Optimal Scheduling of Vehicle-network Interaction Based on Interval Stackelberg Game of Virtual Power Plant

Authors

Weiliang Liu, Automation Department of North China Electric Power University, Baoding 071003, China; Baoding Key Laboratory for Condition Detection and Optimal Regulation of Comprehensive Energy System, Baoding 071003, ChinaFollow
Qianwen Yan, Automation Department of North China Electric Power University, Baoding 071003, China
Qiliang Zhang, Automation Department of North China Electric Power University, Baoding 071003, China; Baoding Key Laboratory for Condition Detection and Optimal Regulation of Comprehensive Energy System, Baoding 071003, ChinaFollow
Shuai Liu, Automation Department of North China Electric Power University, Baoding 071003, China; Baoding Key Laboratory for Condition Detection and Optimal Regulation of Comprehensive Energy System, Baoding 071003, China
Changliang Liu, Automation Department of North China Electric Power University, Baoding 071003, China; Baoding Key Laboratory for Condition Detection and Optimal Regulation of Comprehensive Energy System, Baoding 071003, China
Jiayao Kang, National Energy Group New Energy Technology Research Institute Co., Ltd., Beijing 102209, China
Xin Wang, National Energy Group New Energy Technology Research Institute Co., Ltd., Beijing 102209, China

Abstract

Abstract: To better exploit the regulation potential of electric vehicles (EVs), resolve the conflicts of interest among the stakeholders in vehicle-to-grid (V2G) interactions, and overcome the uncertainty of distributed energy sources and load, this paper proposes a two-level optimization scheduling model for V2G interactions based on the interval Stackelberg game of a virtual power plant (VPP). The VPP aggregator is considered as the upper level, and the EV users as the lower level. The upper level model uses interval numbers to describe the uncertainty of sources and loads, with the aim of minimizing the operating cost of the VPP aggregator, updating the electricity price information and transmitting it to the lower level model. The lower level model aims to maximize user satisfaction and minimize costs by solving the charging and discharging behavior of EV users and returning the results to the upper level model. The improved particle swarm optimization algorithm with integrated interval possibility degree is used to obtain the optimal scheduling results of the Stackelberg game. Simulation results demonstrate that the proposed model can effectively shave peak and fill the valley, coordinate the bilateral interests of the aggregator and EV users, and has good robustness.

Recommended Citation

Liu, Weiliang; Yan, Qianwen; Zhang, Qiliang; Liu, Shuai; Liu, Changliang; Kang, Jiayao; and Wang, Xin (2024) "Optimal Scheduling of Vehicle-network Interaction Based on Interval Stackelberg Game of Virtual Power Plant," Journal of System Simulation: Vol. 36: Iss. 7, Article 5.
DOI: 10.16182/j.issn1004731x.joss.23-0503
Available at: https://dc-china-simulation.researchcommons.org/journal/vol36/iss7/5

First Page

1559

Last Page

1572

CLC

TP391.9

Recommended Citation

Liu Weiliang, Yan Qianwen, Zhang Qiliang, et al. Optimal Scheduling of Vehicle-network Interaction Based on Interval Stackelberg Game of Virtual Power Plant[J]. Journal of System Simulation, 2024, 36(7): 1559-1572.

Corresponding Author

Zhang Qiliang

DOI

10.16182/j.issn1004731x.joss.23-0503