Mayfly Optimization Algorithm–Based PV Cell Triple-Diode Model Parameter Identification - Chen, Nuo; Bi, Wei; Xu, Gentang; Wu, Zongshi; Wu, Mingwei; Luo, Ke (Frontiers in Energy Research, 2022)
The maximum power output, control optimization analysis of photovoltaic (PV) systems are based on accurate and reliable PV cell parameter identification. However, its difficult problems such as high nonlinearity and multimodality have become obstacles to the traditional optimization methods to obtain accurate and efficient results. This study uses a new intelligent optimization algorithm called mayfly algorithm (MA) to efficiently identify the triple diode model (TDM) of PV cells, and uses the minimum root mean square error (RMSE) as the evaluation index to verify the effectiveness of the algorithm. Besides, by continuously adjusting the parameters, population number, and iteration times of MA algorithm to better balance the relationship between global development and local optimization, we can obtain more efficient and better optimization results. The research case shows that MA algorithm is superior to other meta-heuristic algorithms in the accuracy and stability of PV cell parameter identification. For example, the minimum standard deviation (SD) of RMSE obtained by MA algorithm is 1305 times smaller than another algorithm.