S. Bracco, M. Brignone, F. Delfino, F. Pampararo, M. Rossi, G. Ferro, M. Robba
{"title":"An Optimization Model for Polygeneration Microgrids with Renewables, Electrical and Thermal Storage: Application to the Savona Campus","authors":"S. Bracco, M. Brignone, F. Delfino, F. Pampararo, M. Rossi, G. Ferro, M. Robba","doi":"10.1109/EEEIC.2018.8493965","DOIUrl":null,"url":null,"abstract":"In this paper, an optimization model for polygeneration microgrids is presented. In particular, the system is characterized by trigeneration plants, renewables, district heating, thermal and electrical storage systems and flexible loads. The control variables are represented by the schedule of the power plants and of the deferrable demand, while the state variables are the energy stored in batteries and water tanks. The objective function minimizes operational costs in the day-ahead. The model is applied to the University of Genoa research infrastructures at Savona Campus, characterized by a Smart Polygeneration Microgrid and a Smart Energy Building.","PeriodicalId":6563,"journal":{"name":"2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)","volume":"74 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEEIC.2018.8493965","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, an optimization model for polygeneration microgrids is presented. In particular, the system is characterized by trigeneration plants, renewables, district heating, thermal and electrical storage systems and flexible loads. The control variables are represented by the schedule of the power plants and of the deferrable demand, while the state variables are the energy stored in batteries and water tanks. The objective function minimizes operational costs in the day-ahead. The model is applied to the University of Genoa research infrastructures at Savona Campus, characterized by a Smart Polygeneration Microgrid and a Smart Energy Building.