{"title":"Central model predictive control of a group of domestic heat pumps case study for a small district","authors":"R. V. Leeuwen, J. Fink, G. Smit","doi":"10.5220/0005434301360147","DOIUrl":null,"url":null,"abstract":"In this paper we investigate optimal control of a group of heat pumps. Each heat pump provides space heating and domestic hot water to a single household. Besides a heat pump, each house has a buffer for domestic hot water and a floor heating system for space heating. The paper describes models and algorithms used for the prediction and planning steps in order to obtain a planning for the heat pumps. The optimization algorithm minimizes the maximum peak electricity demand of the district. Simulated results demonstrate the resulting aggregated electricity demand, the obtained thermal comfort and the state of charge of the domestic hot water storage for an example house. Our results show that a model predictive control outperforms conventional control of individual heat pumps based on feedback control principles.","PeriodicalId":408526,"journal":{"name":"2015 International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Smart Cities and Green ICT Systems (SMARTGREENS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005434301360147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
In this paper we investigate optimal control of a group of heat pumps. Each heat pump provides space heating and domestic hot water to a single household. Besides a heat pump, each house has a buffer for domestic hot water and a floor heating system for space heating. The paper describes models and algorithms used for the prediction and planning steps in order to obtain a planning for the heat pumps. The optimization algorithm minimizes the maximum peak electricity demand of the district. Simulated results demonstrate the resulting aggregated electricity demand, the obtained thermal comfort and the state of charge of the domestic hot water storage for an example house. Our results show that a model predictive control outperforms conventional control of individual heat pumps based on feedback control principles.