Load Peak Shaving Operation Management and Control Strategy of AC/DC Hybrid Distribution Network Based on Two-stage Robust Game Model

被引:0
|
作者
Zhong L. [1 ]
Gao H. [1 ]
Yang Y. [2 ]
Liu Y. [1 ]
Liu J. [1 ]
机构
[1] College of Electrical Engineering and Information Technology, Sichuan University, Sichuan Province, Chengdu
[2] Institute of Electrical Engineering, Chinese Academy of Sciences, Haidian District, Beijing
基金
中国国家自然科学基金;
关键词
AC/DC hybrid distribution network; electric vehicle(EV); interactive game; peak shaving operation control; two-stage robust optimization;
D O I
10.13334/j.0258-8013.pcsee.210628
中图分类号
学科分类号
摘要
AC/DC hybrid distribution network has been widely adopted for its high flexibility and control ability. In addition, the large-scale access of electric vehicles and air conditioners can increase the peak load of distribution network. This paper proposed a load peak operation control model for AC/DC hybrid distribution network based on two-stage robust game. Firstly, a master-slave game model among grid companies, the electric vehicle agents and energy storage operators was built. Then, a multi-objective two-stage robust optimization model for grid companies (leaders) with maximum profit and minimum peak-valley difference was established. Meanwhile, two profit optimization models for energy storage operators and electric vehicle agents (followers) were built respectively. The existence and uniqueness of the master-slave game equilibrium was proved. Secondly, the follower model was equivalent to the equilibrium constraint in the leader model by KKT condition. So, the two-layer master-slave game model was equivalent to a single-layer two-stage robust optimization model, which was solved by CCG algorithm. Finally, the simulation results show that load peak operation control strategy can achieve load peak shaving for AC/DC hybrid distribution network and interest balance among multi-stakeholders. © 2022 Chin.Soc.for Elec.Eng.
引用
收藏
页码:5550 / 5564
页数:14
相关论文
共 30 条
  • [1] LI Tie, LI Zhengwen, YANG Junyou, Coordination and optimal scheduling of multi-energy complementary system considering peak regulation initiative[J], Power System Technology, 44, 10, pp. 3622-3630, (2020)
  • [2] WANG Kaiyan, LUO Xianjue, JIA Rong, Short-term coordinated scheduling of wind-pumped-hydro-thermal power system with multi-energy complementarities[J], Power System Technology, 44, 10, pp. 3631-3640, (2020)
  • [3] ZHANG Yaoxiang, LIU Wenying, LI Xiao, Optimal control method of peak load regulation combined concentrating solar power and thermal power for power grid accessed with high proportion of renewable energy[J], Electric Power Automation Equipment, 41, 4, pp. 1-7, (2021)
  • [4] LI Ji, ZHANG Huiyuan, CHENG Jiehui, Et al., Coordinated and optimal scheduling of inter-regional interconnection system based on source and load status[J], Automation of Electric Power Systems, 44, 17, pp. 26-33, (2020)
  • [5] GUO Tong, LI Yonggang, XU Shanshan, Planning of flexibility retrofits of thermal power units considering multi-agent game[J], Transactions of China Electrotechnical Society, 35, 11, pp. 2448-2459, (2020)
  • [6] HUANG Chunyi, WANG Chengmin, XIE Ning, Distribution expansion planning based on strong coupling of operation and spot market[J], Proceedings of the CSEE, 39, 16, pp. 4716-4731, (2019)
  • [7] JIA Qiangang, CHEN Sijie, LI Yiyan, Learning automata based bidding strategy for power suppliers in incomplete information environment, Automation of Electric Power Systems, 45, 6, pp. 133-139, (2021)
  • [8] KUANG Yi, WANG Xiuli, WANG Jianxue, Virtual power plant energy sharing mechanism based on stackelberg game[J], Power System Technology, 44, 12, pp. 4556-4564, (2020)
  • [9] XIANG Enmin, GAO Hongjun, LIU Chang, Optimal decision of energy trading for community multi-energy operator based on game interaction with supply and demand sides[J], Proceedings of the CSEE, 41, 8, pp. 2744-2756, (2021)
  • [10] YANG Guoqing, FU Jing, WANG Deyi, Study on one-leader three-follower game dispatching of regional power system with wind-hydro-gas power[J], Power System Technology, 42, 2, pp. 495-502, (2018)