{"title":"考虑需求响应和电池储能系统参与的多结算电力市场设计","authors":"Anshul Goyal;Kankar Bhattacharya","doi":"10.1109/TEMPR.2024.3350510","DOIUrl":null,"url":null,"abstract":"This article presents a novel framework with new mathematical models that integrate Demand Response (DR) and Battery Energy Storage Systems (BESSs) simultaneously in a Locational Marginal Price (LMP)-based Multi-Settlement Market (MSM), i.e. a coordinated Day-Ahead Market (DAM) and Real-Time Market (RTM). A new set of generator ramping constraints, developed from the DAM settlement, and referred to as Day-Ahead Load-Following (DALF) Ramp, are included in the RTM auction model. The performance of the mathematical models are tested on the IEEE 24-bus Reliability Test System (RTS) by carrying out various case studies, scenarios, uncertainty and sensitivity analyses. Effect of DR and BESS characteristics such as level of participation, initial state-of-charge (SOC), discharge rate, etc. on market settlement is examined. The results demonstrate the merits of the proposed framework, and the impact of the DALF Ramp, DR and BESS inclusion in the MSM auction models on marginal prices, market settlement and system operation. It is noted that the system with DR and BESS in the MSM hedges real-time prices and effectively supports system operation during uncertain events such as line and generators outages, changes in demand or in generation from renewables.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 2","pages":"226-239"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of Multi-Settlement Electricity Markets Considering Demand Response and Battery Energy Storage Systems Participation\",\"authors\":\"Anshul Goyal;Kankar Bhattacharya\",\"doi\":\"10.1109/TEMPR.2024.3350510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a novel framework with new mathematical models that integrate Demand Response (DR) and Battery Energy Storage Systems (BESSs) simultaneously in a Locational Marginal Price (LMP)-based Multi-Settlement Market (MSM), i.e. a coordinated Day-Ahead Market (DAM) and Real-Time Market (RTM). A new set of generator ramping constraints, developed from the DAM settlement, and referred to as Day-Ahead Load-Following (DALF) Ramp, are included in the RTM auction model. The performance of the mathematical models are tested on the IEEE 24-bus Reliability Test System (RTS) by carrying out various case studies, scenarios, uncertainty and sensitivity analyses. Effect of DR and BESS characteristics such as level of participation, initial state-of-charge (SOC), discharge rate, etc. on market settlement is examined. The results demonstrate the merits of the proposed framework, and the impact of the DALF Ramp, DR and BESS inclusion in the MSM auction models on marginal prices, market settlement and system operation. It is noted that the system with DR and BESS in the MSM hedges real-time prices and effectively supports system operation during uncertain events such as line and generators outages, changes in demand or in generation from renewables.\",\"PeriodicalId\":100639,\"journal\":{\"name\":\"IEEE Transactions on Energy Markets, Policy and Regulation\",\"volume\":\"2 2\",\"pages\":\"226-239\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Energy Markets, Policy and Regulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10381872/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Energy Markets, Policy and Regulation","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10381872/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本文提出了一种新的数学模型框架,将需求响应(DR)和电池储能系统(BESS)同时纳入基于本地边际价格(LMP)的多结算市场(MSM),即协调的日前市场(DAM)和实时市场(RTM)。RTM 拍卖模型中包含了一组新的发电机斜坡约束,该约束由 DAM 结算发展而来,被称为 "日前负荷跟随(DALF)斜坡"。通过开展各种案例研究、情景分析、不确定性和敏感性分析,在 IEEE 24 总线可靠性测试系统(RTS)上测试了数学模型的性能。研究了 DR 和 BESS 特性(如参与水平、初始充电状态 (SOC)、放电率等)对市场结算的影响。结果表明了所建议框架的优点,以及将 DALF Ramp、DR 和 BESS 纳入 MSM 拍卖模型对边际价格、市场结算和系统运行的影响。结果表明,在 MSM 中包含 DR 和 BESS 的系统可以对冲实时价格,并在线路和发电机停运、需求变化或可再生能源发电量变化等不确定事件发生时有效支持系统运行。
Design of Multi-Settlement Electricity Markets Considering Demand Response and Battery Energy Storage Systems Participation
This article presents a novel framework with new mathematical models that integrate Demand Response (DR) and Battery Energy Storage Systems (BESSs) simultaneously in a Locational Marginal Price (LMP)-based Multi-Settlement Market (MSM), i.e. a coordinated Day-Ahead Market (DAM) and Real-Time Market (RTM). A new set of generator ramping constraints, developed from the DAM settlement, and referred to as Day-Ahead Load-Following (DALF) Ramp, are included in the RTM auction model. The performance of the mathematical models are tested on the IEEE 24-bus Reliability Test System (RTS) by carrying out various case studies, scenarios, uncertainty and sensitivity analyses. Effect of DR and BESS characteristics such as level of participation, initial state-of-charge (SOC), discharge rate, etc. on market settlement is examined. The results demonstrate the merits of the proposed framework, and the impact of the DALF Ramp, DR and BESS inclusion in the MSM auction models on marginal prices, market settlement and system operation. It is noted that the system with DR and BESS in the MSM hedges real-time prices and effectively supports system operation during uncertain events such as line and generators outages, changes in demand or in generation from renewables.