基于势博弈的负荷聚合商日前市场动态定价模型

doi:10.3969/j.issn.2097-0706.2023.11.008

综合智慧能源 ›› 2023, Vol. 45 ›› Issue (11): 62-69.doi: 10.3969/j.issn.2097-0706.2023.11.008

基于势博弈的负荷聚合商日前市场动态定价模型

梅文卿¹(), 刘晓峰¹^,^*(), 王嘉诚¹(), 谭梦玲²

1.南京师范大学电气与自动化工程学院，南京 210023
2.国网九江供电公司，江西九江 332099

收稿日期:2023-02-27 修回日期:2023-07-05 出版日期:2023-11-25
通讯作者: * 刘晓峰（1991），男，讲师，硕士生导师，博士，从事需求响应、博弈论、电力市场等方面的研究， liuxiaofeng@njnu.edu.cn。
* 刘晓峰（1991），男，讲师，硕士生导师，博士，从事需求响应、博弈论、电力市场等方面的研究， liuxiaofeng@njnu.edu.cn。
* 刘晓峰（1991），男，讲师，硕士生导师，博士，从事需求响应、博弈论、电力市场等方面的研究， liuxiaofeng@njnu.edu.cn。
作者简介:梅文卿（1999），男，在读硕士研究生，从事博弈论、电力市场等方面的研究，1065793928@qq.com；
王嘉诚（2000），男，在读硕士研究生，从事电动汽车与碳排放等方面的研究，1204292675@qq.com。
基金资助:
江苏省高等学校基础科学（自然科学）研究面上项目(23KJB470020)

A day-ahead market pricing model for load aggregators based on potential game

MEI Wenqing¹(), LIU Xiaofeng¹^,^*(), WANG Jiacheng¹(), TAN Mengling²

1. School of Electrical and Automation Engineering， Nanjing Normal University， Nanjing 210023，China
2. State Grid Jiujiang Electric Power Supply Company， Jiujiang 332099，China

Received:2023-02-27 Revised:2023-07-05 Published:2023-11-25
Supported by:
Fundamental Science （Natural Science） Research Program of Universities and Colleges in Jiangsu Province(23KJB470020)

摘要/Abstract

摘要：

随着居民用电量的不断提高，新型电力系统加速构建，需求响应成为保障上级电网安全稳定的重要手段，系统对需求侧的重视程度大幅提高。负荷聚合商作为上级电网和用户之间的协调机构，发挥着越来越重要的作用。为促进负荷聚合商日前投标市场的稳定性并提高用户参与需求响应的积极性，将参与需求响应的负荷资源作为广义需求侧资源，提出基于价格激励的需求响应机制，引入博弈理论及势博弈概念，建立上级电网、负荷聚合商和用户的分层交易模型。首先，根据用户的响应机制及日前市场的投标价格机制建立用户和负荷聚合商的收益模型；随后，建立各负荷聚合商之间的非合作博弈模型，通过构建势函数将原来的多目标优化问题转换为单目标凸二次规划问题，能够短时间内收敛至纳什均衡且对大规模需求响应仍能保持收敛性。算例分析表明，该模型可在提高负荷聚合商利润的同时提升用户的收益。

关键词: 新型电力系统, 需求响应, 电力市场, 非合作博弈, 势博弈, 负荷聚合商, 日前市场投标, 纳什均衡

Abstract:

As residential electricity consumption continues to increase and new power systems are under construction， demand response has become an important means to ensure the safety and stability of the superior power grid，and higher requirements on demand side are proposed by the power grid. Load aggregators play an increasingly important role as the intermediary between the system and users. To keep the stability of the aggregators' day-ahead bidding market and motivate users to participate in demand response， the load resources participating in demand response are taken as generalized demand-side resources. Then， a demand response mechanism based on price incentives is proposed， and a hierarchical trading model including the superior grid， load aggregators and users is established based on game theory and potential game. The revenue models of users and load aggregators are made based on the user response mechanism and day-ahead market bidding mechanism. The models can simplify the multi-objective optimization problem to single-objective convex quadratic programming problems through function construction. The proposed algorithm can converge to Nash equilibria in a short time and maintain the convergence under large-scale demand responses. Proven by the practical cases， the proposed model can improve the profit of load aggregators and the revenue of users at the same time.

Key words: new power system, demand response, electrical power market, non-cooperative game, potential game, load aggregator, day-ahead market bidding, Nash equilibrium

中图分类号:

TK01⁺8:TM73

梅文卿, 刘晓峰, 王嘉诚, 谭梦玲. 基于势博弈的负荷聚合商日前市场动态定价模型[J]. 综合智慧能源, 2023, 45(11): 62-69.

MEI Wenqing, LIU Xiaofeng, WANG Jiacheng, TAN Mengling. A day-ahead market pricing model for load aggregators based on potential game[J]. Integrated Intelligent Energy, 2023, 45(11): 62-69.

图/表 9

图1

图2

图3

图4

图5

图6

图7

表1

表2

参考文献 19

[1]	王凌云, 安晓, 杨波, 等. 考虑负荷聚合商参与下的微网双层两阶段优化调度[J]. 三峡大学学报(自然科学版), 2021, 43(2):86-92.
	WANG Lingyun, AN Xiao, YANG Bo, et al. Double level two-stage optimal scheduling of microgrid with the participation of load aggregator[J]. Journal of China Three Gorges University(Natural Sciences), 2021, 43(2):86-92.
[2]	AGHAEI J, ALIZADEH M I, SIANO P, et al. Contribution of emergency demand response programs in power system reliability[J]. Energy, 2016, 103 : 688-696. doi: 10.1016/j.energy.2016.03.031
[3]	孙玲玲, 高赐威, 谈健, 等. 负荷聚合技术及其应用[J]. 电力系统自动化, 2017, 41(6):159-167.
	SUN Lingling, GAO Ciwei, TAN Jian, et al. Load aggregation technology and its applications[J]. Automation of Electric Power Systems, 2017, 41(6):159-167.
[4]	许志荣, 张高瑞. 响应用户有限理性需求的微电网优化策略[J]. 综合智慧能源, 2022, 44(11): 43-49. doi: 10.3969/j.issn.2097-0706.2022.11.006
	XU Zhirong, ZHANG Gaorui. Optimization strategy of microgrid responding users' bounded rational demand[J]. Integrated Intelligent Energy, 2022, 44(11): 43-49. doi: 10.3969/j.issn.2097-0706.2022.11.006
[5]	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. Methodology and operation mechanism of demand response resources integration based on load aggregator[J]. Automation of Electric Power Systems, 2013, 37(17):78-86.
[6]	王芸芸, 马志程, 周强, 等. 计及公平性的多能合作博弈鲁棒优化调度[J]. 综合智慧能源, 2023, 45(2): 10-21. doi: 10.3969/j.issn.2097-0706.2023.02.002
	WANG Yunyun, MA Zhicheng, ZHOU Qiang, et al. Robust optimal scheduling of multi-energy cooperative game considering fairness[J]. Integrated Intelligent Energy, 2023, 45(2): 10-21. doi: 10.3969/j.issn.2097-0706.2023.02.002
[7]	张静页, 王磊, 刘顺桂. 负荷聚合商参与可中断负荷项目的成本效益分析[J]. 南方电网技术, 2016, 10(8):74-81.
	ZHANG Jingye, WANG Lei, LIU Shungui. Cost-benefit analysis of load aggregator participating in interruptible load program[J]. Southern Power System Technology, 2016, 10(8):74-81.
[8]	何沁蔓, 刘晓峰, 王琦, 等. 计及用电满意度优先级划分的负荷聚合商调度策略研究[J]. 电网技术, 2021, 45(7):2666-2675.
	HE Qinman, LIU Xiaofeng, WANG Qi, et al. Scheduling strategy of load aggregator considering priority classification of electricity consumption satisfaction[J]. Power System Technology, 2021, 45(7):2666-2675.
[9]	吴宛潞, 韩帅, 孙乐平, 等. 负荷聚合商多类型需求侧资源激励价格制定一般模型及应用[J]. 电力建设, 2021, 42(1):1-9. doi: 10.12204/j.issn.1000-7229.2021.01.001
	WU Wanlu, HAN Shuai, SUN Leping, et al. A general incentive pricing model and its application for multi-type demand-side resources of load aggregators[J]. Electric Power Construction, 2021, 42(1):1-9. doi: 10.12204/j.issn.1000-7229.2021.01.001
[10]	张晓东, 艾欣, 潘玺安. 考虑用户可调度潜力的负荷聚合商优化调度策略[J]. 华北电力大学学报(自然科学版), 2023, 50(1):28-37.
	ZHANG Xiaodong, AI Xin, PAN Xi'an. Optimal scheduling strategy of load aggregators considering user′s scheduling potential[J]. Journal of North China Electric Power University (Natural Science Edition), 2023, 50(1):28-37.
[11]	刘晓峰, 高丙团, 罗京, 等. 基于非合作博弈的居民负荷分层调度模型[J]. 电力系统自动化, 2017, 41(14):54-60.
	LIU Xiaofeng, GAO Bingtuan, LUO Jing, et al. Non-cooperative game based hierarchical dispatch model of residential loads[J]. Automation of Electric Power Systems, 2017, 41(14):54-60.
[12]	张开宇, 宋依群, 严正, 等. 负荷聚合商市场侧投标与用户侧调度的双向决策模型研究[J]. 水电能源科学, 2015, 33(9):209-212.
	ZHANG Kaiyu, SONG Yiqun, YAN Zheng, et al. Research on bidirectional decision-making for load aggregators participating in market transactions and dispatching adjustable loads[J]. Water Resources and Power, 2015, 33(9):209-212.
[13]	冶兆年, 赵长禄, 王永真, 等. 基于纳什议价的共享储能能源互联网络双目标优化[J]. 综合智慧能源, 2022, 44(7): 40-48. doi: 10.3969/j.issn.2097-0706.2022.07.005
	YE Zhaonian, ZHAO Changlu, WANG Yongzhen, et al. Dual-objective optimization of energy networks with shared energy storage based on Nash bargaining[J]. Integrated Intelligent Energy, 2022, 44(7): 40-48. doi: 10.3969/j.issn.2097-0706.2022.07.005
[14]	WANG X, YANG J Y, ZHANG K, et al. Game-theoretic analysis of market-based operation mechanism for demand response resources[J]. International Journal of Electrical Power and Energy Systems, 2022, 134: 107456. doi: 10.1016/j.ijepes.2021.107456
[15]	朱兆霞, 邹斌. PJM日前市场电价的统计分析[J]. 电力系统自动化, 2006, 30(23):53-57.
	ZHU Zhaoxia, ZOU Bin. Statistical analysis of day-ahead prices in PJM market[J]. Automation of Electric Power Systems, 2006, 30(23):53-57.
[16]	BHATTI B A, BROADWATER R. Distributed Nash equilibrium seeking for a dynamic micro-grid energy trading game with non-quadratic payoffs[J]. Energy, 2020, 202:117709. doi: 10.1016/j.energy.2020.117709
[17]	汪希玥, 徐箭, 廖思阳, 等. 考虑虚拟储能特性的柔性负荷调控裕度评估方法[J]. 华电技术, 2021, 43(9):37-45.
	WANG Xiyue, XU Jian, LIAO Siyang, et al. Flexible load regulation margin evaluation method considering virtual energy storage characteristics[J]. Huadian Technology, 2021, 43(9): 37-45.
[18]	MONDERER D, SHAPLEY L S. Potential games[J]. Games and Economic Behavior, 1996, 14(1): 124-143. doi: 10.1006/game.1996.0044
[19]	LIANG Y L, LIU F, MEI S W. Distributed real-time economic dispatch in smart grids: A state-based potential game approach[J]. IEEE Transactions on Smart Grid, 2018, 9(5): 4194-4208. doi: 10.1109/TSG.5165411

LA	场景1	场景2
1	9 711.34	9 676.50
2	11 404.43	11 341.67
3	12 917.33	12 673.65

LA	用户	场景1	场景2
1	A类用户	0.563 3	0.538 9
	B类用户	0.287 0	0.271 9
	C类用户	0.191 3	0.181 3
2	A类用户	0.473 2	0.472 5
	B类用户	0.237 0	0.236 9
	C类用户	0.158 0	0.157 9
3	A类用户	0.453 0	0.440 1
	B类用户	0.226 5	0.220 2
	C类用户	0.151 0	0.146 8

基于势博弈的负荷聚合商日前市场动态定价模型

A day-ahead market pricing model for load aggregators based on potential game

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 9

参考文献 19

相关文章 15

编辑推荐

Metrics

本文评价

[1]	邹风华, 朱星阳, 殷俊平, 孟诗语, 江海燕, 陈爱康, 刘澜. “双碳”目标下建筑能源系统发展趋势分析[J]. 综合智慧能源, 2024, 46(8): 36-40.
[2]	王泽宁, 李文中, 李东辉, 徐泰山, 俞俊. 基于软件定义的新型电力系统分层自治电力平衡模式研究[J]. 综合智慧能源, 2024, 46(7): 1-11.
[3]	何方波, 裴力耕, 郑睿, 范康健, 张晓曼, 李更丰. “源网荷储”协同助力陕西省新型电力系统建设[J]. 综合智慧能源, 2024, 46(7): 40-46.
[4]	郁海彬, 卢闻州, 唐亮, 张煜晨, 邹翔宇, 姜玉靓, 刘嘉宝. 考虑风险偏好的多主体虚拟电厂经济调度与收益分配策略[J]. 综合智慧能源, 2024, 46(6): 66-77.
[5]	王亮, 邓松. 面向新型电力系统的异常数据检测方法[J]. 综合智慧能源, 2024, 46(5): 12-19.
[6]	王永利, 王亚楠, 马子奔, 秦雨萌, 陈锡昌, 滕越. 面向区块链技术应用的能源交易系统效果评价[J]. 综合智慧能源, 2024, 46(4): 78-84.
[7]	丁乐言, 柯松, 杨军, 施兴烨. 基于自适应控制参数整定的虚拟同步发电机控制策略[J]. 综合智慧能源, 2024, 46(3): 35-44.
[8]	苑曙光, 张瑜婷, 王峰, 苑广震. 蒙西地区规模化储能商业运行模式及风险分析[J]. 综合智慧能源, 2024, 46(3): 63-71.
[9]	李彦高, 林健, 马雨彤. 电价改革形势下电网企业代理购电风险分析及应对策略研究[J]. 综合智慧能源, 2024, 46(3): 79-86.
[10]	李成雲, 杨东升, 周博文, 杨波, 李广地. 基于数字孪生技术的新型电力系统数字化[J]. 综合智慧能源, 2024, 46(2): 1-11.
[11]	张心怡, 杨波. 考虑构网型和跟网型变流器的孤岛微电网小信号稳定性分析[J]. 综合智慧能源, 2024, 46(2): 12-18.
[12]	孙娜, 董海鹰, 陈薇, 马虎林. 新型电力系统场景下网侧规模化储能二次调频控制策略[J]. 综合智慧能源, 2024, 46(2): 59-67.
[13]	孔慧超, 王文钟, 雷一, 彭静, 李海波. 园区受端新型电力系统电力电量再平衡方法[J]. 综合智慧能源, 2024, 46(2): 68-74.
[14]	鲍海波, 梁浚杰, 李想. 园区供电系统广义负荷需求响应建模与分析[J]. 综合智慧能源, 2024, 46(1): 11-17.
[15]	蔺家骏, 闫玮丹, 胡俊华, 郑一鸣, 邵先军, 郭炳延. 多模态知识图谱在电力运检中的应用与展望[J]. 综合智慧能源, 2024, 46(1): 65-74.