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A flexible power point tracking algorithm based on adaptive lion swarm optimization for photovoltaic system

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Abstract

In PV power generation systems, flexible power point tracking control needs to be introduced to regulate the output power on the PV side for meeting the grid connection requirements. However, traditional FPPT control methods tend to cause certain oscillations in the system. This paper proposes an FPPT method based on the adaptive lion swarm optimization algorithm (ALSO). First, an ALSO algorithm is proposed, which adds adaptive scaling parameters to the lion swarm optimization algorithm, so that the number of adult lions can be adjusted adaptively with increasing iterations to coordinate the local exploitation and global search abilities of the algorithm. Then the ALSO is used to selectively optimize the operation of different intervals so as to achieve the FPPT control on the left or right side of the maximum power point. The test experiments for the ALSO algorithm show that the ALSO algorithm has strong local exploitation and global search abilities, which is better than the compared algorithms. Through the simulations on the PV grid-connected system, the validity and superiority of the ALSO-based method over the traditional FPPT algorithm in terms of dynamic and steady-state performance are verified under different operating conditions.

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Data availability

The data used to support the findings of this study are available from the corresponding author upon request.

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Acknowledgments

This project was supported by the Natural Science Foundation of Hebei Province under Grant F2020203014.

Funding

Funding was provided by Natural Science Foundation of Hebei Province, F2020203014, Zhongqiang Wu.

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Authors and Affiliations

  1. Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, 066004, China

    Zongkui Xie & Zhongqiang Wu

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  1. Zongkui Xie
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  2. Zhongqiang Wu
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Correspondence to Zhongqiang Wu.

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Xie, Z., Wu, Z. A flexible power point tracking algorithm based on adaptive lion swarm optimization for photovoltaic system. Soft Comput 27, 4953–4973 (2023). https://doi.org/10.1007/s00500-022-07568-w

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