--- title: "PV simulators comparison: Overview" slug: "pv-simulators-comparison" description: "Compare Solargis Evaluate with top PV yield simulators, exploring methodology differences and energy yield impacts for informed design decisions." updated: 2026-08-11T06:45:19Z published: 2026-08-11T06:45:19Z canonical: "kb.solargis.com/pv-simulators-comparison" --- > ## Documentation Index > Fetch the complete documentation index at: https://kb.solargis.com/llms.txt > Use this file to discover all available pages before exploring further. # PV simulators comparison: Overview **In this document** This article introduces the comparison of Solargis Evaluate against five other PV yield simulators across the full PV simulation chain. It summarizes the comparison setup, the main results, and the methodology differences across the simulators, and points to dedicated articles for each stage of the simulation chain. ### Overview PV yield simulation software differ in the data they consume, the models they implement, the assumptions they make, and the way they report intermediate results. For an investor, an independent engineer, or a developer choosing between simulation software, these differences affect the simulated energy yield and impact design decisions. The Comparison of PV simulators series compares Solargis Evaluate against four widely used PV simulators: **PVsyst**, the National Laboratory of the Rockies (NLR) **System Advisor Model** (SAM), the open-source **pvlib Python library**, and **DNV's SolarFarmer**. Solargis Prospect, the simplified site assessment tool from Solargis, is included as a sixth comparator to show how it relates to Solargis Evaluate. The comparison is **methodology-driven**: each simulator runs the same six test sites and the same four PV system configurations, and the results are compared topic by topic across the full simulation chain. The goal is to **characterize where simulators differ in approach and in output**, not to validate any simulator against measured plant data. The methodology references industry-standard, peer-reviewed models. ### PV simulators compared Where possible, each compared simulator is configured to use the same input data, the same model selections, and the same system parameters to observe differences in methodology rather than configuration choices. | PV simulator | Version | Type | | --- | --- | --- | | Solargis Evaluate | v2.5 | Commercial, cloud-based | | Solargis Prospect | v2.5 | Commercial, cloud-based | | PVsyst | v8.1.4 | Commercial, desktop | | System Advisor Model (SAM) | v2025.4.16 | Free, desktop (NLR) | | pvlib | v0.13.1 | Open-source Python library | | SolarFarmer | v1.6 | Commercial, desktop and cloud (DNV) | ***Table 1****: Compared PV simulators.* ### What is compared The comparison covers the three stages of the PV simulation chain: - **Inputs:** Solar resource, meteorological and environmental data, and scene definition. - **Optical simulation:** Plane-of-array irradiance, including transposition, rear-side irradiance for bifacial PV modules, horizon shading, near shading, and PV module losses (soiling, snow, angular, spectral). - **Electrical simulation:** DC/AC conversion, DC cabling, inverter, auxiliary, AC cabling, transformer, grid connection, and unavailability. These stages are unpacked across eight dedicated articles in this series: - [Setup and test methodology](/v1/docs/comparison-setup-and-test-methodology): test sites, test system configurations, simulator versions, and statistical metrics. - [Solar data and system configuration](/v1/docs/comparison-solar-data-and-system-config): data inputs, scene modelling, and simulation chain variables. - [Irradiance modeling](/v1/docs/comparison-irradiance-modeling): GTI transposition, rear-side irradiance for bifacial PV modules, horizon shading, near shading. - [Optical losses](/v1/docs/comparison-optical-losses): soiling, snow, angular, spectral. - [Electrical modeling of the DC side](/v1/docs/pv-simulators-comparison-electrical-modeling-of-the-dc-side): electrical chain from PV cell to inverter AC output. - [Electrical modeling of the AC side](/v1/docs/clone-pv-simulators-comparison-electrical-modeling-of-the-ac-side): electrical chain from inverter AC output to grid delivery. - [Conclusion](/v1/docs/pv-simulators-comparison-conclusion): overall results of the comparison with interpretation - [Detailed results and analysis](/v1/docs/pv-simulators-comparison-detailed-results-analysis): a deep dive into the most salient results with a detailed analysis ### Results summary Across the full PV simulation chain, from solar radiation to power at the grid connection point, **pvlib, PVsyst, and SAM all agree relatively closely with Solargis Evaluate**. The median bias stays inside ±3.2% for every simulator and mounting configuration, most values (44/72 test cases) fall inside ±2%, and the largest single deviation stays under 8%. **All three simulators tend to calculate slightly less energy delivered to the grid than Solargis Evaluate**, but none of them sits consistently below it: each one crosses to the other side at some sites and mounting configurations. The direction and size of the difference depend on the mounting configuration and the site climate, and the differences are systematic rather than random scatter, traceable to specific steps in the simulation chain. These effects in individual simulation steps are investigated in the next articles in this series. For the full breakdown of the differences in the final output of the simulation (energy delivered to the grid) and the underlying analysis of why these differences occur see the [Conclusion](/v1/docs/pv-simulators-comparison-conclusion) article. A sample result is shown in Figure 1 below – the total energy delivered to the grid as a bias of the three compared simulators against Solargis Evaluate. > [!TIP] > **Note**: Solargis Evaluate is used as the mathematical reference series for bias and RMSE calculations across this comparison series. These statistics require a reference, and Solargis Evaluate is one suitable choice. This convention does not imply Solargis Evaluate is more accurate than the other simulators. ![](https://cdn.document360.io/ae2d502f-6c0d-4865-a68e-43ad8da61149/Images/Documentation/ac_grid__summary__bias(2).png) ***Figure 1****: Total energy delivered to the grid bias for pvlib, PVsyst, and SAM against Solargis Evaluate, as a percentage of the Solargis Evaluate value, by mounting configuration across the six test sites.* #### How the simulators compare on key capabilities Beyond the numerical results, the simulators differ structurally in the models they implement, the resolution they support, and the workflow they offer. Table 2 summarizes capabilities that users of PV simulation software commonly look at when choosing the right solution. The table shows: - Where the simulators are functionally equivalent (for example, all simulators support sub-hourly simulations in some form). - Where they differ in approach (ray tracing versus view factor, cell-level versus submodule IV curves). - Where each tool has its own characteristic strengths. Users should choose the simulator whose strengths align with their project requirements and workflow. | Capability | Solargis Evaluate | Solargis Prospect | pvlib | PVsyst | SAM | SolarFarmer | | --- | --- | --- | --- | --- | --- | --- | | **Built-in solar and meteorological database** | Yes | Yes | No | No | No | No | | **Native temporal resolution** | 15-minute, 1-minute | 15-minute input, hourly output, 12 daily profiles | Hourly or sub-hourly | Hourly or sub-hourly | Hourly or sub-hourly | Hourly or sub-hourly | | **Built-in soiling model** | Yes | No | Yes | No | No | No | | **Built-in snow model** | Yes | No | Yes | No | Yes | No | | **Visual scene editor** | Yes | No | No | Yes | Yes | Yes | | **Shading computation method** | 3D ray tracing | Advanced view factor | View factor | View factor | View factor | View factor | | **IV curve modeling** | Cell level | Cell level | Configurable | Submodule level | Submodule level | Submodule and string level | | **Transient thermal correction for PV cell** | Yes | No | Available | Available | Available | No | | **Inverter model** | SANDIA | SANDIA presets, or Euro-efficiency | SANDIA, Anton Driesse grid connected, PVWatts | PVsyst model | SANDIA, datasheet, NREL part-load | Efficiency curves | | **Transformer model** | Iron and copper losses, two stages | Simple efficiency | Iron and copper losses | Iron and copper losses, two stages | Iron and copper losses (as factors) | No-load and full-load efficiency | | **Integrated reporting and analysis** | Yes | Yes | No | Yes | Yes | Yes | ***Table 2****: Summarized capabilities of compared PV simulators.* ### Further reading #### Solargis knowledge base - "[Argus PV simulation chain](/v1/docs/argus-pv-simulation-chain)": Solargis - "[PV energy yield simulation](/v1/docs/pv-energy-yield-simulation)": Solargis - "[Understanding accuracy in solar software](/v1/docs/understanding-accuracy-in-solar-software)": Solargis #### Simulator comparison and models - ["Cross-validation of PV system simulation software"](https://www.researchgate.net/publication/335842590_Cross-validation_of_PV_System_Simulation_Software): Driesse, A., Patel, N. - "[Soiling Model for PV Applications: Improved Parameterizations](https://ieeexplore.ieee.org/document/10359694)": Lara-Fanego, V., Gueymard, C., Micheli, L. - ["HSU soiling model"](https://pvpmc.sandia.gov/modeling-guide/1-weather-design-inputs/shading-soiling-and-reflection-losses/soiling-losses/hsu-soiling-model/): PVPMC - ["Kimber soiling model"](https://pvpmc.sandia.gov/modeling-guide/1-weather-design-inputs/shading-soiling-and-reflection-losses/soiling-losses/kimber-soiling-model/)": PVPMC - "[Measured and modeled photovoltaic system energy losses from snow for Colorado and Wisconsin locations.](https://www.sciencedirect.com/science/article/abs/pii/S0038092X13003034)": Marion, B., Schaefer, R., Caine, H., Sanchez, G. - ["Townsend snow model"](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.snow.loss_townsend.html): pvlib documentation - "[Transient weighted moving-average model of photovoltaic module back-surface temperature](https://ieeexplore.ieee.org/document/9095219)": Prilliman, M, Stein, JS, Riley, D, Tamizhmani, G. - "[Performance Model for Grid-Connected Photovoltaic Inverters](https://www.osti.gov/servlets/purl/920449)": King, DL, Gonzalez, S., Galbraith, GM, Boyson, WE - "[Beyond the curves: Modeling the electrical efficiency of photovoltaic inverters](https://ieeexplore.ieee.org/document/4922827/)": Driesse, A., Jain, P., Harrison, S. - "[PVWatts Version 5 Manual](https://docs.nlr.gov/docs/fy14osti/62641.pdf)": Dobos, A.