{"title":"A linear decision rule approach for robust unit commitment considering wind power generation","authors":"Peng Xiong, P. Jirutitijaroen","doi":"10.1109/PSCC.2014.7038414","DOIUrl":null,"url":null,"abstract":"This paper proposes a robust optimization formulation to solve unit commitment (UC) problems under wind energy uncertainties. Unlike the conventional stochastic programming or chance-constrained methods, this robust approach does not require information on the exact distribution of wind power. Instead, it protects the system against load loss under all possible wind generation scenarios within a straightforward uncertainty set. The level of conservatism of yielded UC decisions can be readily adjusted by the parameters of the uncertainty set. This robust UC is formulated as a two-stage problem, and the linear decision rule technique is applied to approximate the recourse decisions, so that the solution is computationally tractable. Case studies based on the IEEE Reliability Test System are conducted to demonstrate the performance of the proposed method. The results show that this method can well manage the uncertainty of wind power in UC decision-making.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Power Systems Computation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PSCC.2014.7038414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
This paper proposes a robust optimization formulation to solve unit commitment (UC) problems under wind energy uncertainties. Unlike the conventional stochastic programming or chance-constrained methods, this robust approach does not require information on the exact distribution of wind power. Instead, it protects the system against load loss under all possible wind generation scenarios within a straightforward uncertainty set. The level of conservatism of yielded UC decisions can be readily adjusted by the parameters of the uncertainty set. This robust UC is formulated as a two-stage problem, and the linear decision rule technique is applied to approximate the recourse decisions, so that the solution is computationally tractable. Case studies based on the IEEE Reliability Test System are conducted to demonstrate the performance of the proposed method. The results show that this method can well manage the uncertainty of wind power in UC decision-making.