article/pii/S2211467X18300609
Lee, KH, Araki, K, & Yamaguchi, M (2018). Achieving high efficiency static low-concentration photovoltaic module using hybrid lens arrays. … PVSC, 28th PVSEC & 34th EU …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8547928/
Sehnem, JM, Michels, L, & … (2018). SIMULAÇÕES NUMÉRICAS PARA DETERMINAÇÃO DE INCLINAÇÕES ÓTIMAS PARA MÓDULOS FOTOVOLTAICOS. … de Energia Solar …, anaiscbens.emnuvens.com.br, http://anaiscbens.emnuvens.com.br/cbens/article/view/723
Groenendyk, D (2018). cons2_Python Documentation., media.readthedocs.org, https://media.readthedocs.org/pdf/cons2-python/master/cons2-python.pdf
Kumler, A, Xie, Y, & Zhang, Y (2018). A new approach for short-term solar radiation forecasting using the estimation of cloud fraction and cloud albedo., osti.gov, https://www.osti.gov/biblio/1476449
Khosrojerdi, F, Gagnon, S, & Valverde, R (2018). Using Software Quality Evaluation Standard Model for Managing Software Development Projects in Solar Sector., spectrum.library.concordia.ca, https://spectrum.library.concordia.ca/id/eprint/984517/
Litjens, GBMA, Kausika, BB, Worrell, E, & Sark, W van (2018). A spatio-temporal city-scale assessment of residential photovoltaic power integration scenarios. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X18309496
Sun, X, Khan, MR, Deline, C, & Alam, MA (2018). Optimization and performance of bifacial solar modules: A global perspective. Applied energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261917317567
Hobbs, WB, Lave, M, & … (2018). Simulating High-Frequency Generation Profiles for Large Solar PV Portfolios. 2018 IEEE 7th World …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8547850/
Pelaez, SA, Deline, CA, Greenberg, P, Stein, J, & Kostuk, R (2018). Model and Validation of Single-Axis Tracking with Bifacial Photovoltaics., osti.gov, https://www.osti.gov/biblio/1478728
Riihelä, A, Kallio, V, Devraj, S, Sharma, A, & Lindfors, AV (2018). Validation of the SARAH-E satellite-based surface solar radiation estimates over India. Remote Sensing, mdpi.com, https://www.mdpi.com/269038
Zhao, B, Sun, X, & Alam, MA (2018). Online Simulation Tools for Global Photovoltaic Performance: Purdue University Meteorological Tool (PUMET) and Bifacial Module Calculator (PUB). 2018 IEEE 7th World Conference on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8547981/
Nazarian, N, Sin, T, & Norford, L (2018). Numerical modeling of outdoor thermal comfort in 3D. Urban climate, Elsevier, https://www.sciencedirect.com/science/article/pii/S2212095518300786
Nunnari, G (2018). Forecasting the Class of Daily Clearness Index for PV Applications.. ICINCO (1), pdfs.semanticscholar.org, https://pdfs.semanticscholar.org/ed6a/8901b1adf3e6d15c3747968e718e1f3eacdd.pdf
Prada, J, & Dorronsoro, JR (2018). General noise support vector regression with non-constant uncertainty intervals for solar radiation prediction. … of Modern Power Systems and Clean …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/9024331/
Gašparović, I, Gašparović, M, & Medak, D (2018). Determining and analysing solar irradiation based on freely available data: A case study from Croatia. Environmental Development, Elsevier, https://www.sciencedirect.com/science/article/pii/S2211464517302105
Boudon, F, Persello, S, Grechi, I, Marquier, A, & … (2018). Assessing the role of ageing and light availability in leaf mortality in the mango tree. … Systems of 1281, actahort.org, https://www.actahort.org/books/1281/1281_79.htm
Duan, J, McKenna, A, Kooten, GC Van, & Liu, S (2018). Renewable Electricity Grids, Battery Storage and Missing Money: An Alberta Case Study., ageconsearch.umn.edu, https://ageconsearch.umn.edu/record/277525/
Stein, J (2018). Solar PV Performance and New Technologies in Northern Latitude Regions.., osti.gov, https://www.osti.gov/servlets/purl/1510188
Yang, J, Li, X, Peng, W, Wagner, F, & … (2018). Climate, air quality and human health benefits of various solar photovoltaic deployment scenarios in China in 2030. Environmental …, iopscience.iop.org, https://doi.org/10.1088/1748-9326/aabe99
Lindig, S, Ingenhoven, PC, Belluardo, G, & … (2018). Evaluation of Technology-Dependent Maximum Power Point Current and Voltage Degradation in a Temperate Climate. EUPVSEC European PV …, bia.unibz.it, https://bia.unibz.it/esploro/outputs/conferenceProceeding/Evaluation-of-Technology-Dependent-Maximum-Power-Point-Current-and-Voltage-Degradation-in-a-Temperate-Climate/991005773038401241
Tzikas, C, Valckenborg, RME, & … (2018). Outdoor characterization of colored and textured prototype PV facade elements. 35th European …, researchgate.net, https://www.researchgate.net/profile/Chris-Tzikas/publication/330349994_Outdoor_Characterization_of_Colored_and_Textured_Prototype_PV_Facade_Elements/links/5c3b0d62458515a4c7225c4d/Outdoor-Characterization-of-Colored-and-Textured-Prototype-PV-Facade-Elements.pdf
Scolari, E, Sossan, F, Haure-Touzé, M, & Paolone, M (2018). Local estimation of the global horizontal irradiance using an all-sky camera. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X18308119
Nascimento, MMS (2018). Optimization of memory usage in quantum computing simulation., repositorio.ufpel.edu.br, http://repositorio.ufpel.edu.br:8080/handle/prefix/4355
Stein, J (2018). The Disruption of Future PV Developments.., osti.gov, https://www.osti.gov/servlets/purl/1512004
Raker, D, Kini, R, Huntsman, R, Green, M, & … (2018). Transactive Mitigation Of Variability In The Output Of 1 MW Photovoltaic Array Using VolttronTM. 2018 IEEE 7th World …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8548242/
Gurupira, TL (2018). Evaluation and optimisation of photovoltaic (PV) plant designs., scholar.sun.ac.za, http://scholar.sun.ac.za/handle/10019.1/103499
Woodruff, DL, Deride, J, Staid, A, Watson, JP, Slevogt, G, & … (2018). Constructing probabilistic scenarios for wide-area solar power generation. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X17310605
Peronato, G, Rastogi, P, Rey, E, & Andersen, M (2018). A toolkit for multi-scale mapping of the solar energy-generation potential of buildings in urban environments under uncertainty. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X18307862
Mejia, JF, Giordano, M, & Wilcox, E (2018). Conditional summertime day-ahead solar irradiance forecast. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X18301154
Gamarro, H, Gonzalez, JE, & … (2018). Urban WRF-Solar Validation and Potential for Power Forecast in New York City. Energy …, asmedigitalcollection.asme.org, https://asmedigitalcollection.asme.org/ES/proceedings-abstract/ES2018/V001T09A001/269942
Spiess, R (2018). Imitation Learning for Photovoltaic Power Fluctuation., research-collection.ethz.ch, https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/303532/1/Spiess_Robin.pdf
Ruth, D, & Muller, M (2018). A methodology to analyze photovoltaic tracker uptime. Progress in Photovoltaics: Research and …, Wiley Online Library, https://doi.org/10.1002/pip.3002
Lago, J, Brabandere, K De, Ridder, F De, & … (2018). A generalized model for short-term forecasting of solar irradiance. … IEEE Conference on …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8618693/
Hafez, AAA, & Alblawi, A (2018). A feasibility study of PV installation: Case study at Shaqra University. 2018 9th International Renewable …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8362486/
Litjens, G, Worrell, E, & Sark, W Van (2018). Economic benefits of combining self-consumption enhancement with frequency restoration reserves provision by photovoltaic-battery systems. Applied energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261918305622
Bognár, Á, Loonen, R, Valckenborg, RME, & … (2018). Modeling reflected irradiance in urban environments–a case study for simulation-based measurement quality control for an outdoor PV test site. … Energy Conference and …, pure.tue.nl, https://pure.tue.nl/ws/files/110724078/6DO.10.4_paper.pdf
Bruinewoud, M (2018). Assessing the performance of the Utrecht Science Park PV system.
Moraitis, P, Kausika, BB, Nortier, N, & Sark, W Van (2018). Urban environment and solar PV performance: the case of the Netherlands. Energies, mdpi.com, https://www.mdpi.com/297244
Klise, KA, & Hart, D (2018). Pecos and Canary Webinar.., osti.gov, https://www.osti.gov/servlets/purl/1511107
Taghezouit, B, Arab, A Hadj, Larbes, C, & … (2018). Dynamic Modelling and Performance Analysis for a Grid-Connected PV System under LabVIEW. … Seminar on New and …, researchgate.net, https://www.researchgate.net/profile/A-Hadj-Arab/publication/328601814_Dynamic_Modelling_and_Performance_Analysis_for_a_Grid-Connected_PV_System_under_LabVIEW/links/610931a9169a1a0103d4fa4f/Dynamic-Modelling-and-Performance-Analysis-for-a-Grid-Connected-PV-System-under-LabVIEW.pdf
Massidda, L, & Marrocu, M (2018). Quantile regression post-processing of weather forecast for short-term solar power probabilistic forecasting. Energies, mdpi.com, https://www.mdpi.com/312484
Dzurick, MR (2018). Exploration of Sensor Systems for Increasing the Accuracy of Photovoltaic Modeling Application to the TEP/AzRISE Solar Test Yard., search.proquest.com, https://search.proquest.com/openview/6c20a34c4344792b63248cd4e46a4d08/1?pq-origsite=gscholar&cbl=18750&diss=y
Kam, MJ Van der, Meelen, AAH, Sark, W Van, & … (2018). Diffusion of solar photovoltaic systems and electric vehicles among Dutch consumers: Implications for the energy transition. Energy research & …, Elsevier, https://www.sciencedirect.com/science/article/pii/S2214629618305875
MacAlpine, SM, Wolfrom, CW, & … (2018). Evaluation of Irradiance Transposition Models When Utilized with Single Axis Tracking PV Systems in the Southwestern United States. 2018 IEEE 7th World …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8547777/
Hariharan, A, Karady, GG, & … (2018). Application of Machine Learning Algorithm to Forecast Load and Development of a Battery Control Algorithm to Optimize PV System Performance in Phoenix, Arizona. 2018 North American …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8600594/
Buffat, R, Grassi, S, & Raubal, M (2018). A scalable method for estimating rooftop solar irradiation potential over large regions. Applied energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0306261918301272
DiOrio, NA, Blair, NJ, Freeman, JM, Habte, AM, & … (2018). Solar System Modeling at NREL., osti.gov, https://www.osti.gov/biblio/1477226
Lago, J, Brabandere, K De, Ridder, F De, & Schutter, B De (2018). Short-term forecasting of solar irradiance without local telemetry: A generalized model using satellite data. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X18307138
Øgaard, MB, Haug, H, & Selj, JHK (2018). Methods for quality control of monitoring data from commercial PV systems. Proceedings of the European …, duo.uio.no, https://www.duo.uio.no/handle/10852/71679
Dupin, N (2018). Portfolio balancing strategy for the integration of renewable energy sources to the day ahead market., diva-portal.org, https://www.diva-portal.org/smash/record.jsf?pid=diva2:1295919
Schweighofer, B, Buchroithner, A, & … (2018). Generic Simulation Framework for Grid-Connected Photovoltaic and Energy Storage Systems. 2018 IEEE Green …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8745548/
Narayan, N, Vega-Garita, V, Qin, Z, & … (2018). A modeling methodology to evaluate the impact of temperature on Solar Home Systems for rural electrification. 2018 IEEE …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8398756/
Stein, J (2018). FY2018 PV Lifetime Annual Report.., osti.gov, https://www.osti.gov/servlets/purl/1484335
Li, X (2018). Radiative Effects of Atmospheric Aerosols and Impacts on Solar Photovoltaic Electricity Generation., search.proquest.com, https://search.proquest.com/openview/e669cd1478b33d5212c565885a26944c/1?pq-origsite=gscholar&cbl=18750
Prisikar, M (2018). Feasibility study of renovation of a residential building in near zero-energy building., aaltodoc.aalto.fi, https://aaltodoc.aalto.fi/handle/123456789/32460
Beebe, NHF (2018). A Complete Bibliography of Publications in the Journal of Open Source Software., netlib.org, http://www.netlib.org/tex/bib/joss.pdf
Prieto, E Castillo (2018). Predicción de Energía Fotovoltaica a partir de Ensembles NWP., repositorio.uam.es, https://repositorio.uam.es/handle/10486/685414
Mountain, B, Percy, S, Kars, A, Saddler, H, & Billimoria, F (2018). Does renewable electricity generation reduce electricity prices?., apo.org.au, https://apo.org.au/node/226981
Litjens, G (2018). Here comes the sun: Improving local use of electricity generated by rooftop photovoltaic systems., dspace.library.uu.nl, https://dspace.library.uu.nl/handle/1874/373082
Edition, F (2018). A Solar Design Manual for Alaska., acep.uaf.edu, https://acep.uaf.edu/media/260463/EEM-01255_SolarDesignManual_5thEd201805.pdf
Nagel, J (2018). Optimization of Energy Supply Systems., Springer, https://doi.org/10.1007/978-3-319-96355-6
Touz, N Le (2018). Conception et étude d’infrastructures de transports à énergie positive: de la modélisation thermomécanique à l’optimisation de tels systèmes énergétiques., tel.archives-ouvertes.fr, https://tel.archives-ouvertes.fr/tel-01959310/
Agutu, CO (2018). Influence of spectral beam splitting on the performance of polycrystalline silicon PV cells., repository.up.ac.za, https://repository.up.ac.za/handle/2263/66384
Krishnamurthy, CKB, Vesterberg, M, Böök, H, & … (2018). Real-time pricing revisited: Demand flexibility in the presence of micro-generation. Energy policy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0301421518305524
Wilson, TA (2018). Evaluating the Effectiveness of Current Atmospheric Refraction Models in Predicting Sunrise and Sunset Times., search.proquest.com, https://search.proquest.com/openview/22ac065f7c59d07245c502279b2849eb/1?pq-origsite=gscholar&cbl=18750
Huuki, H, Karhinen, S, Böök, H, Lindfors, AV, & … (2018). Virtual Power Plant Operation with Solar Power Forecast Errors and Demand Response. Available at SSRN …, papers.ssrn.com, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3277354
Yang, D, Kleissl, J, Gueymard, CA, Pedro, HTC, & … (2018). History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X17310022
Krishnamurthy, CK, Vesterberg, M, Böök, H, Lindfors, AV, & … (2018). Benefits of real-time pricing and rooftop solar PV generation: Explorations using Swedish micro-data., papers.ssrn.com, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3144215
Jacobo, AF Zambrano (2018). Predicción de irradiación solar en Colombia a partir de mediciones en sitio y satelitales utilizando redes neuronales., repositorio.uniandes.edu.co, https://repositorio.uniandes.edu.co/bitstream/handle/1992/39107/u820956.pdf?sequence=1
Han, X, & Xu, L (2018). Technology Adoption in Input-Output Networks. Available at SSRN 3266251, papers.ssrn.com, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3266251
Freitas, SRT (2018). Photovoltaic potential in building façades., repositorio.ul.pt, https://repositorio.ul.pt/handle/10451/34868
Sartor, K (2018). Développement d’un outil de simulation et d’analyse technico-économique et environnementale d’un réseau de chaleur., orbi.uliege.be, https://orbi.uliege.be/handle/2268/229271
Scheiber, G (2018). Gesamtheitliche Modellierung von leitungsgebundenen Energiesystemen mit exergetischer Bewertung., pure.unileoben.ac.at, https://pure.unileoben.ac.at/portal/en/publications/gesamtheitliche-modellierung-von-leitungsgebundenen-energiesystemen-mit-exergetischer-bewertung(ee724293-b5e1-4547-bde4-0add5f1641fd).html
Gurupira, T, & Rix, A (2017). Pv simulation software comparisons: Pvsyst, nrel sam and pvlib. Conf.: SAUPEC, orcun.baslak.com.

2017

Holmgren, WF, Lorenzo, AT, & … (2017). A comparison of pv power forecasts using pvlib-python. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366724/
Stein, J (2017). PV Performance Modeling Methods and Practices.., osti.gov, https://www.osti.gov/servlets/purl/1474242
Stein, J (2017). Challenges of PV Degradation Analysis: PVLIB and Performance Data Analysis.., osti.gov, https://www.osti.gov/servlets/purl/1482294
Ransome, S. and Sutterlueti, J. (2017). “OPTIMUM USE OF THE LOSS FACTORS MODEL (LFM) FOR IMPROVED PV PERFORMANCE MODELLING”, 13th PVSAT 2017 Bangor, UK,
Ransome, S. and Sutterlueti, J. (2017). “Choosing the best Empirical Model for predicting energy yield”, 7th PV Energy Rating and Module Performance Modeling Workshop, Canobbio, Switzerland 2017, https://www.slideshare.net/sandiaecis/15-2017-pvpmc7ransome170330t081corrected2-74980695
Gurupira, T, & Rix, AJ (2017). Pv simulation software comparisons: Pvsyst, nrel sam and pvlib,(january).
Benito, AJ Gil de Santivañes de (2017). Interfaz gráfica para el modelado de sistemas fotovoltaicos mediante el paquete de funciones de código abierto PVLIB.., oa.upm.es, https://oa.upm.es/id/eprint/47456
Stein, J (2017). PV System Performance Modeling.., osti.gov, https://www.osti.gov/servlets/purl/1418248
Li, X, Wagner, F, Peng, W, Yang, J, & … (2017). Reduction of solar photovoltaic resources due to air pollution in China. Proceedings of the …, National Acad Sciences, https://www.pnas.org/content/114/45/11867.short
Mikofski, MM, Hansen, CW, & … (2017). Use of measured aerosol optical depth and precipitable water to model clear sky irradiance. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366314/
Klise, KA, Stein, JS, & … (2017). Application of IEC 61724 Standards to Analyze PV System Performance in Different Climates. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366666/
Hansen, CW, Stein, J, & Riley, DM (2017). 2017 IEEE PVSC tutorial PV system modeling.., osti.gov, https://www.osti.gov/servlets/purl/1513607
Gurupira, T, & Rix, A (2017). PV simulation software comparisons: PVSYST. NREL SAM AND PVLIB
Anoma, M Abou, Jacob, D, Bourne, BC, & … (2017). View factor model and validation for bifacial PV and diffuse shade on single-axis trackers. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366704/
Klise, GT (2017). Reliability Impacts to PV Plant Performance: Methods and Tools for O&M Insight.., osti.gov, https://www.osti.gov/servlets/purl/1427416
Jordan, DC, Deline, C, Kurtz, SR, & … (2017). Robust PV degradation methodology and application. IEEE Journal of …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8233204/
Lee, KH, Araki, K, Elleuch, O, Kojima, N, & … (2017). Pypvcell: An open-source solar cell modeling library in Python. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366371/
Klise, KA (2017). Pecos Open Source Software for PV Performance Monitoring.., osti.gov, https://www.osti.gov/servlets/purl/1457957
Kühnel, M, Hanke, B, Geißendörfer, S, & … (2017). Energy forecast for mobile photovoltaic systems with focus on trucks for cooling applications. Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.2886
Haapaniemi, J, Narayanan, A, Tikka, V, & … (2017). Effects of major tariff changes by distribution system operators on profitability of photovoltaic systems. … Conference on the …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7981935/
Petric, T, Dupont, C, & Gall, F Le (2017). Evaluating benefits of adding intelligence to small-scale renewable energy systems. IEEE EUROCON 2017-17th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8011139/
Stein, JS, Riley, D, Lave, M, Hansen, C, & … (2017). Outdoor field performance from bifacial photovoltaic modules and systems. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366042/
Litjens, G, Kausika, BB, Worrell, E, & … (2017). Spatial Analysis of Residential Combined Photovoltaic and Battery Potential: Case Study Utrecht, the Netherlands. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366519/
II, DJ Gagne, McGovern, A, Haupt, SE, & Williams, JK (2017). Evaluation of statistical learning configurations for gridded solar irradiance forecasting. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X17303158
Klise, GT, Freeman, JM, & Lavrova, O (2017). Simulating PV System Performance with Component Reliability Distributions. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366397/
Litjens, G, Worrell, E, & Sark, W Van (2017). Influence of demand patterns on the optimal orientation of photovoltaic systems. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X17305856
Catalina, A, Torres-Barrán, A, & Dorronsoro, JR (2017). Satellite based nowcasting of PV energy over peninsular Spain. … Work-Conference on …, Springer, https://doi.org/10.1007/978-3-319-59153-7_59
Haschke, J, Seif, JP, Riesen, Y, Tomasi, A, & … (2017). Energy Yield in Hot & Sunny Climates: Impact of Silicon Solar Cell Architecture and Cell Interconnection. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366703/
Chen, D, & Irwin, D (2017). Black-box solar performance modeling: Comparing physical, machine learning, and hybrid approaches. ACM SIGMETRICS Performance Evaluation Review, dl.acm.org, https://doi.org/10.1145/3152042.3152067
Louwen, A, Schropp, REI, Sark, WG van, & Faaij, APC (2017). Geospatial analysis of the energy yield and environmental footprint of different photovoltaic module technologies. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X17306412
Elsinga, B, Sark, W van, & … (2017). Inverse photovoltaic yield model for global horizontal irradiance reconstruction. Energy Science & …, Wiley Online Library, https://doi.org/10.1002/ese3.162
Pannebakker, BB, Waal, AC de, & … (2017). Photovoltaics in the shade: one bypass diode per solar cell revisited. Progress in …, Wiley Online Library, https://doi.org/10.1002/pip.2898
Moraitis, P, Kausika, BB, & … (2017). Effects of Urban Environment on Solar PV Performance. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366669/
Jenson, D, D’Sa, R, Henderson, T, Kilian, J, & … (2017). Energy characterization of a transformable solar-powered unmanned aerial vehicle. 2017 IEEE/RSJ …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8206401/
Computação, C da (2017). Mateus MS do Nascimento.
Polo, J, Fernandez-Neira, WG, & Alonso-García, MC (2017). On the use of reference modules as irradiance sensor for monitoring and modelling rooftop PV systems. Renewable energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0960148117300265
Steiner, M, Gerstmaier, T, & Bett, AW (2017). Concentrating photovoltaic systems. The Performance of Photovoltaic (PV) …, Elsevier, https://www.sciencedirect.com/science/article/pii/B9781782423362000100
Curran, AJ, Hu, Y, Haddadian, R, Braid, JL, & … (2017). Determining the power rate of change of 353 plant inverters time-series data across multiple climate zones, using a month-by-month data science analysis. 2017 IEEE 44th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/8366477/
Hamann, HF (2017). A multi-scale, multi-model, machine-learning solar forecasting technology., osti.gov, https://www.osti.gov/biblio/1395344
Thiébaut, J (2017). Theoretical and experimental investigations of parabolic trough collectors for a small-scale solar thermal power plant., matheo.uliege.be, https://matheo.uliege.be/handle/2268.2/3210
López, AB Cristóbal, Nadal, C Cañizo, Vega, A Martí, & … (2017). Fostering a Next GeneRation of European Photovoltaic SoCiety through Open Science-GRECO 787289., oa.upm.es, http://oa.upm.es/50489/1/GRECO_section1-3_abc45%20.pdf
Lovati, M, Maturi, L, Adami, J, & Moser, D (2017). Methodologies and tools for BIPV implementation in the early stage of the architectural design. 12th conference on Advanced …, iris.unitn.it, https://iris.unitn.it/bitstream/11572/263544/4/Tesi_Lovati_202005_definitiva.pdf
Chambers, JD (2017). Developing a rapid, scalable method of thermal characterisation for UK dwellings using smart meter data., discovery.ucl.ac.uk, https://discovery.ucl.ac.uk/id/eprint/10030678/

2016

Stein, JS, Holmgren, WF, Forbess, J, & … (2016). PVLIB: Open source photovoltaic performance modeling functions for Matlab and Python. 2016 ieee 43rd …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7750303/
Holmgren, WF, & Groenendyk, DG (2016). An open source solar power forecasting tool using PVLIB-Python. 2016 ieee 43rd photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7749755/
Gurupira, T, & Rix, AJ (2016). Photovoltaic System Modelling using PVLib-Python. Fourth South African Solar Energy …, researchgate.net, https://www.researchgate.net/profile/Arnold-Rix/publication/313249264_PHOTOVOLTAIC_SYSTEM_MODELLING_USING_PVLIB-PYTHON/links/589440ddaca27231daf6340f/PHOTOVOLTAIC-SYSTEM-MODELLING-USING-PVLIB-PYTHON.pdf
Stein, J (2016). 2016 PVLIB Users Group Meeting.., osti.gov, https://www.osti.gov/servlets/purl/1514526
Ransome, S, Stein, J, Holmgren, W, & … (2016). PV Performance modelling with PVPMC/PVLIB. PVSAT12, pdfs.semanticscholar.org, https://pdfs.semanticscholar.org/516e/d000fa1e9910668d6960c05c2db2816e3e27.pdf
Klise, KA, & Stein, JS (2016). Automated performance monitoring for PV systems using pecos. 2016 IEEE 43rd Photovoltaic Specialists …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7750304/
Li, X, Mauzerall, DL, Wagner, F, & … (2016). Impact of Atmospheric Aerosols on Solar Photovoltaic Electricity Generation in China. AGU Fall Meeting …, ui.adsabs.harvard.edu, https://ui.adsabs.harvard.edu/abs/2016AGUFMGC53G..05L/abstract
Deline, C, DiOrio, N, Jordan, D, & Toor, F (2016). Progress & frontiers in PV performance., osti.gov, https://www.osti.gov/biblio/1327483
Lee, M, & Panchula, A (2016). Spectral correction for photovoltaic module performance based on air mass and precipitable water. 2016 IEEE 43rd Photovoltaic Specialists …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7749836/
Klise, GT (2016). PV System Reliability: An O&M Perspective.., osti.gov, https://www.osti.gov/servlets/purl/1346103
Passow, K, & Lee, M (2016). Effect of spectral shift on solar PV performance. 2016 IEEE Conference on Technologies for …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7897175/
Litjens, G, Sark, W Van, & Worrell, E (2016). On the influence of electricity demand patterns, battery storage and PV system design on PV self-consumption and grid interaction. 2016 IEEE 43rd Photovoltaic …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7749983/
Klise, KA, & Stein, J (2016). Performance Monitoring using Pecos Version 0.1.., osti.gov, https://www.osti.gov/servlets/purl/1734479
Mikofski, M, Oumbe, A, Li, C, & … (2016). Evaluation and correction of the impact of spectral variation of irradiance on pv performance. 2016 ieee 43rd …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7749837/
Ruf, H, Schroedter-Homscheidt, M, Heilscher, G, & … (2016). Quantifying residential PV feed-in power in low voltage grids based on satellite-derived irradiance data with application to power flow calculations. Solar Energy, Elsevier, https://www.sciencedirect.com/science/article/pii/S0038092X16301803
Polo, J, Garcia-Bouhaben, S, & … (2016). A comparative study of the impact of horizontal-to-tilted solar irradiance conversion in modelling small PV array performance. Journal of Renewable …, aip.scitation.org, https://doi.org/10.1063/1.4964363
Phinikarides, A, Shimitra, C, Bourgeon, R, & … (2016). Development of a novel web application for automatic photovoltaic system performance analysis and fault identification. 2016 IEEE 43rd …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7749921/
Lassila, J, Tikka, V, Haapaniemi, J, Child, M, Breyer, C, & … (2016). Nationwide photovoltaic hosting capacity in the Finnish electricity distribution system. … Photovoltaic Solar Energy …
Lave, M, Stein, J, & Smith, R (2016). Solar variability datalogger. Journal of Solar …, asmedigitalcollection.asme.org, https://asmedigitalcollection.asme.org/solarenergyengineering/article-abstract/138/5/054503/383682
Ruf, H, Schroedter-Homscheidt, M, Beyer, HG, & … (2016). Simulation of the Load Flow at the Transformer in Low Voltage Distribution Grids with a Significant Number of PV Systems using Satellite-derived Solar …. Sol. Energy, researchgate.net, https://www.researchgate.net/profile/Holger-Ruf/publication/304525176_Simulation_of_the_Load_Flow_at_the_Transformer_in_Low_Voltage_Distribution_Grids_with_a_Significant_Number_of_PV_Systems_using_Satellite-Derived_Solar_Irradiance/links/57723db708ae842225adc8d4/Simulation-of-the-Load-Flow-at-the-Transformer-in-Low-Voltage-Distribution-Grids-with-a-Significant-Number-of-PV-Systems-using-Satellite-Derived-Solar-Irradiance.pdf
Tomažič, T (2016). Napovedovanje dnevne proizvodnje električne energije sončnih elektrarn., eprints.fri.uni-lj.si, http://eprints.fri.uni-lj.si/3650/
Ruf, HI (2016). Computation of the load flow at the transformer in distribution grids with a significant number of photovoltaic systems using satellite-derived solar irradiance data., uia.brage.unit.no, https://uia.brage.unit.no/uia-xmlui/bitstream/handle/11250/2398250/Dissertation_Holger-Ruf_Print-Version_embedded_Fonts.pdf?sequence=1
Hernández-Torres, D, Turpin, C, & … (2016). Modélisation en ﬂux d’énergie d’une batterie Li-Ion en vue d’une optimisation technico économique d’un micro-réseau intelligent. … de Genie Electrique, hal.archives-ouvertes.fr, https://hal.archives-ouvertes.fr/hal-01361618/
Fortuna, L, Nunnari, G, & Nunnari, S (2016). Nonlinear modeling of solar radiation and wind speed time series., Springer, https://doi.org/10.1007/978-3-319-38764-2
Campaigne, C, Balandat, M, & Ratliff, L (2016). Welfare effects of dynamic electricity pricing. Working Paper, ocf.berkeley.edu, https://www.ocf.berkeley.edu/~clay/file/SimulatingDynamicTariffs.pdf
Banadkooki, AS (2016). Prediction of Photovoltaic Power Generation from Cloud Imaging., research-collection.ethz.ch, https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/155770/eth-49449-01.pdf
Altes-Buch, Q (2016). Mechanical design, control and optimization of a hybrid solar microgrid for rural electrification and heat supply in sub-Saharan Africa., orbi.uliege.be, https://orbi.uliege.be/bitstream/2268/208976/1/QAB_MasterThesis.pdf

2015

Holmgren, WF, Andrews, RW, & … (2015). PVLIB python 2015. 2015 ieee 42nd …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7356005/
Ellis, A (2015). Large-Scale Photovoltaics deployment.., osti.gov, https://www.osti.gov/servlets/purl/1333247
Köhler, C, Ruf, H, Steiner, A, Lee, D, & … (2015). Nutzung Numerischer Wettervorhersagen in der Simulation von Verteilnetzen: Die Effekte einer Sonnenfinsternis auf netzgekoppelte PV-Anlagen und …. 30th Symposium …, researchgate.net, https://www.researchgate.net/profile/Carmen-Koehler/publication/273143752_Nutzung_Numerischer_Wettervorhersagen_in_der_Simulation_von_Verteilnetzen_Die_Effekte_einer_Sonnenfinsternis_auf_netzgekoppelte_PV-Anlagen_und_Netztransformatoren/links/554b7f3f0cf21ed2135948f7/Nutzung-Numerischer-Wettervorhersagen-in-der-Simulation-von-Verteilnetzen-Die-Effekte-einer-Sonnenfinsternis-auf-netzgekoppelte-PV-Anlagen-und-Netztransformatoren.pdf
Ruf, H, Schroedter-Homscheidt, M, & … (2015). Load Flow Calculation of a Low Voltage Transformer using Satellitebased Irradiance Data. … ETG Congress 2015 …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/7388521/
Stein, JS (2015). FY15 Final Technical Report for DOE SunShot., osti.gov, https://www.osti.gov/servlets/purl/1232610
Andrews, RW, Stein, JS, Hansen, C, & … (2014). Introduction to the open source PV LIB for python Photovoltaic system modelling package. 2014 IEEE 40th …, ieeexplore.ieee.org, https://ieeexplore.ieee.org/abstract/document/6925501/
Stein, J. S. and M. Green (2015). Novel strategies for PV system monitoring. PV-Tech Power. London, UK, Solar Media. 02.
Ransome, S., Sutterlueti, J., Scholz, J, Stein, J.S. (2015). Improved PV Performance modelling by combining the PV_LIB Toolbox with the Loss Factors Model (LFM), 42nd IEEE PV Specialists Conference, New Orleans, LA, USA.

2014

Andrews, R. W., J. S. Stein, C. Hansen and D. Riley (2014). Introduction to the open source PV LIB for python Photovoltaic system modelling package. 2014 IEEE 40th photovoltaic specialist conference (PVSC), IEEE.
Riley, DM, Stein, J, Hansen, CW, & Andrews, R (2014). 2014 IEEE PVSC Tutorial on PV System Performance Modeling.., osti.gov, https://www.osti.gov/servlets/purl/1714482
Stein, JS, & Toolbox, P (2014). Sandia National Laboratories: Albuquerque. NM, USA
Rogers, E, & Sexton, S (2014). Distributed Decisions: The Efficiency of Policy for Rooftop Solar Adoption. Online at https://www. aeaweb. org …, evangrogers.org, https://evangrogers.org/wp-content/uploads/2014/04/Rogers_JMP.pdf
Gregg, DC, Murgia, FM, & Seydioglu, B (2014). Solar Panel Layout and Installation. US Patent App. 13/551,863, Google Patents, https://patents.google.com/patent/US20140025343A1/en
Nogueira, PHO (2014). Simulação do desempenho de sistemas solares fotovoltaicos para a geração de eletricidade: um estudo de caso do sistema fotovoltaico da embaixada da Itália., bdm.unb.br, https://bdm.unb.br/handle/10483/9270

2013

Stein, J. S. and B. H. King (2013). Modeling for PV plant optimization. Photovoltaics International, Solar Media Ltd. 19th: 101-109.