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The Scientific World Journal
Volume 2014, Article ID 859239, 12 pages
Research Article

Parameters Identification for Photovoltaic Module Based on an Improved Artificial Fish Swarm Algorithm

College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China

Received 28 April 2014; Revised 20 July 2014; Accepted 6 August 2014; Published 27 August 2014

Academic Editor: Shih-Wei Lin

Copyright © 2014 Wei Han et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A precise mathematical model plays a pivotal role in the simulation, evaluation, and optimization of photovoltaic (PV) power systems. Different from the traditional linear model, the model of PV module has the features of nonlinearity and multiparameters. Since conventional methods are incapable of identifying the parameters of PV module, an excellent optimization algorithm is required. Artificial fish swarm algorithm (AFSA), originally inspired by the simulation of collective behavior of real fish swarms, is proposed to fast and accurately extract the parameters of PV module. In addition to the regular operation, a mutation operator (MO) is designed to enhance the searching performance of the algorithm. The feasibility of the proposed method is demonstrated by various parameters of PV module under different environmental conditions, and the testing results are compared with other studied methods in terms of final solutions and computational time. The simulation results show that the proposed method is capable of obtaining higher parameters identification precision.