Milad Kabirifar, M. Fotuhi‐Firuzabad, M. Moeini‐Aghtaie, Niloofar Pourghaderi
{"title":"结合储能系统和主动网络管理的多级主动配电网综合规划","authors":"Milad Kabirifar, M. Fotuhi‐Firuzabad, M. Moeini‐Aghtaie, Niloofar Pourghaderi","doi":"10.1109/IEPS51250.2020.9263121","DOIUrl":null,"url":null,"abstract":"Active distribution network (ADN) expansion planning by modeling network active management is addressed in this paper. In this regard the expansion of distributed energy resources (DERs) and distribution network assets are jointly planned. In the proposed model active management is applied to efficiently utilize the DERs in the planning problem and alleviated the uncertainties. In this paper energy storage systems (ESSs) as an important DER are utilized in active management framework. To model active management of the network, based on load and renewable energy resources’ behavior, some operating levels are regarded for each planning time stage. The objective is to minimize the net present worth of investment, maintenance and operation costs for all planning stages and operating levels. As the problem is solved the expansion plans of network alternatives including feeders, transformers, and substations as long as DERs including micro turbines, wind turbines and ESSs are extracted. Furthermore, the optimal operations of the network and DERs are obtained through the operating levels. Associated uncertainties are considered using a correlated scenario based approach. The problem is mathematically modeled in the form of mixed integer linear programming (MILP).","PeriodicalId":235261,"journal":{"name":"2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Multistage Active Distribution Network Integrated Planning Incorporating Energy Storage Systems and Active Network Management\",\"authors\":\"Milad Kabirifar, M. Fotuhi‐Firuzabad, M. Moeini‐Aghtaie, Niloofar Pourghaderi\",\"doi\":\"10.1109/IEPS51250.2020.9263121\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Active distribution network (ADN) expansion planning by modeling network active management is addressed in this paper. In this regard the expansion of distributed energy resources (DERs) and distribution network assets are jointly planned. In the proposed model active management is applied to efficiently utilize the DERs in the planning problem and alleviated the uncertainties. In this paper energy storage systems (ESSs) as an important DER are utilized in active management framework. To model active management of the network, based on load and renewable energy resources’ behavior, some operating levels are regarded for each planning time stage. The objective is to minimize the net present worth of investment, maintenance and operation costs for all planning stages and operating levels. As the problem is solved the expansion plans of network alternatives including feeders, transformers, and substations as long as DERs including micro turbines, wind turbines and ESSs are extracted. Furthermore, the optimal operations of the network and DERs are obtained through the operating levels. Associated uncertainties are considered using a correlated scenario based approach. The problem is mathematically modeled in the form of mixed integer linear programming (MILP).\",\"PeriodicalId\":235261,\"journal\":{\"name\":\"2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEPS51250.2020.9263121\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEPS51250.2020.9263121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multistage Active Distribution Network Integrated Planning Incorporating Energy Storage Systems and Active Network Management
Active distribution network (ADN) expansion planning by modeling network active management is addressed in this paper. In this regard the expansion of distributed energy resources (DERs) and distribution network assets are jointly planned. In the proposed model active management is applied to efficiently utilize the DERs in the planning problem and alleviated the uncertainties. In this paper energy storage systems (ESSs) as an important DER are utilized in active management framework. To model active management of the network, based on load and renewable energy resources’ behavior, some operating levels are regarded for each planning time stage. The objective is to minimize the net present worth of investment, maintenance and operation costs for all planning stages and operating levels. As the problem is solved the expansion plans of network alternatives including feeders, transformers, and substations as long as DERs including micro turbines, wind turbines and ESSs are extracted. Furthermore, the optimal operations of the network and DERs are obtained through the operating levels. Associated uncertainties are considered using a correlated scenario based approach. The problem is mathematically modeled in the form of mixed integer linear programming (MILP).