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Exponential slime mould algorithm based spatial arrays optimization of hybrid wind-wave-PV systems for power enhancement

Author

Listed:
  • Li, Miwei
  • Yang, Bo
  • Duan, Jinhang
  • Shu, Hongchun
  • Wang, Yutong
  • Yang, Zhaowei
  • Jiang, Lin
  • Chen, Yixuan
  • Sang, Yiyan

Abstract

Renewable clean energy sources, such as wind, solar, and wave energy, are currently gaining prominence and are being extensively researched. Given the escalating significance of clean energy, hybrid systems have gradually become an effective solution to address energy and environmental issues. In order to maximize the advantages of wind, wave energy, and photovoltaic (PV), this paper proposes a hybrid wind-wave-PV system (HWWPS) by combining wind turbines, PV panels, and wave energy converter (WEC) to achieve higher energy production and efficiency. To further enhance power output, this paper focuses on the influence of system spatial array optimization on power output and adopts an algorithm to establish a strategic layout. Through the integration of the chaos algorithm, exponential asynchronous factor, and the sine-cosine mechanism, the original slime mould algorithm (SMA) algorithm is enhanced to the exponential slime mould algorithm (ESMA), which has better optimization capability and is particularly suitable for determining the optimal power configuration. Simulations are conducted on hybrid systems consisting of three, seven, and thirteen buoys, respectively, which compare the ESMA are compared with the other six algorithms. The results verify the advantages of ESMA over the other algorithms, and demonstrates the superiority becomes more prominent as the system size increases.

Suggested Citation

  • Li, Miwei & Yang, Bo & Duan, Jinhang & Shu, Hongchun & Wang, Yutong & Yang, Zhaowei & Jiang, Lin & Chen, Yixuan & Sang, Yiyan, 2024. "Exponential slime mould algorithm based spatial arrays optimization of hybrid wind-wave-PV systems for power enhancement," Applied Energy, Elsevier, vol. 373(C).
    • Handle: RePEc:eee:appene:v:373:y:2024:i:c:s0306261924012881
    DOI: 10.1016/j.apenergy.2024.123905
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