研究目的
To reliably and accurately extract parameters of photovoltaic (PV) models using an improved moths-flames optimization (IMFO) method.
研究成果
The proposed IMFO method demonstrates superior performance in accurately and reliably extracting parameters of different PV models, achieving a promising balance between global exploration and local exploitation. It outperforms eight well-established algorithms in terms of accuracy, reliability, and convergence speed.
研究不足
The study focuses on parameter extraction for specific PV models (SDM, DDM, PMM) and may not generalize to all types of photovoltaic systems. The performance of IMFO is compared against a select group of algorithms, and its effectiveness may vary with different optimization problems.
1：Experimental Design and Method Selection:
The IMFO method is proposed for parameter extraction of PV models, incorporating a double flames generation (DFG) strategy and two different update strategies for moths.
2：Sample Selection and Data Sources:
The study uses measured current and voltage values from a commercial silicon solar cell and a Photowatt-PWP201 PV module.
3：List of Experimental Equipment and Materials:
The study involves photovoltaic models (SDM, DDM, PMM) and heuristic optimization algorithms for comparison.
4：Experimental Procedures and Operational Workflow:
The IMFO algorithm is applied to extract parameters of the PV models, with comparisons made against eight well-established algorithms.
5：Data Analysis Methods:
The root mean square error (RMSE) is used as the objective function to evaluate the accuracy of the extracted parameters.
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