多元零售市场环境下电力聚合商有功-无功协同优化竞标策略OA北大核心CSTPCD
Active and Reactive Power Collaborative Bidding Strategy for the Power Aggregator in Multiple Categories of Retail Markets
随着电力体制改革推进和电力市场发展,由多类资源构成的电力零售商参与到零售市场的交易机制及竞价投标策略亟待完善.鉴于此,兼顾零售市场运营者和电力聚合商的利益诉求,提出了一种基于双层优化的零售市场环境下电力聚合商的有功-无功协同竞标模型.顶层以电力聚合商利益最大化为目标,考虑多类可控资源特征,制定合理的电力聚合商报量报价方案;底层以零售市场运营者总成本最低为目标,考虑配电网络拓扑结构及潮流安全,获取零售市场有功-无功出清结果.利用实际案例系统验证所提策略有效性.仿真结果表明,该模型能够有效实现零售市场和聚合商运营利益的趋同.同时,与传统仅考虑有功电量的竞标方法相比,该方法在提升系统运营效益方面展现出明显优势,对零售市场运营模式和电力聚合商竞标策略具有重要的指导价值.
With the promotion of power system reforms and development of the power market,the transaction mechanism and bidding strategies of retailers in the retail power market composed of various types of resources needs investigation.Considering this,a bi-level optimization-based active and reactive power collaborative bidding model for power retailers in the retail market environment is proposed.This model considers the respective interests of the retail market operators and power retailers and also the secure and economic operation constraints of power systems.At the upper level,the power retailer aims to develop an optimal bidding strategy to maximize the operational benefits by considering various controllable resources.At the lower level,the market owner conducts the retail market-clearing process to minimize the overall system cost by considering the network topology and power flow security.The simulation results,validated through real-world case studies,show that the model successfully aligns with the operational goals of both the retail market and the aggregators.Unlike traditional bidding methods that focus solely on the active power,this approach significantly improves the operational efficiency of the system.These findings offer important insights into the development of retail market operation models and bidding strategies for power aggregators.
孙勇;仪忠凯;李宝聚;时雨;徐英
国网吉林省电力有限公司经济技术研究院,长春市 130021哈尔滨工业大学电气工程及自动化学院,哈尔滨市 150016
动力与电气工程
电力聚合商零售市场双层优化竞标策略
power aggregatorretail marketbi-level optimizationbidding strategy
《电力建设》 2024 (010)
146-157 / 12
This work is supported by National Key R&D Program of China(No.2022YFB2404000)and Science and Technology Projects of the State Grid(No.SGJLJYOOGPJS2300038). 国家重点研发计划资助项目(2022YFB2404000);国家电网公司科技项目(SGJLJYOOGPJS2300038)
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