{"title":"温控负荷与用户偏好的市场化协调研究","authors":"Sen Li, Wei Zhang, Jianming Lian, K. Kalsi","doi":"10.1109/CDC.2014.7039766","DOIUrl":null,"url":null,"abstract":"This paper presents a market-based control framework to coordinate a group of Thermostatically Controlled Loads (TCL) to achieve system-level objectives with price incentives. The problem is formulated as maximizing the social welfare subject to a feeder power constraint. It allows the coordinator to affect the aggregated power of a group of dynamical systems, and creates an interactive market where the users and the coordinator cooperatively determine the optimal energy allocation and energy price. The optimal pricing strategy is derived, which maximizes social welfare while respecting the feeder power constraint. The bidding strategy is also designed for the coordinator to compute the optimal price based on local device information. Numerical simulations based on realistic price and model data are performed. The simulation results demonstrate that the proposed approach can effectively maximize the social welfare and reduce power congestion at key times.","PeriodicalId":202708,"journal":{"name":"53rd IEEE Conference on Decision and Control","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"On market-based coordination of Thermostatically Controlled Loads with user preference\",\"authors\":\"Sen Li, Wei Zhang, Jianming Lian, K. Kalsi\",\"doi\":\"10.1109/CDC.2014.7039766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a market-based control framework to coordinate a group of Thermostatically Controlled Loads (TCL) to achieve system-level objectives with price incentives. The problem is formulated as maximizing the social welfare subject to a feeder power constraint. It allows the coordinator to affect the aggregated power of a group of dynamical systems, and creates an interactive market where the users and the coordinator cooperatively determine the optimal energy allocation and energy price. The optimal pricing strategy is derived, which maximizes social welfare while respecting the feeder power constraint. The bidding strategy is also designed for the coordinator to compute the optimal price based on local device information. Numerical simulations based on realistic price and model data are performed. The simulation results demonstrate that the proposed approach can effectively maximize the social welfare and reduce power congestion at key times.\",\"PeriodicalId\":202708,\"journal\":{\"name\":\"53rd IEEE Conference on Decision and Control\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"53rd IEEE Conference on Decision and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2014.7039766\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"53rd IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2014.7039766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On market-based coordination of Thermostatically Controlled Loads with user preference
This paper presents a market-based control framework to coordinate a group of Thermostatically Controlled Loads (TCL) to achieve system-level objectives with price incentives. The problem is formulated as maximizing the social welfare subject to a feeder power constraint. It allows the coordinator to affect the aggregated power of a group of dynamical systems, and creates an interactive market where the users and the coordinator cooperatively determine the optimal energy allocation and energy price. The optimal pricing strategy is derived, which maximizes social welfare while respecting the feeder power constraint. The bidding strategy is also designed for the coordinator to compute the optimal price based on local device information. Numerical simulations based on realistic price and model data are performed. The simulation results demonstrate that the proposed approach can effectively maximize the social welfare and reduce power congestion at key times.