A. Shapovalov, Christopher Spieker, C. Rehtanz, Torben Engelmeyer
{"title":"基于预测的网络重构算法","authors":"A. Shapovalov, Christopher Spieker, C. Rehtanz, Torben Engelmeyer","doi":"10.1109/PSCC.2014.7038419","DOIUrl":null,"url":null,"abstract":"This paper proposes a forecast-based network reconfiguration algorithm and its application to a distribution network. Altering loads and generation may cause overloads while operating the network at the static topology configuration. By using forecast-based nodal power time series a suitable switching strategy is generated. In a second step the amount of switching actions is to be reduced. The generated action plan may be used as a guide for network operation in the course of the day.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"238 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Forecast-based network reconfiguration algorithm\",\"authors\":\"A. Shapovalov, Christopher Spieker, C. Rehtanz, Torben Engelmeyer\",\"doi\":\"10.1109/PSCC.2014.7038419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a forecast-based network reconfiguration algorithm and its application to a distribution network. Altering loads and generation may cause overloads while operating the network at the static topology configuration. By using forecast-based nodal power time series a suitable switching strategy is generated. In a second step the amount of switching actions is to be reduced. The generated action plan may be used as a guide for network operation in the course of the day.\",\"PeriodicalId\":155801,\"journal\":{\"name\":\"2014 Power Systems Computation Conference\",\"volume\":\"238 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Power Systems Computation Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PSCC.2014.7038419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Power Systems Computation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PSCC.2014.7038419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper proposes a forecast-based network reconfiguration algorithm and its application to a distribution network. Altering loads and generation may cause overloads while operating the network at the static topology configuration. By using forecast-based nodal power time series a suitable switching strategy is generated. In a second step the amount of switching actions is to be reduced. The generated action plan may be used as a guide for network operation in the course of the day.