Andrej Trpovski, Prabal Banerjee, Yan Xu, T. Hamacher
{"title":"A Hybrid Optimization Method for Distribution System Expansion Planning with Lithium-ion Battery Energy Storage Systems","authors":"Andrej Trpovski, Prabal Banerjee, Yan Xu, T. Hamacher","doi":"10.1109/iSPEC50848.2020.9351208","DOIUrl":null,"url":null,"abstract":"The accelerating trend of mobility electrification and the constantly increasing accessibility of distributed energy resources (DERs) play an important role in the changing landscape of the modern power system. To maintain the reliability and continuity of supply under the newly encountered EV charging demand, it is a necessity for the planning engineers to use economically viable planning strategies. Traditionally, the expansion of the distribution system, is accomplished using additional lines, cables, transformers, switchgear, or substations. Modern expansion planning is further advanced to consider widespread use of centralized and/or distributed energy storage systems due to their cost competitiveness. In this paper, a robust distribution system expansion planning approach for a combined installation of new lines and energy storage systems is proposed. A hybrid optimization method using a meta-heuristic Genetic Algorithm (GA) and a mixed integer quadratically constrained program (MIQCP) is defined. The solution encompasses a cost-effective line expansion strategy combined with the placement of new energy storage systems and their optimal sizing. The proposed model is tested on a modified 45 bus case study of a Singaporean synthetic grid model. The results are shown and analyzed to conclude the benefits of using energy storage systems as an additional strategy in the expansion planning approach.","PeriodicalId":403879,"journal":{"name":"2020 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Sustainable Power and Energy Conference (iSPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iSPEC50848.2020.9351208","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
The accelerating trend of mobility electrification and the constantly increasing accessibility of distributed energy resources (DERs) play an important role in the changing landscape of the modern power system. To maintain the reliability and continuity of supply under the newly encountered EV charging demand, it is a necessity for the planning engineers to use economically viable planning strategies. Traditionally, the expansion of the distribution system, is accomplished using additional lines, cables, transformers, switchgear, or substations. Modern expansion planning is further advanced to consider widespread use of centralized and/or distributed energy storage systems due to their cost competitiveness. In this paper, a robust distribution system expansion planning approach for a combined installation of new lines and energy storage systems is proposed. A hybrid optimization method using a meta-heuristic Genetic Algorithm (GA) and a mixed integer quadratically constrained program (MIQCP) is defined. The solution encompasses a cost-effective line expansion strategy combined with the placement of new energy storage systems and their optimal sizing. The proposed model is tested on a modified 45 bus case study of a Singaporean synthetic grid model. The results are shown and analyzed to conclude the benefits of using energy storage systems as an additional strategy in the expansion planning approach.