{"title":"A risk-aware coordinated trading strategy for load aggregators with energy storage systems in the electricity spot market and demand response market","authors":"Ziyang Xiang;Chunyi Huang;Kangping Li;Chengmin Wang;Pierluigi Siano","doi":"10.23919/IEN.2025.0004","DOIUrl":null,"url":null,"abstract":"The demand response (DR) market, as a vital complement to the electricity spot market, plays a key role in evoking user-side regulation capability to mitigate system-level supply-demand imbalances during extreme events. While the DR market offers the load aggregator (LA) additional profitable opportunities beyond the electricity spot market, it also introduces new trading risks due to the significant uncertainty in users' behaviors. Dispatching energy storage systems (ESSs) is an effective means to enhance the risk management capabilities of LAs; however, coordinating ESS operations with dual-market trading strategies remains an urgent challenge. To this end, this paper proposes a novel systematic risk-aware coordinated trading model for the LA in concurrently participating in the day-ahead electricity spot market and DR market, which incorporates the capacity allocation mechanism of ESS based on market clearing rules to jointly formulate bidding and pricing decisions for the dual market. First, the intrinsic coupling characteristics of the LA participating in the dual market are analyzed, and a joint optimization framework for formulating bidding and pricing strategies that integrates ESS facilities is proposed. Second, an uncertain user response model is developed based on price-response mechanisms, and actual market settlement rules accounting for under- and over-responses are employed to calculate trading revenues, where possible revenue losses are quantified via conditional value at risk. Third, by imposing these terms and the capacity allocation mechanism of ESS, the risk-aware stochastic coordinated trading model of the LA is built, where the bidding and pricing strategies in the dual model that trade off risk and profit are derived. The simulation results of a case study validate the effectiveness of the proposed trading strategy in controlling trading risk and improving the trading income of the LA.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 1","pages":"31-42"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10934762","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"iEnergy","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10934762/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The demand response (DR) market, as a vital complement to the electricity spot market, plays a key role in evoking user-side regulation capability to mitigate system-level supply-demand imbalances during extreme events. While the DR market offers the load aggregator (LA) additional profitable opportunities beyond the electricity spot market, it also introduces new trading risks due to the significant uncertainty in users' behaviors. Dispatching energy storage systems (ESSs) is an effective means to enhance the risk management capabilities of LAs; however, coordinating ESS operations with dual-market trading strategies remains an urgent challenge. To this end, this paper proposes a novel systematic risk-aware coordinated trading model for the LA in concurrently participating in the day-ahead electricity spot market and DR market, which incorporates the capacity allocation mechanism of ESS based on market clearing rules to jointly formulate bidding and pricing decisions for the dual market. First, the intrinsic coupling characteristics of the LA participating in the dual market are analyzed, and a joint optimization framework for formulating bidding and pricing strategies that integrates ESS facilities is proposed. Second, an uncertain user response model is developed based on price-response mechanisms, and actual market settlement rules accounting for under- and over-responses are employed to calculate trading revenues, where possible revenue losses are quantified via conditional value at risk. Third, by imposing these terms and the capacity allocation mechanism of ESS, the risk-aware stochastic coordinated trading model of the LA is built, where the bidding and pricing strategies in the dual model that trade off risk and profit are derived. The simulation results of a case study validate the effectiveness of the proposed trading strategy in controlling trading risk and improving the trading income of the LA.