Electric Power ›› 2022, Vol. 55 ›› Issue (11): 175-183.DOI: 10.11930/j.issn.1004-9649.202206091

• New Energy • Previous Articles     Next Articles

Available Capacity Evaluation Method of Electric Vehicle Charging Stations Based on Multi-parametric Programming

CAI Haiqing1,2,3, DAI Wei4, ZHAO Jingyi4, WANG Cheng4, ZHANG Zhijie4, LI Shuyong1,2,5   

  1. 1. State Key Laboratory of HVDC, Electric Power Research Institute, China Southern Power Grid, Guangzhou 510663, China;
    2. National Energy Power Grid Technology R & D Centre, Guangzhou 510663, China;
    3. Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System, Guangzhou 510663, China;
    4. School of Electrical Engineering, Guangxi University, Nanning 530006, China;
    5. CSG Key Laboratory for Power System Simulation, Guangzhou 510663, China
  • Received:2022-06-22 Revised:2022-10-09 Published:2022-11-29
  • Supported by:
    This work is supported by the State Key Laboratory of HVDC (No.SKLHVDC-2021-KF-03).

Abstract: To precisely evaluate the bearing capacity of distribution networks for electric vehicles (EVs) and thus ensure the secure operation of distribution networks, this paper proposes the definition of the available capacity (AC) of EV charging stations (EVCSs) and its evaluation method on the basis of the multi-parametric programming theory. The proposed method can efficiently and accurately visualize the AC boundaries of EVCSs with full consideration of the implicit coupling effects among multiple EVCSs and assists in the decision-making of distribution network scheduling. Firstly, according to the economic scheduling model of distribution networks and Karush-Kuhn-Tucker (KKT) conditions, the equivalent constraint sets of AC are formulated to represent the feasible space of AC and provide accurate boundary information for the scheduling. Next, the piecewise operational costs for different AC sub-space are derived to reflect the impact of charging power on the economic operation of distribution networks. Finally, simulations on the modified IEEE-33 bus system demonstrate the accuracy and effectiveness of the proposed evaluation model.

Key words: electric vehicles, distribution network, available capacity evaluation, multi-parametric programming, safe operation, scheduling