Game Strategy for Cluster Development of User-side Distributed Photovoltaic Resources

被引：0
|
作者：
Sun L. [1 ]
Li H. [1 ]
Jia Q. [1 ]
Zhang G. [2 ]
Wang M. [2 ]
机构：
[1] Key Laboratory of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao
[2] Qinhuangdao Power Supply Company of State Grid Jibei Electric Power Company Limited, Qinhuangdao
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2023年 / 47卷 / 10期
基金：
中国国家自然科学基金;
关键词：
bi-level optimization; cluster development; distributed photovoltaic generation; photovoltaic site lease; Stackelberg game;
D O I：
10.7500/AEPS20220707001
中图分类号：
学科分类号：
摘要：
Currently, distributed photovoltaics (PVs) on the user side are showing a low-end quantitative expansion trend of decentralized construction and disorderly access, which is difficult to meet the needs of large-scale deep development and sustainable development of distributed PV power generation under the low-carbon transformation of the power grid. This paper explores the integrated development and operation mode of distributed PV clusters, and proposes a game strategy for cluster development of users-side distributed PV resource. Firstly, a distributed PV cluster development and operation model with cluster operators as the main body is constructed. Secondly, a prediction method for user PV development behavior is proposed for two development modes: self-built PV or rented site. Then, the game relationship between cluster operators and users in the allocation of PV development resources is revealed, and a two-layer optimization model of distributed PV resource Stackelbery game is constructed. Finally, the simulation results validate the effectiveness of the proposed method in guiding the orderly and rational development and rational and efficient configuration of user-side distributed PV. © 2023 Automation of Electric Power Systems Press. All rights reserved.
引用
收藏
页码：26 / 37
页数：11
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共 26 条
  • [1] WANG P., Estimation of photovoltaic power generation potential in 2020 and 2030 using land resource changes：an empirical study from China［J］, Energy, 219, (2021)
  • [2] The role of residential rooftop photovoltaic in long-term energy and climate scenarios［J］, Applied Energy, 279, (2020)
  • [3] SHENG Wanxing, WU Ming, JI Yu, Et al., Key techniques and engineering practice of distributed renewable generation clusters integration［J］, Proceedings of the CSEE, 39, 8, pp. 2175-2186, (2019)
  • [4] WANG Caixia, SHI Zhiyong, LIANG Zhifeng, Et al., Key technologies and prospects of demand-side resource utilization for power systems dominated by renewable energy［J］, Automation of Electric Power Systems, 45, 16, pp. 37-48, (2021)
  • [5] LIU Wenxia, YAO Qi, WANG Yuehan, Et al., Generation planning model of stackelberg game between supply and demand based on stepped demand response mechanism［J］, Automation of Electric Power Systems, 46, 20, pp. 54-63, (2022)
  • [6] YANG L A, GUO Q L, Et al., Optimal distributed generation planning in active distribution networks considering integration of energy storage［J］, Applied Energy, 210, pp. 1073-1081, (2018)
  • [7] SUN Lingling, JIA Qingquan, ZHANG Gong, Et al., Optimal configuration method of micro-grid considering operating and exchanging［J］, Proceedings of the CSEE, 40, 7, pp. 2221-2233, (2020)
  • [8] FANG Yichen, ZHANG Shenxi, CHENG Haozhong, Et al., Robust optimization of distributed photovoltaic hosting capacity of active distribution network with soft open point［J］, Automation of Electric Power Systems, 45, 7, pp. 8-17, (2021)
  • [9] ZENG Ming, SHU Tong, LI Yuanfei, Et al., Optimal allocation and pricing decision making method for DG considering benefits of different shareholders in electricity market environment［J］, Electric Power Construction, 38, 10, pp. 115-122, (2017)
  • [10] LI Zhuyun, Xia LEI, QIU Shaoyin, Et al., Coordinated planning of active distribution network considering “source-grid-load” benefits ［J］, Power System Technology, 41, 2, pp. 378-387, (2017)
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