Modified Grasshopper Optimization Algorithm and Applications in Optimal Dispatch of Electric Vehicle Battery Swapping Station

doi:10.12068/j.issn.1005-3026.2020.02.004

Abstract

Abstract: The dispatch of electric vehicle battery swapping station is usually optimized by swarm intelligence algorithms. However， the existing algorithms are easily trapped in local optimum and premature convergence. Thus， an improved grasshopper optimization algorithm(IGOA)is proposed to achieve optimal dispatch. In the IGOA， the boundary bounce strategy is adopted to improve the efficiency; the sine/cosine algorithm is introduced to enhance the global searching ability; the Lévy flight is applied to perturb the particles randomly to keep the algorithm from being trapped in local optimum; the nonlinear operation is used to accelerate the convergence rate at the later stage of the algorithm. The simulation results show that the IGOA outperforms GOA and several other swarm intelligence algorithms as to the optimal dispatch of electric vehicle battery swapping station.

Key words: electric vehicle, battery swapping station, optimal dispatch, swarm intelligence, grasshopper optimization algorithm

CLC Number:

TP319

WANG Sheng-sheng， ZHANG Wei， DONG Ru-yi， LI Wen-hui. Modified Grasshopper Optimization Algorithm and Applications in Optimal Dispatch of Electric Vehicle Battery Swapping Station[J]. Journal of Northeastern University Natural Science, 2020, 41(2): 170-175.

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