研究目的
To develop a novel optimization method for parameter extraction of industrial solar cells using a triple diode model and Flower Pollination Optimization Algorithm (FPOA) to accurately simulate and match the I-V characteristics of large silicon solar cells.
研究成果
The triple diode model combined with FPOA provides a superior fit for industrial solar cells, accurately capturing the I-V characteristics that single and double diode models cannot. FPOA's efficiency in parameter extraction is demonstrated through lower MAE values compared to DE and PSO methods.
研究不足
The study is limited to simulation-based validation and does not include physical experimentation. The triple diode model, while more accurate, shows slightly higher MAE values compared to the double diode model in some cases.
1：Experimental Design and Method Selection:
The study utilizes the triple diode model for creating a lumped parameter equivalent circuit for solar PV models. FPOA is employed for parameter extraction, comparing its performance with DE and PSO methods.
2：Sample Selection and Data Sources:
Nine industrial solar cell samples are used for testing under different environmental conditions.
3：List of Experimental Equipment and Materials:
Simulation is carried out using Matlab 2017 on an Intel i7 Processor with 4-GB RAM.
4：Experimental Procedures and Operational Workflow:
The FPOA algorithm is applied to extract parameters from the triple diode model, with performance metrics like MAE and IAE used for comparison.
5：Data Analysis Methods:
The estimated I-V curves are matched with measured curves, and MAE values are calculated to assess accuracy.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
