The Sandia Inverter Model provides a means to predict AC output power () from DC input power ().

The form of the model is as follows:

where

,

, and

Parameters:

• : DC input voltage (V).  This is typically assumed to be the array’s maximum power voltage.
• : DC voltage level (V) at which the AC power rating is achieved at reference operating conditions.
• : AC output power (W)
• : Maximum AC power rating for inverter at reference conditions (W).  Assumed to be an upper limit.
•  : DC power level (W) at which the AC power rating is achieved at reference operating conditions.
• : DC power required to start the inversion process (W)
• : Parameter defining the curvature of the relationship between AC output power and DC input power
• : empirical coefficient allowing  to vary linearly with DC-voltage input, default value
is zero, (1/V)
• : empirical coefficient allowing  to vary linearly with DC-voltage input, default value
is zero, (1/V)
• : empirical coefficient allowing  to vary linearly with dc-voltage input, default value is
zero, (1/V)

#### Algorithm to estimate model parameters from inverter efficiency curves

The Sandia inverter model requires eight parameters: .

Given measurements of an inverter’s AC power, DC voltage and efficiency, parameters for the Sandia inverter model are determined by the following algorithm. Denote the AC power measurements by  where  is the DC voltage level, is the power level, and  indexes the replicated measurements. Similarly denote the DC voltage measurements as  and measured efficiency as .

Step 1: Set  equal to the inverter’s AC rating.

Step 2: Calculate

Step 3: For  :

Step 3a: Calculate

Step 3b: Obtain coefficients  for a quadratic fit by linear regression using the data indexed by  :

Step 3c: Set

Step 3d: Solve each of the following equations to obtain :

Step 3e: Denote  and use linear regression on the data indexed by   to find coefficients   for each of

Step 4: Extract parameters as: