Matthias A. Bucher, S. Delikaraoglou, K. Heussen, P. Pinson, G. Andersson
{"title":"电力系统柔性的量化研究","authors":"Matthias A. Bucher, S. Delikaraoglou, K. Heussen, P. Pinson, G. Andersson","doi":"10.1109/PTC.2015.7232514","DOIUrl":null,"url":null,"abstract":"Large scale integration of fluctuating and non-dispatchable generation and variable transmission patterns induce high uncertainty in power system operation. In turn, transmission system operators (TSOs) need explicit information about available flexibility to maintain a desired reliability level at a reasonable cost. In this paper, locational flexibility is defined and a unified framework to compare it against forecast uncertainty is introduced. Both metrics are expressed in terms of ramping rate, power and energy and consider the network constraints. This framework is integrated into the operational practice of the TSO using a robust reserve procurement strategy which guarantees optimal system response in the worst-case realization of the uncertainty. The proposed procurement model is applied on an illustrative three-node system and a case study focuses on the available locational flexibility in a larger power system.","PeriodicalId":193448,"journal":{"name":"2015 IEEE Eindhoven PowerTech","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":"{\"title\":\"On quantification of flexibility in power systems\",\"authors\":\"Matthias A. Bucher, S. Delikaraoglou, K. Heussen, P. Pinson, G. Andersson\",\"doi\":\"10.1109/PTC.2015.7232514\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Large scale integration of fluctuating and non-dispatchable generation and variable transmission patterns induce high uncertainty in power system operation. In turn, transmission system operators (TSOs) need explicit information about available flexibility to maintain a desired reliability level at a reasonable cost. In this paper, locational flexibility is defined and a unified framework to compare it against forecast uncertainty is introduced. Both metrics are expressed in terms of ramping rate, power and energy and consider the network constraints. This framework is integrated into the operational practice of the TSO using a robust reserve procurement strategy which guarantees optimal system response in the worst-case realization of the uncertainty. The proposed procurement model is applied on an illustrative three-node system and a case study focuses on the available locational flexibility in a larger power system.\",\"PeriodicalId\":193448,\"journal\":{\"name\":\"2015 IEEE Eindhoven PowerTech\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"40\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Eindhoven PowerTech\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PTC.2015.7232514\",\"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.2015.7232514","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Large scale integration of fluctuating and non-dispatchable generation and variable transmission patterns induce high uncertainty in power system operation. In turn, transmission system operators (TSOs) need explicit information about available flexibility to maintain a desired reliability level at a reasonable cost. In this paper, locational flexibility is defined and a unified framework to compare it against forecast uncertainty is introduced. Both metrics are expressed in terms of ramping rate, power and energy and consider the network constraints. This framework is integrated into the operational practice of the TSO using a robust reserve procurement strategy which guarantees optimal system response in the worst-case realization of the uncertainty. The proposed procurement model is applied on an illustrative three-node system and a case study focuses on the available locational flexibility in a larger power system.