An improved bat algorithm for more efficient and faster maximum power point tracking for a photovoltaic system under partial shading conditions

Chih Yu Liao, Ramadhani Kurniawan Subroto, Ibrahim Saiful Millah, Kuo Lung Lian, Wei Tzer Huang

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

Solar modules under partial shading (PS) conditions will result in power and voltage characteristic curves (P-VCC) having multiple peaks. If the maximum power point cannot be obtained, the output power of the solar modules will be greatly reduced. Hence, there have been various maximum power point tracking (MPPT) control methods developed to address this problem. One alternative is to employ the meta-heuristic approach (MHA) to track the global maximum power point (GMPP). Recently, a new MHA called Bat Algorithm (BA) has performed well in the MPPT. Nevertheless, BA may fail to track the GMPP when there are some local maximum power points (LMPPs) close to the GMPP. Also, the tracking time needs to be further reduced to accommodate rapidly changing irradiance. Therefore, a combination of BA with the abandonment mechanism of Cuckoo Search (CS) is proposed to improve the tracking performance of the BA. Both simulation and experimental results show that the proposed method, as compared to BA, yields better accuracy and an improvement of convergence speed of about 35% for various P-VCCs can be achieved. Moreover, the MBA has also been tested against some of the state-of-the-art MPPT algorithms such as Particle Swarm Optimization and Grey Wolf Optimization (GWO), and the results showed the superiority of the proposed method.

原文English
文章編號9090139
頁(從 - 到)96378-96390
頁數13
期刊IEEE Access
8
DOIs
出版狀態Published - 2020

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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