An Improved Differential Evolution to Extract Photovoltaic Cell Parameters
Zuowen Liao, Qiong Gu, Shuijia Li, Zhenzhen Hu, Bin Ning
Abstract
Parameter extraction of photovoltaic (PV) models plays a vital role in simulation, evaluation and control of PV systems. It requires to identify the parameters of different PV models quickly and accurately. In this paper, an improved differential evolution by reusing the past individual vectors and adaptive mutation strategy is proposed to extract PV parameters. In the proposed method, the successful difference vectors from previous generations are introduced to produce the offspring in the next generations to improve the performance of differential evolution. In addition, to obtain a nice result, an adaptive mutation strategy is considered to establish a good balance of exploration and exploitation. The proposed method is applied to identify the parameters of different PV models, such as single diode, double diode, and PV models. Comparison results demonstrate that the proposed method obtains the competitive performance on accuracy, reliability and convergence when compared with other state-of-the-art methods.