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Parameter extraction of solar cell models using improved shuffled complex evolution algorithm

Author:
Gao, Xiankun, Cui, Yan, Hu, Jianjun, Xu, Guangyin, Wang, Zhenfeng, Qu, Jianhua, Wang, Heng
Source:
Energy conversion and management 2018 v.157 pp. 460-479
ISSN:
0196-8904
Subject:
algorithms, data collection, diodes, energy, models, probability, roughness, solar cells, solar collectors
Abstract:
Fast and accurate parameter extraction of solar cell models is always desired for simulation, evaluation and maximum energy harvesting of PV systems. This paper proposes an improved shuffled complex evolution (ISCE) algorithm for parameter extraction of different PV models, including single diode model, double diode model and single diode solar module model. The novelty of proposed ISCE algorithm lies primary in the improved competitive complex evolution strategy, where three amendments are proposed to overcome the shortcomings of original SCE algorithm. (1) The expansion step and outside contraction step are inserted into to improve the probability of producing better solution. (2) The reflecting-absorbing bound- handling method is employed to enhance the chance of global search and avoid being trapped in local minima. (3) The main diagonal of simplex is adopted to overcome local roughness and drive the global search in an efficient manner. In order to test the parameter extraction performance of proposed ISCE and compare it with some state-of-the-art algorithms, the standard datasets and practical measured datasets of one solar cell and three solar modules are selected for parameter extraction of different PV models. Comparison results indicate that the proposed ISCE algorithm always exhibits the highest computational efficiency to get the most accurate parameter values among all compared algorithms. More importantly, the proposed ISCE algorithm generally promises better convergence speed and robustness than the best reported algorithms. Due to these superiorities, the proposed ISCE algorithm is quite promising and envisaged to be an accurate, efficient and reliable alternative for solving the parameter extraction problem of solar cell models.
Agid:
6018814