Charging and Discharging Scheduling Mechanism of Electric Vehicles in Park Based on User Credit Index

doi:10.16183/j.cnki.jsjtu.2023.196

Abstract

Abstract:

The default behavior of electric vehicle (EV) users to end charging in advance is easy to cause default losses to load aggregators and users themselves. Therefore,it is crucial to dispatch charging behavior rationally considering default behavior. This paper quantifies EV user credit based on Wu’s three-dimensional credit theory, and revises EV charging and discharging plan in the dimensions of discharge depth and charging priority. In addition, it establishes a multi-objective optimization model considering the load fluctuation of regional distribution network and the user cost. Using a park as an example for simulation, it compares and analyzes the effects of different user default rates and EV permeability on the proposed multi-dimensional modified charging and discharging strategy. The results show that the charging and discharging scheduling mechanism based on the user credit index has advantages in calming the load fluctuation of the distribution network in the park and improving the charging experience of users. Compared with the orderly charging and discharging strategy which does not consider the charging and discharging execution of users, the proposed mechanism can better adapt to the scenario of increasing penetration rate of EV and expanding default scale.

Key words: electric vehicle (EV), orderly charging and discharging, user credit index, charging priority, three dimensional credit theory

CLC Number:

TM732
U491.8

SUN Xin, JIANG Hailin, XIE Jingdong, WANG Simin, WANG Sen. Charging and Discharging Scheduling Mechanism of Electric Vehicles in Park Based on User Credit Index[J]. Journal of Shanghai Jiao Tong University, 2025, 59(2): 200-207.

Figures/Tables 10

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参数	场景1	场景2	场景3
负荷均方差/kW	155.78	83.22	83.41
充电费用/元	1170.20	1047.79	1064.91
放电收入/元	0	37.25	35.15
总费用/元	1170.20	1010.54	1029.76
应充电量/(kW·h)	1332.20	1332.20	1332.20
未充电量/(kW·h)	0	243.04	111.53

违约率/%	充电满足率/%
违约率/%	场景2	场景3
5	96.33	97.41
20	81.76	91.63
30	75.11	89.68

用户	充电满足率/%	预计放电收入/元	实际放电收入/元
违约	40.84	11.18	4.37
未违约	100	30.78	30.78