Journal of Jilin University (Information Science Edition) ›› 2022, Vol. 40 ›› Issue (3): 379-386.

Previous Articles     Next Articles

MPPT Research Based on LGWO and Perturbation Observation Compound Algorithm

ZHANG Tiesheng1 , ZHANG Fengwu2 , ZHANG Mingyi2   

  1. 1. School of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China; 2. Oil Production Engineering Research Institute, Daqing Oilfield Company Limited, Daqing163453, China
  • Received:2021-10-15 Online:2022-07-14 Published:2022-07-14

Abstract: In order to solve the problem of multi-peak output power of photovoltaic power generation generated by local shadows, a compound algorithm combining gray wolf optimization algorithm and disturbance observation method is proposed. Levy flight module and greedy strategy are embedded into the grey wolf algorithm to achieve optimization. The composite algorithm makes use of the accuracy of gray wolf optimization algorithm and the rapidity of disturbance observation method to accurately track the maximum power point of photovoltaic power generation under multiple peak values. The simulation results are verified by Simulink experimental platform. The Simulation results show that the proposed algorithm has better tracking performance than the traditional gray Wolf algorithm in accuracy and rapidity. 

Key words: Levy flight module, gray wolf optimization algorithm, perturbation and observation method, maximum power point tracking; local shadow

CLC Number: 

  • TM914. 4