电力系统自动化2024，Vol.48Issue(4)：111-122,12.DOI:10.7500/AEPS20230313004
多品种电力市场交易下负荷聚合商投标策略及市场均衡分析
Bidding Strategy of Load Aggregators and Market Equilibrium Analysis for Multi-variety Electricity Market Trading
摘要
Abstract
The construction of the new power system in China is facing the challenge of a shortage of flexible resources,and it is urgent to exert the adjustment ability of load side.As the mutual interaction between the power grid and load becomes more frequent,more load aggregators participate in market transactions by integrating jurisdictional flexible resources,resulting in the break of the market equilibrium dominated by the power generation side in the past.In order to study the game strategy of multi-agent load aggregators,a bi-level bidding model of load aggregators under energy-reserve electricity market is constructed,and multiple scenarios are introduced to describe the influence of bidding uncertainty of non-decision makers on the market equilibrium.The multiple bi-level models are transformed into an equilibrium problem with equilibrium constraints(EPEC)model by strong stationary method(SSM),and linearization methods such as big-M method and binary expansion approach are used for linearization.Results of the case validate the validity and effectiveness of the model and solving algorithm,demonstrating that the EPEC model based optimal bidding strategy of load aggregators is more in line with the actual market rules,which is helpful to optimize the load curve of the system and alleviate the tension between the supply and demand of flexible resources.关键词
负荷聚合商/多品种电力交易/投标策略/双层优化/市场均衡/强平稳算法Key words
load aggregator/multi-variety electricity trading/bidding strategy/bi-level optimization/market equilibrium/strong stationary method(SSM)引用本文复制引用
王鹏,贺焕然,伏凌霄,王雁凌,戴尧..多品种电力市场交易下负荷聚合商投标策略及市场均衡分析[J].电力系统自动化,2024,48(4):111-122,12.基金项目
内蒙古电力(集团)有限责任公司咨询项目(YXYY-YBHT-2023-DFJSZX-0708-0060) （集团）
国家自然科学基金青年基金资助项目(51907063). This work is supported by Consultation Key Project of Inner Mongolia Power(Group)Co.,Ltd.(No.YXYY-YBHT-2023-DFJSZX-0708-0060)and National Natural Science Foundation of China(No.51907063). （51907063）
