Main Factors Affecting the Accuracy of Bifacial Solar Panel Simulations
Bifacial solar panels, which can capture sunlight from both sides, require accurate simulation models to predict their power generation. Several key factors influence the accuracy of these simulations:
1. Modeling Techniques
- Ray Tracing vs. View Factor Models:
- Ray Tracing: Techniques like bifacial_radiance provide high accuracy but are computationally intensive, making them less suitable for extensive analyses.
- View Factor Models: Tools like pvfactors offer faster simulations but may limit detailed analysis of power variations between modules.
2. Environmental Factors
- Irradiance Nonuniformity: The uneven distribution of rear-side irradiance can lead to mismatch losses, affecting overall efficiency.
- Ground Albedo: Variations in ground reflectivity significantly impact the bifacial gain, which is the additional energy generated compared to monofacial panels.
- Snow Coverage: Snow can drastically reduce power output during winter months, requiring adjustments in models to improve accuracy.
3. System Parameters
- Mounting and Installation: Parameters such as tilt angle, clearance height, and system layout influence both front and rear irradiance.
- Panel Characteristics: The bifaciality coefficient and cell temperature models (e.g., Homer Pro) can impact simulation accuracy.
4. Data Sources
- Local vs. Satellite-Derived Irradiance: Local data tends to improve model accuracy compared to satellite-derived data, which may have higher errors.
5. Computational Efficiency
- Parallel Computing and Optimization: Techniques to reduce computational time are essential for comprehensive annual simulations.
Original article by NenPower, If reposted, please credit the source: https://nenpower.com/blog/what-are-the-main-factors-affecting-the-accuracy-of-bifacial-solar-panel-simulations/
