Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2023 , Vol. 57 >Issue 1: 1 - 9

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2021.499

New Type Power System and the Integrated Energy

Management and Optimal Control Algorithm for Electric Vehicle Charging in Random Environment

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  • 1. College of Electronic and Information Engineering, Guangxi Normal University, Guilin 541004, Guangxi Zhuang Autonomous Region, China
    2. Power Research Institute of Guangxi Power Grid Co., Ltd., Nanning 530000, China

Received date: 2021-12-07

  Revised date: 2022-02-12

  Online published: 2022-10-31

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Abstract

With the increasing scale of electric vehicles (EVs), the adaptive management of its charging behavior becomes an urgent problem to be solved. From the point of view of charging service provider, an online management algorithm for EV charging is proposed based on the Lyapunov optimization theory under the random environment in this paper, considering renewable sources energy, storage equipment, time-varying electricity price, and the tolerable delay of EV, with an aim of maximizing the benefits of charging service providers (i.e., minimizing the cost of electricity purchased). The performance of the proposed algorithm is analyzed to verify that it can achieve near-optimal optimization results without any a priori statistical information about the system inputs (renewable energy generation, charging demand, and time-varying electricity price). The simulation results show that the proposed algorithm can effectively reduce the economic cost by 27.3% compared with the benchmark algorithm.

Key words： electric vehicles (EVs); charging schedule; smart grid; random environment; renewable energy source

Cite this article

LIU Didi, YANG Yifei, YANG Yuhui, ZOU Yanli, WANG Xiaohua, LI Xin . Management and Optimal Control Algorithm for Electric Vehicle Charging in Random Environment[J]. Journal of Shanghai Jiaotong University, 2023 , 57(1) : 1 -9 . DOI: 10.16183/j.cnki.jsjtu.2021.499

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