Two-stage robust optimization model of multiple prosumers based on centralized-decentralized trading mechanism

被引：0
|
作者：
Wang S. [1 ]
Sun G. [1 ]
Wu C. [1 ,2 ]
Hu G. [2 ]
Zhou Y. [1 ]
Chen S. [1 ]
Wei Z. [1 ]
机构：
[1] College of Energy and Electrical Engineering, Hohai University, Nanjing
[2] Economic and Technology Research Institute of State Grid Jiangsu Electric Power Co., Ltd., Nanjing
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2022年 / 42卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Centralized-decentralized trading; Nash negotiation; P2P trading; Prosumer; Two-stage robust optimization;
D O I：
10.16081/j.epae.202202008
中图分类号：
学科分类号：
摘要：
Aiming at the uncertainty in the process of prosumers participating in electricity market trading, a two-stage robust centralized-decentralized trading model of multiple prosumers is proposed. Considering that P2P(Peer to Peer) decentralized trading can be carried out between prosumers, a centralized-decentra-lized market trading model of multiple prosumers is built. Considering the impact of uncertainty of photovoltaic output on trading strategy, a two-stage robust market trading model of multiple prosumers is built. Nash negotiation method is adopted to realize fair distribution of cooperative surplus among multiple prosumers. Simulation examples verify the effectiveness of the proposed model. © 2022, Electric Power Automation Equipment Press. All right reserved.
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页码：175 / 182
页数：7
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  • [1] ZHU Xiping, FU Qian, WEN Hong, Et al., Optimal allocation model of multi-energy entity energy storage from perspective of blockchain, Electric Power Automation Equipment, 40, 8, pp. 47-56, (2020)
  • [2] RATHNAYAKA A J D, POTDAR V M, DILLON T S, Et al., A methodology to find influential prosumers in prosumer community groups, IEEE Transactions on Industrial Infor-matics, 10, 1, pp. 706-713, (2014)
  • [3] TEOTIA F, MATHURIA P, BHAKAR R., Peer-to-peer local electricity market platform pricing strategies for prosumers, IET Generation, Transmission & Distribution, 14, 20, pp. 4388-4397, (2020)
  • [4] YANG Zhao, AI Xin, Distributed optimal scheduling for integ-rated energy building clusters considering energy sharing, Power System Technology, 44, 10, pp. 3769-3778, (2020)
  • [5] JIANG T, LI Z N, JIN X L, Et al., Flexible operation of active distribution network using integrated smart buildings with heating, ventilation and air-conditioning systems, Ap-plied Energy, 226, pp. 181-196, (2018)
  • [6] WANG F, ZHOU L D, REN H, Et al., Multi-objective opti-mization model of source-load-storage synergetic dispatch for a building energy management system based on TOU price demand response, IEEE Transactions on Industry Applica-tions, 54, 2, pp. 1017-1028, (2018)
  • [7] FENG Changsen, SHEN Jiajing, ZHAO Chongjuan, Et al., Coope-rative game-based coordinated operation strategy of smart energy community, Electric Power Automation Equipment, 41, 4, pp. 85-93, (2021)
  • [8] PAUDEL A, CHAUDHARI K, LONG C, Et al., Peer-to-peer energy trading in a prosumer-based community microgrid: a game-theoretic model, IEEE Transactions on Industrial Elec-tronics, 66, 8, pp. 6087-6097, (2019)
  • [9] CHEN K X, LIN J, SONG Y H., Trading strategy optimization for a prosumer in continuous double auction-based peer-to-peer market: a prediction-integration model, Applied Energy, 242, pp. 1121-1133, (2019)
  • [10] CHEN Xiupeng, LI Gengyin, ZHOU Ming, Et al., Distributed optimal scheduling for prosumers in distribution network considering uncertainty of renewable sources and P2P trading, Power System Technology, 44, 9, pp. 3331-3340, (2020)
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