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Cooperative Evolutionary Game Strategy for Electricity Trading Stakeholders in Active Distribution Network under Consortium Blockchain Framework |
Ye Chang1,2, Miao Shihong1,2, Liu Hao3, Zhang Di1,2, Zhao Jian3 |
1. State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan 430074 China; 2. Hubei Electric Power Security and High Efficiency Key Laboratory School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan 430074 China; 3. State Grid Henan Electric Power Company Electric Power Research InstituteZhengzhou 450052 China |
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Abstract In the traditional electricity trading mode, centralized transaction data and regulatory agency will bring the issues such as low data security and regulatory trust crisis. The rise and development of blockchain technology provides new ideas and methods for solving these problems. Firstly, by analyzing behavior characteristics of electricity trading stakeholders (ETSs) in the active distribution network (ADN), a electricity market trading system is established under consortium blockchain framework. This system pre-authorizes each ETS as a semi-open local node. Through the dynamic selection of alliance node, distributed storage of transaction data can be realized without additional third-party regulatory agency. Then a detailed certification method for electricity trading in AND is proposed. Furthermore, a cooperative evolutionary game model of ETSs is established, and a multi-objective evolutionary algorithm based on decomposition is utilized to solve this model. The solution results can be used as a basis for generating smart contracts, and realize the decision-making optimization for electricity trading in ADN. Finally, the case study verify the proposed strategy.
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Received: 26 July 2019
Published: 24 April 2020
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[1] 曾博, 杨煦, 张建华. 考虑可再生能源跨区域消纳的主动配电网多目标优化调度[J]. 电工技术学报, 2016, 31(22): 148-158. Zeng Bo, Yang Xu, Zhang Jianhua.Multi-objective optimization for active distribution network schedu- ling considering renewable energy harvesting across regions[J]. Transactions of China Electrotechnical Society, 2016, 31(22): 148-158. [2] 赵波, 王财胜, 周金辉, 等. 主动配电网现状与未来发展[J]. 电力系统自动化, 2014, 38(18): 125-135. Zhao Bo, Wang Caisheng, Zhou Jinhui, et al.Present and future development trend of active distribution network[J]. Automation of Electric Power Systems, 2014, 38(18): 125-135. [3] 孙建军, 张世泽, 曾梦迪. 考虑分时电价的主动配电网柔性负荷多目标优化控制[J]. 电工技术学报, 2018, 33(2): 401-411. Sun Jianjun, Zhang Shize, Zeng Mengdi.Multi- objective optimal control for flexible load in active distribution network considering time-of-use tariff[J]. Transactions of China Electrotechnical Society, 2018, 33(2): 401-411. [4] 黄伟, 熊伟鹏, 华亮亮, 等. 基于动态调度优先级的主动配电网多目标优化调度[J]. 电工技术学报, 2018, 33(15): 3486-3498. Huang Wei, Xiong Weipeng, Hua Liangliang, et al.Multi-objective optimization dispatch of active distribution network based on dynamic schedule priority[J]. Transactions of China Electrotechnical Society, 2018, 33(15): 3486-3498. [5] Xiang Yue, Liu Junyong, Yang Wei, et al.Active energy management strategies for active distribution system[J]. Journal of Modern Power Systems and Clean Energy, 2015, 3(4): 533-543. [6] 乐健, 柳永妍, 叶曦, 等. 含高渗透率分布式电能资源的区域电网市场化运营模式[J]. 中国电机工程学报, 2016, 36(12): 3343-3353. Le Jian, Liu Yongyan, Ye Xi, et al.Market-oriented operation pattern of regional power network integration with high penetration level of distributed energy resources[J]. Proceedings of the CSEE, 2016, 36(12): 3343-3353. [7] 高赐威, 李倩玉, 李慧星, 等. 基于负荷聚合商业务的需求响应资源整合方法与运营机制[J]. 电力系统自动化, 2013, 37(17): 78-86. Gao Ciwei, Li Qianyu, Li Huixing, et al.Methodo- logy and operation mechanism of demand response resources integration based on load aggregator[J]. Automation of Electric Power Systems, 2013, 37(17): 78-86. [8] 黄伟, 李宁坤, 李玟萱, 等. 考虑多利益主体参与的主动配电网双层联合优化调度[J]. 中国电机工程学报, 2017, 37(12): 3418-3428. Huang Wei, Li Ningkun, Li Wenxuan, et al.Bi-level joint optimization dispatch of active distribution network considering the participation of multi- stakeholder[J]. Proceedings of the CSEE, 2017, 37(12): 3418-3428. [9] 鲁静, 宋斌, 向万红, 等. 基于区块链的电力市场交易结算智能合约[J]. 计算机系统应用, 2017, 26(12): 43-50. Lu Jing, Song Bin, Xiang Wanhong, et al.Smart contract for electricity transaction and charge settlement based on blockchain[J]. Computer Systems & Applications, 2017, 26(12): 43-50. [10] Kishigami J, Fujimura S, Watanabe H, et al.The blockchain-based digital content distribution system[C]// IEEE Fifth International Conference on Big Data and Cloud Computing (BDCloud), Dalian, China, 2015: 87-190. [11] Puthal D, Malik N, Mohanty S P, et al.The blockchain as a decentralized security framework [future directions][J]. IEEE Consumer Electronics Magazine, 2018, 7(2): 18-21. [12] 杨德昌, 赵肖余, 徐梓潇, 等. 区块链在能源互联网中应用现状分析和前景展望[J]. 中国电机工程学报, 2017, 37(13): 3664-3671. Yang Dechang, Zhao Xiaoyu, Xu Zixiao, et al.Developing status and prospect analysis of block- chain in energy internet[J]. Proceedings of the CSEE, 2017, 37(13): 3664-3671. [13] 张俊, 高文忠, 张应晨, 等. 运行于区块链上的智能分布式电力能源系统: 需求、概念、方法以及展望[J]. 自动化学报, 2017, 43(9): 1544-1554. Zhang Jun, Gao Wenzhong, Zhang Yingchen, et al.Blockchain based intelligent distributed electrical energy systems: needs, concepts, approacher and vision[J]. Acta Automatica Sinica, 2017, 43(9): 1544-1554. [14] 曾鸣, 程俊, 王雨晴, 等. 区块链框架下能源互联网多模块协同自治模式初探[J]. 中国电机工程学报, 2017, 37(13): 3672-3681. Zeng Ming, Cheng Jun, Wang Yuqing, et al.Primarily research for multi module cooperative autonomous mode of energy internet under block- chain framework[J]. Proceedings of the CSEE, 2017, 37(13): 3672-3681. [15] 马天男, 彭丽霖, 杜英, 等. 区块链技术下局域多微电网市场竞争博弈模型及求解算法[J]. 电力自动化设备, 2018, 38(5): 191-203. Ma Tiannan, Peng Lilin, Du Ying, et al.Competition game model for local multi-microgrid market based on block chain technology and its solution algorithm[J]. Electric Power Automation Equipment, 2018, 38(5): 191-203. [16] 卢强, 陈来军, 梅生伟. 博弈论在电力系统中典型应用及若干展望[J]. 中国电机工程学报, 2014, 34(29): 5009-5017. Lu Qiang, Chen Laijun, Mei Shengwei.Typical applications and prospects of game theory in power system[J]. Proceedings of the CSEE, 2014, 34(29): 5009-5017. [17] 张忠会, 赖飞屹, 谢义苗. 基于纳什均衡理论的电力市场三方博弈分析[J]. 电网技术, 2016, 40(12): 3671-3679. Zhang Zhonghui, Lai Feiyi, Xie Yimiao.Analysis of trilateral game in electricity market based on Nash equilibrium theory[J]. Power System Technology, 2016, 40(12): 3671-3679. [18] 李力行, 苗世洪, 孙丹丹. 多利益主体参与下主动配电网完全信息动态博弈行为[J]. 电工技术学报, 2018, 33(15): 3499-3509. Li Lixing, Miao Shihong, Sun Dandan.Dynamic games of complete information in active distribution network with multi-stakeholder participation[J]. Transactions of China Electrotechnical Society, 2018, 33(15): 3499-3509. [19] Nguyen P H, Kling W L, Ribeiro P F.A game theory strategy to integrate distributed agent-based functions in smart grids[J]. IEEE Transactions on Smart Grid, 2013, 4(1): 568-576. [20] 刘念, 赵璟, 王杰, 等. 基于合作博弈论的光伏微电网群交易模[J]. 电工技术学报, 2018, 33(8): 1903-1910. Liu Nian, Zhao Jing, Wang Jie, et al.A trading model of PV microgrid cluster based on cooperative game theory[J]. Transactions of China Electrotechnical Society, 2018, 33(8): 1903-1910. [21] 吴诚, 高丙团, 汤奕, 等. 基于主从博弈的发电商与大用户双边合同交易模型[J]. 电力系统自动化, 2016, 11(25): 56-62. Wu Cheng, Gao Bingtuan, Tang Yi, et al.Master- slave game based bilateral contract transaction model for generation companies and large consumers[J]. Automation of Electric Power Systems, 2016, 11(25): 56-62. [22] 顾洁. 电力市场辅助报价决策的灰色博弈模型研究[J]. 电力系统保护与控制, 2010, 38(10): 12-21. Gu Jie.Study on bidding strategy model for power market based on grey game theory[J]. Power System Protection and Control, 2010, 38(10): 12-21. [23] 高洁, 盛昭瀚. 演化博弈论及其在电力市场中的应用[J]. 电力系统自动化, 2003, 27(18): 18-21. Gao Jie, Sheng Zhaohan.Elementary groping for evolutionary game theory and its application in electricity market[J]. Automation of Electric Power Systems, 2003, 27(18): 18-21. [24] 张程, 杜松怀, 苏娟. 基于演化博弈的区域电力市场报价策略研究[J]. 现代电力, 2010, 27(2): 87-90. Zhang Cheng, Du Songhuai, Su Juan.Study on bidding strategies of regional electricity markets based on evolutionary game theory[J]. Modern Electric Power, 2010, 27(2): 87-90. [25] 黄仙, 王占华. 基于演化博弈的发电商竞策略仿真分析[J]. 现代电力, 2009, 26(3): 91-94. Huang Xian, Wang Zhanhua.Simulation and analysis of generation companies' bidding strategies based on evolutionary game theory[J]. Modern Electric Power, 2009, 26(3): 91-94. [26] 徐意婷, 艾芊, 胡剑生. 基于协同演化博弈算法的微网和配电网动态优化[J]. 电力系统保护与控制, 2016, 44(18): 8-16. Xu Yiting, Ai Qian, Hu Jiansheng.Dynamic optimization of microgrid and distribution network based on coevolutionary game algorithm[J]. Power System Protection and Control, 2016, 44(18): 8-16. [27] 李彬, 曹望璋, 张洁, 等. 基于异构区块链的多能系统交易体系及关键技术[J]. 电力系统自动化, 2018, 42(4): 183-193. Li Bin, Cao Wangzhang, Zhang Jie, et al.Transaction system and key technologies of multi-energy system based on heterogeneous blockchain[J]. Automation of Electric Power Systems, 2018, 42(4): 183-193. [28] 中国区块链应用研究中心. 图解区块链[M]. 北京:首都经济贸易大学出版社, 2016. [29] 佘维, 杨晓宇, 胡跃, 等. 基于联盟区块链的分布式能源交易认证模型[J]. 中国科学技术大学学报, 2018, 48(4): 307-313. She Wei, Yang Xiaoyu, Hu Yue, et al.Transaction certification model of distributed energy based on consortium blockchain[J]. Journal of University of Science and Technology of China, 2018, 48(4): 307-313. [30] Kang Jiawan, Yu Rong, Huang Xumin, et al.Enabling localized peer-to-peer electricity trading among plug-in hybrid electric vehicles using consortium blockchains[J]. IEEE Transactions on Industrial Informatics, 2017, 13(6): 3154-3164. [31] Zhang Qingfu, Li Hui.MOEA/D: a multiobjective evolutionary algorithm based on decomposition[J]. IEEE Transactions on Evolutionary Computation, 2008, 11(6): 712-731. [32] Das I, Dennis J E.Normal-boundary intersection: a new method for generating the pareto surface in nonlinear multicriteria optimization problems[J]. SIAM Journal on Optimization, 1998, 8(3): 631-657. [33] 李姚旺, 苗世洪, 尹斌鑫, 等. 含先进绝热压缩空气储能电站的电力系统实时调度模型[J]. 电工技术学报, 2019, 34(2): 387-397. Li Yaowang, Miao Shihong, Yin Binxin, et al.Real- time dispatch model for power system with advanced adiabatic compressed air energy storage[J]. Transa- ctions of China Electrotechnical Society, 2019, 34(2): 387-397. |
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