{"title":"Distributed Optimal Active Power Control of a Wind Farm based on Fast ADMM","authors":"Mingzhe Han, Haoran Zhao, Zhan’ao Lv, L. Niu","doi":"10.1109/APPEEC45492.2019.8994815","DOIUrl":null,"url":null,"abstract":"This paper presents a distributed method using the Fast Alternating Direction Method of Multipliers (Fast ADMM) for wind farm optimal active power control. The optimization problem is formulated as a quadratic programming problem by using piece-wise affine wind turbine (WT) model through Model Predictive Control (MPC). With the Fast ADMM, the MPC problem can be solved in a decentralized way with superior convergence properties. The calculation burden of the central controller is reduced by a small number of decentralized iterations. A wind farm was used as the test system, which consists of twelve WTs. Case studies were conducted and analyzed, which verifies the proposed method.","PeriodicalId":241317,"journal":{"name":"2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APPEEC45492.2019.8994815","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents a distributed method using the Fast Alternating Direction Method of Multipliers (Fast ADMM) for wind farm optimal active power control. The optimization problem is formulated as a quadratic programming problem by using piece-wise affine wind turbine (WT) model through Model Predictive Control (MPC). With the Fast ADMM, the MPC problem can be solved in a decentralized way with superior convergence properties. The calculation burden of the central controller is reduced by a small number of decentralized iterations. A wind farm was used as the test system, which consists of twelve WTs. Case studies were conducted and analyzed, which verifies the proposed method.