基于非对称议价的广域综合能源系统多能共享鲁棒-纳什优化方法

黄立言, 艾欣, 王哲

太阳能学报 ›› 2026, Vol. 47 ›› Issue (8) : 338-349.

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (8) : 338-349. DOI: 10.19912/j.0254-0096.tynxb.2025-0497

基于非对称议价的广域综合能源系统多能共享鲁棒-纳什优化方法

  • 黄立言, 艾欣, 王哲
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ROBUST-NASH OPTIMIZATION METHOD FOR MULTI-ENERGY SHARING IN WIDE-AREA INTEGRATED ENERGY SYSTEMS BASED ON ASYMMETRIC BARGAINING

  • Huang Liyan, Ai Xin, Wang Zhe
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摘要

为解决源荷不确定环境下跨区域综合能源系统间多能共享的合作博弈问题,首先,考虑跨区域综合能源系统间的多能源协同特性,以多个跨区域综合能源系统互联的广域综合能源系统为研究对象,构建面向广域综合能源系统的多能共享合作运行模型。其次,为解决资源禀赋综合能源系统间合作博弈及其收益公平分配问题,在所建综合能源系统模型基础上,提出基于非对称议价的广域综合能源系统电热共享纳什谈判模型。然后,为保护合作主体数据隐私并降低源荷不确定性的影响,提高广域综合能源系统纳什谈判的可靠性,提出一种日前-实时两阶段鲁棒-纳什优化方法,并利用交替方向乘子法与列和约束生成法联合求解。最后,通过算例分析验证所提模型和方法在不确定环境下,可有效改善系统的策略适应性、提升收益分配的公平性,并兼顾低碳经济的优化目标。

Abstract

To solve the cooperative game problem of multi-energy sharing among cross regional integrated energy systems in uncertain source load environments, firstly, considering the multi-energy collaboration characteristics between cross regional integrated energy systems, taking the wide area integrated energy system interconnected by multiple cross regional integrated energy systems as the research object, a multi-energy sharing cooperative operation model for wide area integrated energy systems is constructed. Secondly, in order to solve the cooperative game and fair distribution of benefits between resource endowment integrated energy systems, a Nash negotiation model for wide area integrated energy system electric and thermal sharing based on asymmetric bargaining is proposed on the basis of the established integrated energy system model. Then, in order to protect the data privacy of cooperative entities and reduce the impact of source load uncertainty and improve the reliability of Nash negotiations in wide area integrated energy systems, a two-stage robust Nash optimization method of day-ahead real-time is proposed, and the alternating direction multiplier method and column and constraint generation algorithm are used for solving. Finally, through case analysis, it is verified that the proposed model and method can effectively improve the adaptability of strategies, fairness of benefit distribution, and low-carbon economy of the system in uncertain environments.

关键词

综合能源系统 / 多能共享 / 不确定性 / 合作博弈 / 非对称议价 / 两阶段鲁棒-纳什优化

Key words

integrated energy system / multi-energy sharing / uncertainty / cooperative game / asymmetric bargaining / two-stage robust-Nash optimization

引用本文

导出引用
黄立言, 艾欣, 王哲. 基于非对称议价的广域综合能源系统多能共享鲁棒-纳什优化方法[J]. 太阳能学报. 2026, 47(8): 338-349 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0497
Huang Liyan, Ai Xin, Wang Zhe. ROBUST-NASH OPTIMIZATION METHOD FOR MULTI-ENERGY SHARING IN WIDE-AREA INTEGRATED ENERGY SYSTEMS BASED ON ASYMMETRIC BARGAINING[J]. Acta Energiae Solaris Sinica. 2026, 47(8): 338-349 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0497
中图分类号: TM732   

参考文献

[1] 赵振宇, 李炘薪, 包格日乐图. 园区综合能源系统动态多目标规划模型研究[J]. 太阳能学报, 2025, 46(5): 213-226.
Zhao Z Y, Li X X, Bao G R L T. Research on dynamic multi-objective programming model for park-level integrated energy system[J]. Acta Energiae Solaris Sinica, 2025, 46(5): 213-226.
[2] Tillie N, Van Den Dobbelsteen A, Doepel D, et al. Towards CO2 neutral urban planning: presenting the Rotterdam energy approach and planning (REAP)[J]. Journal of Green Building, 2009, 4(3): 103-112.
[3] 辜勇, 汤浩, 葛平旭, 等. 含柔性互联的港口综合能源系统能量流开闭环混合控制策略[J]. 上海海事大学学报, 2025, 46(2): 102-112.
Gu Y, Tang H, Ge P X, et al.Open-loop and closed-loop hybrid control strategy of energy flow in port integrated energy systems with flexible interconnection[J]. Journal of Shanghai Maritime University, 2025, 46(2): 102-112.
[4] 喻潇, 蒋东荣, 肖昊, 等. 计及动态氢价的综合能源系统低碳经济调度[J]. 重庆理工大学学报(自然科学), 2024, 38(12): 197-206.
Yu X, Jiang D R, Xiao H, et al.Low-carbon economic dispatch of integrated energy system considering dynamic hydrogen price[J]. Journal of Chongqing University of Technology (Natural Science), 2024, 38(12): 197-206.
[5] 骆钊, 杨林燕, 王华, 等. 含碳捕集电厂-电转气-液化天然气协同的综合能源系统优化调度[J]. 太阳能学报, 2025, 46(1): 438-448.
Luo Z, Yang L Y, Wang H, et al.Optimization and scheduling of integrated energy system with carbon capture power plant, electricity to gas and liquefied natural gas synergy[J]. Acta Energiae Solaris Sinica, 2025, 46(1): 438-448.
[6] 陈思, 杨宏欣, 王翀, 等. 源荷置信度水平下光伏光热耦合热电联产系统的调度优化[J]. 太阳能学报, 2024, 45(11): 352-359.
Chen S, Yang H X, Wang C, et al.Scheduling optimization of photovoltaic-thermal coupled cogeneration system under source/load confidence level[J]. Acta Energiae Solaris Sinica, 2024, 45(11): 352-359.
[7] Ma Y M, Wang H X, Hong F, et al.Modeling and optimization of combined heat and power with power-to-gas and carbon capture system in integrated energy system[J]. Energy, 2021, 236: 121392.
[8] 李欣, 李涵文, 陈德秋, 等. 储液式CCS耦合P2G的综合能源系统低碳经济调度[J]. 电力系统及其自动化学报, 2024, 36(5): 105-113.
Li X, Li H W, Chen D Q, et al.Low-carbon economic dispatching of integrated energy system with coupling solvent-storage CCS and P2G[J]. Proceedings of the CSU-EPSA, 2024, 36(5): 105-113.
[9] Chen M Z, Lu H, Chang X Q, et al.An optimization on an integrated energy system of combined heat and power, carbon capture system and power to gas by considering flexible load[J]. Energy, 2023, 273: 127203.
[10] 于娜, 原志豪, 黄大为, 等. 计及多重不确定性和P2P交易模式的多综合能源系统优化运行研究[J]. 东北电力大学学报, 2025, 45(2): 93-103.
Yu N, Yuan Z H, Huang D W, et al.Research on optimal operation of multi-integrated energy system considering multiple uncertainties and P2P transaction mode[J]. Journal of Northeast Electric Power University, 2025, 45(2): 93-103.
[11] 周鑫, 韩肖清, 李廷钧, 等. 计及需求响应和电能交互的多主体综合能源系统主从博弈优化调度策略[J]. 电网技术, 2022, 46(9): 3333-3346.
Zhou X, Han X Q, Li T J, et al.Master-slave game optimal scheduling strategy for multi-agent integrated energy system based on demand response and power interaction[J]. Power System Technology, 2022, 46(9): 3333-3346.
[12] Chiş A, Koivunen V.Coalitional game-based cost optimization of energy portfolio in smart grid communities[J]. IEEE Transactions on Smart Grid, 2019, 10(2): 1960-1970.
[13] 高源, 万屹涵, 赵健. 基于碳灵敏度因子的社区P2P电能交易策略[J]. 电力自动化设备, 2024, 44(12): 162-169.
Gao Y, Wan Y H, Zhao J.Community P2P electric energy trading strategy based on carbon sensitivity factor[J]. Electric Power Automation Equipment, 2024, 44(12): 162-169.
[14] Wei C, Shen Z Z, Xiao D L, et al.An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining[J]. Applied Energy, 2021, 295: 117024.
[15] Shuai X Y, Wang X L, Wu X, et al.Peer-to-peer multi-energy distributed trading for interconnected microgrids: a general Nash bargaining approach[J]. International Journal of Electrical Power & Energy Systems, 2022, 138: 107892.
[16] 吴锦领, 楼平, 管敏渊, 等. 基于非对称纳什谈判的多微网电能共享运行优化策略[J]. 电网技术, 2022, 46(7): 2711-2723.
Wu J L, Lou P, Guan M Y, et al.Operation optimization strategy of multi-microgrids energy sharing based on asymmetric Nash bargaining[J]. Power System Technology, 2022, 46(7): 2711-2723.
[17] Xu J Z, Yi Y Q.Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: a Nash bargaining approach[J]. Energy, 2023, 263: 125712.
[18] 黄昊, 倪秋龙, 李震, 等. 考虑柔性负荷无功调节能力的配网日前两阶段无功随机优化调度[J]. 电力系统保护与控制, 2023, 51(16): 23-33.
Huang H, Ni Q L, Li Z, et al.Day-ahead two-stage stochastic reactive power scheduling optimization for a distribution network considering the reactive power regulation capability of flexible loads[J]. Power System Protection and Control, 2023, 51(16): 23-33.
[19] 李江南, 程韧俐, 周保荣, 等. 含碳捕集及电转氢设备的低碳园区综合能源系统随机优化调度[J]. 中国电力, 2024, 57(5): 149-156.
Li J N, Cheng R L, Zhou B R, et al.Stochastic optimal of integrated energy system in low-carbon parks considering carbon capture storage and power to hydrogen[J]. Electric Power, 2024, 57(5): 149-156.
[20] Zhao L, Zeng B.Robust unit commitment problem with demand response and wind energy[C]//2012 IEEE Power and Energy Society General Meeting. San Diego, CA, USA, 2012: 1-8.
[21] An Y, Zeng B.Exploring the modeling capacity of two-stage robust optimization: variants of robust unit commitment model[J]. IEEE Transactions on Power Systems, 2015, 30(1): 109-122.
[22] Bertsimas D, Litvinov E, Sun X A, et al.Adaptive robust optimization for the security constrained unit commitment problem[J]. IEEE Transactions on Power Systems, 2013, 28(1): 52-63.
[23] 郭尊, 李庚银, 周明, 等. 面向风电消纳的电-气联合系统分散协调鲁棒优化调度模型[J]. 中国电机工程学报, 2020, 40(20): 6442-6454.
Guo Z, Li G Y, Zhou M, et al.A decentralized and robust optimal scheduling model of integrated electricity-gas system for wind power accommodation[J]. Proceedings of the CSEE, 2020, 40(20): 6442-6454.
[24] Zhang W W, Wang W Q, Fan X C, et al.Low-carbon optimal operation strategy of multi-park integrated energy system considering multi-energy sharing trading mechanism and asymmetric Nash bargaining[J]. Energy Reports, 2023, 10: 255-284.
[25] Li L X, Zhang S, Cao X L, et al.Assessing economic and environmental performance of multi-energy sharing communities considering different carbon emission responsibilities under carbon tax policy[J]. Journal of Cleaner Production, 2021, 328: 129466.
[26] 马腾飞, 裴玮, 肖浩, 等. 基于纳什谈判理论的风-光-氢多主体能源系统合作运行方法[J]. 中国电机工程学报, 2021, 41(1): 25-39.
Ma T F, Pei W, Xiao H, et al.Cooperative operation method for wind-solar-hydrogen multi-agent energy system based on Nash bargaining theory[J]. Proceedings of the CSEE, 2021, 41(1): 25-39.
[27] Zhang H L, Zhou S Y, Gu W, et al.Optimal operation of micro-energy grids considering shared energy storage systems and balanced profit allocations[J]. CSEE Journal of Power and Energy Systems, 2023, 9(1): 254-271.
[28] 郑杰凯, 何山, 王维庆, 等. 基于非对称议价的多综合能源服务商分布鲁棒热电交易优化[J]. 太阳能学报, 2024, 45(10): 121-133.
Zheng J K, He S, Wang W Q, et al.Distributionally robust thermoelectricity trading optimization for multiple-integrated energy service providers based on asymmetric Nash bargaining[J]. Acta Energiae Solaris Sinica, 2024, 45(10): 121-133.
[29] 李鹏, 窦真兰, 吴和先, 等. 计及多重不确定性的小型园区多能源系统优化调度方法[J]. 太阳能学报, 2025, 46(3): 214-224.
Li P, Dou Z L, Wu H X, et al.Optimal scheduling method for small-scale community multi-energy system considering multiple uncertainties[J]. Acta Energiae Solaris Sinica, 2025, 46(3): 214-224.
[30] Ding J Y, Gao C W, Song M, et al.Optimal operation of multi-agent electricity-heat-hydrogen sharing in integrated energy system based on Nash bargaining[J]. International Journal of Electrical Power & Energy Systems, 2023, 148: 108930.

基金

国家重点研发计划(2021YFB4000104)

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