{"title":"优化匈牙利能源结构中可再生能源的使用","authors":"Endre Börcsök, Ágnes Gerse, J. Fülöp","doi":"10.1109/SAMI.2019.8782774","DOIUrl":null,"url":null,"abstract":"This paper reports short-term energy scenarios for the heat and electricity generation in Hungary, considering the recent developments in the overall European and national energy policy framework promoting the use of energy from renewable energy sources. Focusing on the heating and electricity sectors, a methodology for portfolio optimization has been developed in order to identify the optimal energy mix in terms of technology alternatives and energy sources. As a base case, a pure economic assessment was done considering the investment costs, the net present values and the operation and maintenance (O&M) costs. The optimization was extended by involving additional factors in the next steps, adding carbon prices and the external costs of the environmental and human health (physiological) impacts to the model. An aggregate approach is applied to reduce complexity; national aggregation was chosen for the electricity sector while building typological groups and local geographical entities were defined for the heating sector. The level of saturation of different technology alternatives in the market is modeled in the proposed methodology, as well. The mathematical formulation of the optimization problem was given as a non-linear case of the distribution problem.","PeriodicalId":240256,"journal":{"name":"2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimizing the use of renewable energy sources in the energy mix of Hungary\",\"authors\":\"Endre Börcsök, Ágnes Gerse, J. Fülöp\",\"doi\":\"10.1109/SAMI.2019.8782774\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper reports short-term energy scenarios for the heat and electricity generation in Hungary, considering the recent developments in the overall European and national energy policy framework promoting the use of energy from renewable energy sources. Focusing on the heating and electricity sectors, a methodology for portfolio optimization has been developed in order to identify the optimal energy mix in terms of technology alternatives and energy sources. As a base case, a pure economic assessment was done considering the investment costs, the net present values and the operation and maintenance (O&M) costs. The optimization was extended by involving additional factors in the next steps, adding carbon prices and the external costs of the environmental and human health (physiological) impacts to the model. An aggregate approach is applied to reduce complexity; national aggregation was chosen for the electricity sector while building typological groups and local geographical entities were defined for the heating sector. The level of saturation of different technology alternatives in the market is modeled in the proposed methodology, as well. The mathematical formulation of the optimization problem was given as a non-linear case of the distribution problem.\",\"PeriodicalId\":240256,\"journal\":{\"name\":\"2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2019.8782774\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2019.8782774","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing the use of renewable energy sources in the energy mix of Hungary
This paper reports short-term energy scenarios for the heat and electricity generation in Hungary, considering the recent developments in the overall European and national energy policy framework promoting the use of energy from renewable energy sources. Focusing on the heating and electricity sectors, a methodology for portfolio optimization has been developed in order to identify the optimal energy mix in terms of technology alternatives and energy sources. As a base case, a pure economic assessment was done considering the investment costs, the net present values and the operation and maintenance (O&M) costs. The optimization was extended by involving additional factors in the next steps, adding carbon prices and the external costs of the environmental and human health (physiological) impacts to the model. An aggregate approach is applied to reduce complexity; national aggregation was chosen for the electricity sector while building typological groups and local geographical entities were defined for the heating sector. The level of saturation of different technology alternatives in the market is modeled in the proposed methodology, as well. The mathematical formulation of the optimization problem was given as a non-linear case of the distribution problem.