{"title":"多目标优化在布达佩斯住宅供热系统中的应用","authors":"Endre Borcsok, Agnes Gersc, J. Fülöp","doi":"10.1109/SACI.2018.8440986","DOIUrl":null,"url":null,"abstract":"A multiobjective optimization methodology is presented in the context of the optimal heat supply porfolio of Budapest. The techno-economic assessment is complemented by monetizing the environmental impacts and the influence of the technology choices on human health. Among the technology options, also long-distance heating from Paks Nuclear District Heating has been considered and evaluated. The methodology is based on monthly heat demand profiles while distinguishing between three typological groups of buildings and optimizing the set and installed capacity of heating technologies for each of these groups. Our assessment shows that the resulting optimal heat supply portfolio is influenced both by the factors involved in the optimization and the types of buildings.","PeriodicalId":126087,"journal":{"name":"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Applying Multiobjective Optimization for the Heat Supply in the Residential Sector in Budapest\",\"authors\":\"Endre Borcsok, Agnes Gersc, J. Fülöp\",\"doi\":\"10.1109/SACI.2018.8440986\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multiobjective optimization methodology is presented in the context of the optimal heat supply porfolio of Budapest. The techno-economic assessment is complemented by monetizing the environmental impacts and the influence of the technology choices on human health. Among the technology options, also long-distance heating from Paks Nuclear District Heating has been considered and evaluated. The methodology is based on monthly heat demand profiles while distinguishing between three typological groups of buildings and optimizing the set and installed capacity of heating technologies for each of these groups. Our assessment shows that the resulting optimal heat supply portfolio is influenced both by the factors involved in the optimization and the types of buildings.\",\"PeriodicalId\":126087,\"journal\":{\"name\":\"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2018.8440986\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2018.8440986","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applying Multiobjective Optimization for the Heat Supply in the Residential Sector in Budapest
A multiobjective optimization methodology is presented in the context of the optimal heat supply porfolio of Budapest. The techno-economic assessment is complemented by monetizing the environmental impacts and the influence of the technology choices on human health. Among the technology options, also long-distance heating from Paks Nuclear District Heating has been considered and evaluated. The methodology is based on monthly heat demand profiles while distinguishing between three typological groups of buildings and optimizing the set and installed capacity of heating technologies for each of these groups. Our assessment shows that the resulting optimal heat supply portfolio is influenced both by the factors involved in the optimization and the types of buildings.