Solar Energy Modeling Services

SolarAnywhere® energy modeling services offer customers easy, on-demand access to SolarAnywhere’s high- fidelity weather data and site-specific PV energy estimates through a single, integrated API platform.

SolarAnywhere energy modeling services have been designed with a modular architecture to provide flexibility in selecting from available weather data and PV energy simulation models. The API supports the use of SolarAnywhere typical year (TGY) and time-series (Sites) data, as well as NREL TMY3 weather data. Figure 1 below depicts the modular architecture of SolarAnywhere’s energy modeling services.

Figure 1: Modular Software Architecture of the SolarAnywhere Energy Modeling Services

Simulation Tool Modular Architecture

Energy Simulation Steps

With a single call to the SolarAnywhere API, you can simulate the output of a single PV system or group of PV systems under your license. Returning simulated outputs for your system(s) requires three steps:

  1. 1. Create Energy Site(s): Create an energy site or multiple energy sites that are representative of your actual PV system(s). You can simulate PV system output with just a few basic inputs about your PV system or utilize all available inputs for more precise modeling. Retrieve the EnergySiteId(s) from your request(s) for use in step 2.
  2. 2. Create a Simulation Request: Create a simulation request with the EnergySiteId(s) created in the first step. Specify your choice of power model, simulation and weather outputs, weather data source, and models for simulating energy losses. Retrieve the SimulationId returned from your request for use in step 3.
  3. 3. Get Simulation Results: Using the SimulationId generated in step 2, retrieve the requested weather & irradiance data and simulated PV project output.

It should be noted that uncertainty in energy simulations varies from site to site depending on a number of factors, such as the accuracy of the weather data and system specifications, as well as environmental and system loss assumptions. The various sources of uncertainty and their associated ranges are reported in the publication: “On-site performance verification to reduce yield prediction uncertainties. Reich et al, 2015 IEEE 42nd Photo Voltaic Specialist Conference (PVSC).” SolarAnywhere solar irradiance data is widely used for independent and bankable solar resource assessment, operational monitoring and solar forecasting. Visit our validation page for up-to-date information on model accuracy.


Energy Simulation Models

SolarAnywhere customers can choose from two available energy simulation models: pvlib and CprPVForm.


Initially developed at Sandia National Laboratories, pvlib python is a peer-reviewed1, community maintained, open-source library developed on GitHub. Pvlib provides a set of functions and classes for simulating the performance of PV energy systems. The broader solar community develops, validates and frequently updates pvlib models. The pvlib models integrated into SolarAnywhere support NREL PVWatts as the core engine for simulating module and inverter performance. PVWatts makes internal assumptions about module and inverter characteristics, enabling SolarAnywhere users to quickly model any PV system type and configuration with just a few key inputs.

To enable SolarAnywhere customers to take advantage of the latest research in PV modeling, SolarAnywhere offers the most recent and stable version of pvlib through its API services. Table 1 shows the various models included in SolarAnywhere’s implementation of pvlib, and their relevant publications with model description and validation.

Table 1: Models included in SolarAnywhere’s implementation of pvlib
pvlib Solar Simulation Models
Transposition Model Perez
Temperature Model Faiman
DC Model PVWatts DC Power Model
AC Model PVWatts Inverter Model
Reflection Losses Incidence Angle Modifier (IAM) Physical
(with customization to include modeling for diffuse reflectivity losses)
Snow Losses

NREL (Marion) Model

Townsend Model

Soiling Losses

Humboldt State University (HSU) Model

Kimber Model

Bifacial PV model Infinite Sheds Model

The PVForm model was originally developed by the Sandia National Labs in 1985. In partnership with the SUNY Albany team, Clean Power Research developed an in-house implementation of PVForm called ‘CprPVForm’. The CprPVForm model implements many modeling algorithms found in the PVForm and PVWatts v1 models and has been used in assessing the energy performance of PV fleets.

Table 2 outlines the capabilities and limitations of the two energy models.

Table 2: Comparison of the CprPVForm and pvlib solar simulation models
CprPVForm pvlib
General Derate Percent Default: 0.40%/°C Default: 0.37%/°C
Module Power Temperature Coefficient Default: 85% Default: 86%
Module Rating PTC Rating STC Rating
Tracking types Fixed-Axis,
Single Axis,
Single Axis,
Single Axis with Backtracking
Reflection Losses No Yes
Near-object shading Yes Yes
Row-on-row shading Yes Yes
Snow Losses No Yes
Soiling Losses No Yes
Bifacial PV Modeling No Yes
Frequently Asked Questions
Contact us to request a demo of SolarAnywhere’s energy performance simulation capabilities.

1 Holmgren W, Hansen CW, Mikofski MA. 2018. pvlib python: a python package for modeling solar energy systems. Journal of Open Source Software (JOSS). DOI: 10.21105/joss.00884. Link.

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