{"title":"Distributed generation long-term planning in smart distribution systems considering daily optimal operation","authors":"H. Sindi, M. Shaaban, E. El-Saadany","doi":"10.1109/SEGE.2015.7324604","DOIUrl":null,"url":null,"abstract":"An algorithm to maximize distributed generation (DG) hosting capacity in a system while lowering overall system cost is proposed in this paper. This algorithm considers several realistic aspects of long-term DG planning, such as cost effective design of feeder reinforcement. It allocates DGs and provides the type, size, location, and year of installation. Both dispatchable and non-dispatchable DG technologies are used. The complexity of the problem necessitates modeling the problem as mixed integer nonlinear programming. This is performed while considering the daily optimal operation of the allocated DGs. A case study of a test system was conducted over a planning period of 20 years, with every year consisting of eight-day patterns and each day having 24 varying hours.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEGE.2015.7324604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
An algorithm to maximize distributed generation (DG) hosting capacity in a system while lowering overall system cost is proposed in this paper. This algorithm considers several realistic aspects of long-term DG planning, such as cost effective design of feeder reinforcement. It allocates DGs and provides the type, size, location, and year of installation. Both dispatchable and non-dispatchable DG technologies are used. The complexity of the problem necessitates modeling the problem as mixed integer nonlinear programming. This is performed while considering the daily optimal operation of the allocated DGs. A case study of a test system was conducted over a planning period of 20 years, with every year consisting of eight-day patterns and each day having 24 varying hours.