{"title":"通信限制对柔性传输分布式DCOPF收敛性的影响","authors":"Qianzhi Zhang, M. Sahraei-Ardakani","doi":"10.1109/NAPS.2017.8107274","DOIUrl":null,"url":null,"abstract":"This paper presents a fully-distributed DC optimal power flow (DCOPF) method that incorporates flexible transmission, and studies the impacts of communication limitations on the convergence properties of the proposed method. The distributed DCOPF algorithm iteratively solves the first order optimality conditions at each bus. To converge to the globally optimal solution, some information is communicated to the neighboring buses. While in an ideal case such data should be communicated at each iteration, commutation limitations are an inherent characteristic of real-world implementations. This paper divides the system into different areas, and puts communication constraints between different areas. While the information between buses within the same area is communicated at each iteration, the communication between neighboring areas occurs less frequently. This paper studies the impacts of this constraint on the convergence properties of the presented distributed DCOPF algorithm. Simulation studies on IEEE 118-bus system show that communication constraints affect both the number of iterations needed to reach convergence as well as the dynamics of solution evolution.","PeriodicalId":296428,"journal":{"name":"2017 North American Power Symposium (NAPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Impacts of communication limits on convergence of distributed DCOPF with flexible transmission\",\"authors\":\"Qianzhi Zhang, M. Sahraei-Ardakani\",\"doi\":\"10.1109/NAPS.2017.8107274\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a fully-distributed DC optimal power flow (DCOPF) method that incorporates flexible transmission, and studies the impacts of communication limitations on the convergence properties of the proposed method. The distributed DCOPF algorithm iteratively solves the first order optimality conditions at each bus. To converge to the globally optimal solution, some information is communicated to the neighboring buses. While in an ideal case such data should be communicated at each iteration, commutation limitations are an inherent characteristic of real-world implementations. This paper divides the system into different areas, and puts communication constraints between different areas. While the information between buses within the same area is communicated at each iteration, the communication between neighboring areas occurs less frequently. This paper studies the impacts of this constraint on the convergence properties of the presented distributed DCOPF algorithm. Simulation studies on IEEE 118-bus system show that communication constraints affect both the number of iterations needed to reach convergence as well as the dynamics of solution evolution.\",\"PeriodicalId\":296428,\"journal\":{\"name\":\"2017 North American Power Symposium (NAPS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 North American Power Symposium (NAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAPS.2017.8107274\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS.2017.8107274","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Impacts of communication limits on convergence of distributed DCOPF with flexible transmission
This paper presents a fully-distributed DC optimal power flow (DCOPF) method that incorporates flexible transmission, and studies the impacts of communication limitations on the convergence properties of the proposed method. The distributed DCOPF algorithm iteratively solves the first order optimality conditions at each bus. To converge to the globally optimal solution, some information is communicated to the neighboring buses. While in an ideal case such data should be communicated at each iteration, commutation limitations are an inherent characteristic of real-world implementations. This paper divides the system into different areas, and puts communication constraints between different areas. While the information between buses within the same area is communicated at each iteration, the communication between neighboring areas occurs less frequently. This paper studies the impacts of this constraint on the convergence properties of the presented distributed DCOPF algorithm. Simulation studies on IEEE 118-bus system show that communication constraints affect both the number of iterations needed to reach convergence as well as the dynamics of solution evolution.