{"title":"分布式可再生能源高渗透配电网的智能日前调度","authors":"B. Swaminathan, V. Debusschere, R. Caire","doi":"10.1109/PTC.2015.7232718","DOIUrl":null,"url":null,"abstract":"In order to help Distribution System Operators (DSO) effectively manage their distribution networks with a high penetration of Distributed Renewable Energy Sources (DRES), a new generation of tools is needed. These tools should help them manage their networks in a proactive way, be it short-term or long-term. This work proposes a day-ahead scheduling algorithm that takes into account forecasts of DRES generation and loads in a medium voltage (MV) distribution network, and intelligently utilizes flexibilities available in it, to provide an optimal day-ahead schedule. This schedule, depending on the accuracy of the forecasts, will provide a means for DSOs to manage their network with the lowest short-term operating expenditures. This proposed algorithm is validated on two test grids and the results obtained for typical conditions are shown.","PeriodicalId":193448,"journal":{"name":"2015 IEEE Eindhoven PowerTech","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligent day-ahead scheduling for distribution networks with high penetration of Distributed Renewable Energy Sources\",\"authors\":\"B. Swaminathan, V. Debusschere, R. Caire\",\"doi\":\"10.1109/PTC.2015.7232718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to help Distribution System Operators (DSO) effectively manage their distribution networks with a high penetration of Distributed Renewable Energy Sources (DRES), a new generation of tools is needed. These tools should help them manage their networks in a proactive way, be it short-term or long-term. This work proposes a day-ahead scheduling algorithm that takes into account forecasts of DRES generation and loads in a medium voltage (MV) distribution network, and intelligently utilizes flexibilities available in it, to provide an optimal day-ahead schedule. This schedule, depending on the accuracy of the forecasts, will provide a means for DSOs to manage their network with the lowest short-term operating expenditures. This proposed algorithm is validated on two test grids and the results obtained for typical conditions are shown.\",\"PeriodicalId\":193448,\"journal\":{\"name\":\"2015 IEEE Eindhoven PowerTech\",\"volume\":\"101 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Eindhoven PowerTech\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PTC.2015.7232718\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Eindhoven PowerTech","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PTC.2015.7232718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent day-ahead scheduling for distribution networks with high penetration of Distributed Renewable Energy Sources
In order to help Distribution System Operators (DSO) effectively manage their distribution networks with a high penetration of Distributed Renewable Energy Sources (DRES), a new generation of tools is needed. These tools should help them manage their networks in a proactive way, be it short-term or long-term. This work proposes a day-ahead scheduling algorithm that takes into account forecasts of DRES generation and loads in a medium voltage (MV) distribution network, and intelligently utilizes flexibilities available in it, to provide an optimal day-ahead schedule. This schedule, depending on the accuracy of the forecasts, will provide a means for DSOs to manage their network with the lowest short-term operating expenditures. This proposed algorithm is validated on two test grids and the results obtained for typical conditions are shown.