Accurately model and optimise photovoltaic system performance using advanced optical, thermal, and electrical analytics with speed and precision.
Applications
Sophisticated PV system and project yield modelling that brings clarity and eliminates guesswork. Quickly compare configurations and designs with exceptional accuracy to optimise energy yield.
SunSolve's physics-based engine delivers far greater detail than simplified view-factor models. It seamlessly incorporates specific mounting structures, wavelength-dependent albedo, and other real-world complexities.
Accurately account for tilt angles, system pitch, and structural variations to model both fixed-tilt and tracker arrays with precision.
With bifacial modules now mainstream, generate precise rear-side production values, including the complex impact of mounting structures.
Pinpoint root causes of underperformance early, helping to avoid costly project delays and financial penalties.
Create energy-weighted correction factors (fS, fT, fA, fMR, fλ) directly from SunSolve simulations for use in PVsyst. Ensure consistent and auditable alignment across tools.
Explore system-level effects like edge brightening, sensor placement, and albedo boosters with high-fidelity optical-thermal modelling.
Features
Form meets function by combining a user-friendly interface with extreme computing power.
Forget correction factors for mismatch, shading, and spectrum. Simply input dimensions and material types and SunSolve Yield takes care of the rest.
While complexity can overwhelm less sophisticated engines, SunSolve models full systems in minutes, enabling rapid comparison and optimisation.
From fixed-tilt, 1P and 2P trackers to east-west and vertical arrays, SunSolve handles the widest range of configurations, and can even import custom CAD components for novel designs.
Enhanced Bankability
SunSolve's bifacial approach combined with PVSyst provide "the foundation for bankable, real-world modeling best practices for bifacial power plants." [1]
TECHNICAL SPECS
A side-by-side look at why SunSolve Yield leads in precision and performance.
| Feature | SunSolve Yield | PVsyst |
|---|---|---|
| Front-side direct irradiance | 3D ray tracing | Analytical calculation and polygon shadow mapping |
| Front-side diffuse irradiance | 3D ray tracing | Linearly-symmetric view factor |
| Rear-side and ground-reflected irradiance | 3D ray tracing | Linearly-symmetric view factor with correction factors |
| Module optics | IAM lookup table OR 3D ray tracing into module | IAM lookup table |
| Spectral effects | Full spectral solving (Atmosphere, albedo, system structure and module) | Correction factor (First Solar model) |
| Module temperature | Extended Faiman model. (Sky, ground, transients.) | Faiman model |
| Electrical output | Circuit solving Cell-level to module-level to string-level to array-level to inverter | IV solving at module-level and multipliers for string and array-level to inverter |
| Electrical mismatch | Calculated for cell-to-cell, module-to-module, string-to-string mismatch. | Shadow fraction and / or correction factors |
| Tandem modules | Available | Not available |
| Solving engine | Parallel processing in cloud | Local computer |
| Visualisation | Cell-level irradiance maps at every time step | Graphs & pedagogical tools |
| Results | Yield, waterfall loss chart, time-series download | Yield, waterfall loss chart, time-series download |
| Mounting structure definition | Load dimensions and materials | Load correction factors |
RELATED RESOURCES
Explore guides, papers, and supporting materials.
We released SunSolve P90 at ACP Peak 2025 - a free Python API that quantifies uncertainty in energy yield forecasts from PVsyst, SolarFarmer, PVLib, SunSolve and other tools using Monte Carlo simulation.
This post explores how to predict the bifacial gain of AgriPV systems, which can vary from 2% to 50% depending on system design and conditions. We describe SunSolve's ray-tracing method, PVsyst's industry-standard approach, and how they can be used together.
Our latest white paper examines how radiative heat loss to the sky affects PV module temperatures and yield forecasts. We found that ignoring sky temperature in thermal models can introduce up to ±0.5% uncertainty in annual yield predictions.
Expand what's possible in PV system modelling with high-fidelity, physics-based simulations.