Journal of Power Electronics

The Korean Institute of Power Electronics (전력전자학회)
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SMGSA algorithm-based MPPT control strategy

  • Yiping Xiao (School of Electrical and Electronic Engineering, Hubei University of Technology) ;
  • Yunfeng Zhao (School of Electrical and Electronic Engineering, Hubei University of Technology) ;
  • Zongtao Shen (School of Electrical and Electronic Engineering, Hubei University of Technology) ;
  • Hongjian Jiao (School of Electrical and Electronic Engineering, Hubei University of Technology)
  • Received : 2023.04.24
  • Accepted : 2023.12.21
  • Published : 2024.05.20
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Abstract

Under partial shading conditions (PSCs), photovoltaic arrays exhibit power-voltage curves with multiple peaks. This phenomenon complicates the task of traditional maximum power point tracking (MPPT) algorithms, since they often converge to local maximum power points. To tackle this challenge, a novel MPPT control strategy, termed the slime mold golden sine algorithm (SMGSA), was introduced in this paper. This strategy adeptly identifies and tracks the global maximum power point. The efficacy of the SMGSA algorithm was assessed through six test functions from IEEE CEC 2020. A comparative analysis underscored its superior performance in both convergence speed and accuracy. A simulation model for MPPT was developed in MATLAB/Simulink. Within this model, various algorithms such as particle swarm optimization (PSO), tuna swarm optimization (TSO), slime mold algorithm (SMA), and SMGSA were examined. Comparative simulations revealed that the SMGSA-based MPPT strategy showcased expedited convergence speed and heightened accuracy under scenarios of uniform irradiance intensity, partial static shading, and dynamic shading. Consequently, the implementation of an SMGSA-based MPPT system can notably enhance the power generation efficiency of photovoltaic arrays under PSCs.

Keywords

Acknowledgement

Natural Science Foundation of Hubei Province (2023AFB992).

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