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| Lion Swarm Optimization Based on Chaotic Search Strategy and Application in Parameters Identification of Photovoltaic Cell Models |
| WU Zhong-qiang,XIE Zong-kui,LIU Chong-yang,WANG Guo-yong |
| Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract Up to now, many intelligent algorithms have been used in parameter identification of photovoltaic cell model, but most of them are prone to local optimum and the convergence speed is slow. Lion swarm optimization is a novel intelligent algorithm proposed in recent years, and it also has the problems mentioned above. An improved lion swarm algorithm based on chaotic search strategy (CLSO) was proposed. By introducing chaotic sequence, adaptive parameter and tent chaotic search strategy, the deficiency of the lion swarm optimization was remedied. Firstly,the algorithm was applied to the parameter identification of single-diode model and double-diode model of photovoltaic cells, compared with the results of other five algorithms, which proved the effectiveness and superiority of this algorithm in the parameter identification of photovoltaic cells. Besides, experiments were carried out under different irradiance and different weather types, exploring the influence with changing external environment on model parameters, which further verify the effectiveness and practicability of the algorithm.
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Received: 28 April 2019
Published: 20 April 2021
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2021, Vol. 42 
