能源互联网多能量枢纽合作议价模型

doi:10.11930/j.issn.1004-9649.201912193

中国电力 ›› 2020, Vol. 53 ›› Issue (11): 89-96.DOI: 10.11930/j.issn.1004-9649.201912193

• 新能源电力系统源网荷储协调运行技术专栏 • 上一篇下一篇

能源互联网多能量枢纽合作议价模型

朱西平, 付迁, 李恣霖, 罗健, 王登松

西南石油大学电气信息学院，四川成都 610500

收稿日期:2020-01-02 修回日期:2020-03-06 出版日期:2020-11-05 发布日期:2020-11-05
通讯作者: 四川省科技项目(2019GFW150，2017TJPT0002)
作者简介:朱西平(1971—)，男，博士，教授，从事能源区块链技术及服务、能源互联网与大数据、无线传感器网与车载自组网等研究，E-mail：171372240@qq.com;付迁(1994—)，硕士研究生，从事能源互联网中能源的调度规划、能量枢纽以及需求侧响应技术研究，E-mail：824985249@qq.com
基金资助:
This work is supported by Science and Technology Project of Sichuan Province (No.2019GFW150, No.2017TJPT0002)

Model of Multi-energy Hub Cooperative Bargaining in Energy Internet

ZHU Xiping, FU Qian, LI Zilin, LUO Jian, WANG Dengsong

College of Electrical Information, Southwest Petroleum University, Chengdu 610500, China

Received:2020-01-02 Revised:2020-03-06 Online:2020-11-05 Published:2020-11-05

摘要/Abstract

摘要： 能源互联网的能量枢纽（energy-hub, EH）是实现区域内多能协调供应、区域间能源互补优化运行的有效途径。为实现区域内多能量枢纽的协调经济运行，保障不同能量枢纽之间的信息流和能量流互联互通，基于传统能量枢纽模型，构建多能量枢纽模型。同时考虑能量枢纽间能量交易的成本问题，提出多能量枢纽运营商间的合作议价模型。仿真分析表明：该模型能有效降低各运营商的运行成本，达到各能量枢纽之间能量流协调流动、资源利用率最大化的目的，减少了能源的浪费。

关键词: 能源互联网, 能量枢纽, 能源互补, 运行成本, 合作议价

Abstract: The energy hub (EH) of energy internet is an effective way to realize the coordinated supply of multi energy and the complementary and optimized operation among energy regions. In order to realize the coordinated and economic operation of multiple energy hubs within a region and to ensure the interconnection of information flow and energy flow between different energy hubs, this paper constructs a multi energy hub coordination model based on the traditional energy hub model. At the same time, considering the cost of energy transaction between energy hubs, a cooperative bargaining model among multi energy hub operators is proposed. The simulation analysis shows that it can effectively reduce the operating cost of each operator, achieve the coordinated flow of energy flow between energy hubs, maximize the utilization of resources, and reduce the waste of energy.

Key words: energy internet, energy hub, energy complementarity, operation cost, cooperative bargaining

朱西平, 付迁, 李恣霖, 罗健, 王登松. 能源互联网多能量枢纽合作议价模型[J]. 中国电力, 2020, 53(11): 89-96.

ZHU Xiping, FU Qian, LI Zilin, LUO Jian, WANG Dengsong. Model of Multi-energy Hub Cooperative Bargaining in Energy Internet[J]. Electric Power, 2020, 53(11): 89-96.

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参考文献

[1] 李德智, 龚桃荣. 用户侧多能互补微能源网的规划方法[J]. 中国电力, 2019, 52(11): 68-76
LI Dezhi, GONG Taorong. Planning method of multi-energy complementary micro energy grid on user side[J]. Electric Power, 2019, 52(11): 68-76
[2] 龙涛, 别朝红. 面向终端能源互联网的能效优化调度[J]. 中国电力, 2019, 52(6): 1-10
LONG Tao, BIE Zhaohong. Energy efficiency optimal dispatch for terminal energy Internet[J]. Electric Power, 2019, 52(6): 1-10
[3] 郝然, 艾芊, 朱宇超, 等. 基于能源集线器的区域综合能源系统分层优化调度[J]. 电力自动化设备, 2017, 37(6): 171-178
HAO Ran, AI Qian, ZHU Yuchao, et al. Hierarchical optimal dispatch based on energy hub for regional integrated energy system[J]. Electric Power Automation Equipment., 2017, 37(6): 171-178
[4] ABDELAZIZ A Y, EL-ZONKOLY A M, ELADL A M. Energy hub optimization using modified firefly algorithm[J]. 2017 8th International Renewable Energy Congress (IREC), 2017: 1-6.
[5] BARMAYOON M H, FOTUHI-FIRUZABAD M, RAJABI-GHAHNAVIEH A, et al. Energy storage in renewable-based residential energy hubs[J]. IET Generation, Transmission & Distribution, 2016, 10(13): 3127-3134.
[6] MA T F, WU J Y, HAO L L. Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub[J]. Energy Conversion and Management, 2017, 133: 292-306.
[7] MARTINI L. Trends of smart grids development as fostered by European research coordination: The contribution by the EERA JP on smart grids and the ELECTRA IRP[C]//2015 IEEE 5th International Conference on Power Engineering, Energy and Electrical Drives (POWERENG). Riga, Latvia. IEEE, 2015: 23-30.
[8] 史开拓, 刘念, 张建华, 等. 多运营主体的微电网随机匹配交易机制[J]. 电网技术, 2016, 40(2): 587-594
SHI Kaituo, LIU Nian, ZHANG Jianhua, et al. Random matching trading mechanism in microgrid of multi-operators[J]. Power System Technology, 2016, 40(2): 587-594
[9] SHEIKHI A, RAYATI M, BAHRAMI S, et al. Integrated demand side management game in smart energy hubs[J]. IEEE Transactions on Smart Grid, 2015, 6(2): 675-683.
[10] KAMYAB F, BAHRAMI S. Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets[J]. Energy, 2016, 106: 343-355.
[11] MAROUFMASHAT A, ELKAMEL A, FOWLER M, et al. Modeling and optimization of a network of energy hubs to improve economic and emission considerations[J]. Energy, 2015, 93: 2546-2558.
[12] YE R, LI C, LIANG X Y. Energy storage system in green data centers: architecture and management[J]. Journal of Computer Research and Development, 2016, 53(2): 326.
[13] QIAN Y L, ZHANG Y, TANG Y H, et al. Mathematical modeling and control optimization for energy Internet[J]. 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), 2017: 1-6.
[14] 何永秀, 宋栋, 夏天, 等. 基于合作博弈论的常规能源与新能源发电权置换交易模式研究[J]. 电网技术, 2017, 41(8): 2485-2490
HE Yongxiu, SONG Dong, XIA Tian, et al. Mode of generation right trade between renewable energy and conventional energy based on cooperative game theory[J]. Power System Technology, 2017, 41(8): 2485-2490
[15] NASH J F. The bargaining problem[J]. Econometrica, 1950, 18(2): 155.
[16] 梅生伟, 王莹莹, 刘锋. 风—光—储混合电力系统的博弈论规划模型与分析[J]. 电力系统自动化, 2011, 35(20): 13-19
MEI Shengwei, WANG Yingying, LIU Feng. A game theory based planning model and analysis for hybrid power system with wind generators-photovoltaic panels-storage batteries[J]. Automation of Electric Power Systems, 2011, 35(20): 13-19
[17] Independent Electricity System Operator (IESO). Power Data. Accessed: 2019. [Online]. Available: http://www.ieso.ca.
[18] LIU T H, ZHANG D D. Multi-objective optimal calculation for integrated local area energy system based on NSGA-Ⅱ algorithm[C]//2019 IEEE International Conference on Energy Internet (ICEI). Nanjing, China. IEEE, 2019: 310-315.
[19] FAN S L, LI Z S, WANG J H, et al. Cooperative economic scheduling for multiple energy hubs: a bargaining game theoretic perspective[J]. IEEE Access, 2018, 6: 27777-27789.
[20] LIU S Y, GU Y, WANG C, et al. Multi-energy coordination based on multi-agent system in energy Internet[C]//2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2). Beijing, China. IEEE, 2018: 1-5.

能源互联网多能量枢纽合作议价模型

Model of Multi-energy Hub Cooperative Bargaining in Energy Internet

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Model of Multi-energy Hub Cooperative Bargaining in Energy Internet

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