TWO-LAYER OPTIMIZATION MODEL FOR MULTI-ENERGY INTERACTIVE MICROGRID CLUSTER SYSTEM BASED ON TRIPARTITE GAME

Xie Jingdong; Xu Zhenbang

doi:10.19912/j.0254-0096.tynxb.2022-1675

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (2) : 384-394. DOI: 10.19912/j.0254-0096.tynxb.2022-1675

TWO-LAYER OPTIMIZATION MODEL FOR MULTI-ENERGY INTERACTIVE MICROGRID CLUSTER SYSTEM BASED ON TRIPARTITE GAME

Xie Jingdong¹, Xu Zhenbang²

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Abstract

Along with the increasing proportion of new energy, the multi-energy interactive microgrid cluster has become an important development direction of smart grid with its ability to promote energy inter-grid and enhance the utilization of new energy. In order to solve the problem that the price of energy trading is manipulated in the process of energy trading between MNEs and users, and a fair energy trading mechanism cannot be established between MNEs and users, this paper establishes a three-party game model among the government, MNEs and users to ensure the fair and just energy trading behavior between MNEs and users. Since the traditional single-layer optimization method is difficult to reveal the interaction behavior among multiple subjects, this paper establishes a two-layer optimization model of multi-energy interactive microgrid cluster system based on a three-party game among government, multi-energy interactive microgrid cluster and users. The upper layer of the model is a three-party game among the government, the multienergy interactive microgrid cluster and the users. The objectives of the three-party game are to maximize the social welfare of the government, optimize the benefits of the multi-energy interactive microgrid cluster and maximize the satisfaction of the users. The lower layer of the model is the optimal scheduling of the multi-energy interactive microgrid cluster system, which coordinates the optimal allocation of various energy conversions and the lowest operating cost. Finally, the effectiveness of the model is verified by arithmetic simulation.

Key words

microgrid cluster / game theory / optimizing operation / bi-level optimization

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Xie Jingdong, Xu Zhenbang. TWO-LAYER OPTIMIZATION MODEL FOR MULTI-ENERGY INTERACTIVE MICROGRID CLUSTER SYSTEM BASED ON TRIPARTITE GAME[J]. Acta Energiae Solaris Sinica. 2024, 45(2): 384-394 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1675

References

[1] 康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架[J]. 电力系统自动化, 2017, 41(9): 2-11.
KANG C Q, YAO L Z.Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J]. Automation of electric power systems, 2017, 41(9): 2-11.
[2] 谢敏, 吉祥, 柯少佳, 等. 基于目标级联分析法的多微网主动配电系统自治优化经济调度[J]. 中国电机工程学报, 2017, 37(17): 4911-4921, 5210.
XIE M, JI X, KE S J, et al.Autonomous optimized economic dispatch of active distribution power system with multi-microgrids based on analytical target cascading theory[J]. Proceedings of the CSEE, 2017, 37(17): 4911-4921, 5210.
[3] 吕智林, 廖庞思, 杨啸. 计及需求侧响应的光伏微网群与主动配电网双层优化[J]. 电力系统及其自动化学报, 2021, 33(8): 70-78.
LYU Z L, LIAO P S, YANG X.Bi-layer optimization of PV multi-microgrid and active distribution network considering demand-side response[J]. Proceedings of the CSU-EPSA, 2021, 33(8): 70-78.
[4] 武梦景, 万灿, 宋永华, 等. 含多能微网群的区域电热综合能源系统分层自治优化调度[J]. 电力系统自动化, 2021, 45(12): 20-29.
WU M J, WAN C, SONG Y H, et al.Hierarchical autonomous optimal dispatching of district integrated heating and power system with multi-energy microgrids[J]. Automation of electric power systems, 2021, 45(12): 20-29.
[5] 苏磊, 李振坤, 张智泉, 等. 基于机会约束规划的综合能源微网群协调运行策略研究[J]. 电力系统保护与控制, 2021, 49(14): 123-131.
SU L, LI Z K, ZHANG Z Q, et al.A coordinated operation strategy for integrated energy microgrid clusters based on chance-constrained programming[J]. Power system protection and control, 2021, 49(14): 123-131.
[6] 吴红斌, 孙瑞松, 蔡高原. 多微网互联系统的动态经济调度研究[J]. 太阳能学报, 2018, 39(5): 1426-1433.
WU H B, SUN R S, CAI G Y.Dynamic economic dispatch for multi-microgrid interconnection system[J]. Acta energiae solaris sinica, 2018, 39(5): 1426-1433.
[7] 张宇威, 肖金星, 杨军, 等. 基于风光数据驱动不确定集合的配电网与多微网鲁棒经济调度[J]. 电力建设, 2021, 42(10): 40-50.
ZHANG Y W, XIAO J X, YANG J, et al.Data-driven robust economic dispatch for distribution network and multiple micro-grids considering correlativity of wind and solar output[J]. Electric power construction, 2021, 42(10): 40-50.
[8] 符杨, 邢馨月, 李振坤, 等. 基于主从博弈的微电网群多阶段鲁棒优化规划[J]. 电力自动化设备, 2022, 42(4): 1-8.
FU Y, XING X Y, LI Z K, et al.Multi-stage robust optimization planning of microgrid clusters based on master-slave game[J]. Electric power automation equipment, 2022, 42(4): 1-8.
[9] 顾欣, 王琦, 胡云龙, 等. 基于纳什议价的多微网综合能源系统分布式低碳优化运行策略[J]. 电网技术, 2022, 46(4): 1464-1482.
GU X, WANG Q, HU Y L, et al.Distributed low-carbon optimal operation strategy of multi-microgrids integrated energy system based on Nash bargaining[J]. Power system technology, 2022, 46(4): 1464-1482.
[10] 乔学博, 杨志祥, 李勇, 等. 计及两级碳交易和需求响应的多微网合作运行优化策略[J]. 高电压技术, 2022, 48(7): 2573-2583.
QIAO X B, YANG Z X, LI Y, et al.Optimization strategy for cooperative operation of multi-microgrids considering two-level carbon trading and demand response[J]. High voltage engineering, 2022, 48(7): 2573-2583.
[11] 李鹏, 吴迪凡, 李雨薇, 等. 基于综合需求响应和主从博弈的多微网综合能源系统优化调度策略[J]. 中国电机工程学报, 2021, 41(4): 1307-1321, 1538.
LI P, WU D F, LI Y W, et al.Optimal dispatch of multi-microgrids integrated energy system based on integrated demand response and stackelberg game[J]. Proceedings of the CSEE, 2021, 41(4): 1307-1321, 1538.
[12] 陈友芹, 蒋炯, 殷展翔, 等. 基于NCPSO的微网群优化调度策略研究[J]. 太阳能学报, 2022, 43(8): 477-483.
CHEN Y Q, JIANG J, YIN Z X, et al.Research on optimal scheduling strategy of microgrid clusters based on ncpso[J]. Acta energiae solaris sinica, 2022, 43(8): 477-483.
[13] 杜炜, 窦迅, 王镇, 等. 考虑热电余量交易的微网群优化调度[J]. 电网技术, 2020, 44(10): 3777-3786.
DU W, DOU X, WANG Z, et al.Optimal scheduling for microgrid clusters considering heat-electricity margin transaction[J]. Power system technology, 2020, 44(10): 3777-3786.
[14] 耿健, 杨冬梅, 高正平, 等. 含储能的冷热电联供分布式综合能源微网优化运行[J]. 电力工程技术, 2021, 40(1): 25-32.
GENG J, YANG D M, GAO Z P, et al.Optimal operation of distributed integrated energy microgrid with CCHP considering energy storage[J]. Electric power engineering technology, 2021, 40(1): 25-32.
[15] 谢敬东, 卞泽远, 吕志伟, 等. 基于三方演化博弈的微网接入公共配电网服务输配电价调整监管机制[J]. 科学技术与工程, 2021, 21(15): 6312-6321.
XIE J D, BIAN Z Y, LYU Z W, et al.The regulatory mechanism of microgrid access to public distribution network service transmission and distribution price adjustment based on tripartite evolutionary game[J]. Science technology and engineering, 2021, 21(15): 6312-6321.