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Intra-day unit commitment for wind farm using model predictive control method

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dc.contributor.authorGui, Yonghao-
dc.contributor.authorKim, Chung Hun-
dc.contributor.authorChung, Chung Choo-
dc.contributor.authorKang, Yong-Cheol-
dc.date.accessioned2022-07-16T07:31:02Z-
dc.date.available2022-07-16T07:31:02Z-
dc.date.created2021-05-13-
dc.date.issued2013-11-
dc.identifier.issn1944-9925-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/161503-
dc.description.abstractThis paper presents centralized control for a wind farm using model predictive control (MPC) method. In order to solve intra-day unit commitment (UC) problem, the UC problem is solved by using the MPC method with short-term wind power forecasting. We introduce a new dynamics model for the UC with some constraints to utilize the benefits of the MPC method. The objective function considering the operation and maintenance costs is formulated by adding a new variable in order to average the operating time of each wind turbine (WT) within the whole time. The proposed method could solve the UC problems on-line using the prediction time horizon that could be selected flexibly considering time horizon based on wind power forecasting errors. From the simulation study using 10 WTs, we observed that the proposed dynamics model of UC effectively provided the optimal solution to each scenario. Numerical study will validate that the proposed method can be applied to solving the UC problem of a large scale wind farm by aggregating WTs.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE-
dc.titleIntra-day unit commitment for wind farm using model predictive control method-
dc.typeArticle-
dc.contributor.affiliatedAuthorChung, Chung Choo-
dc.identifier.doi10.1109/PESMG.2013.6672813-
dc.identifier.scopusid2-s2.0-84893156206-
dc.identifier.bibliographicCitationIEEE Power and Energy Society General Meeting, pp.1 - 5-
dc.relation.isPartOfIEEE Power and Energy Society General Meeting-
dc.citation.titleIEEE Power and Energy Society General Meeting-
dc.citation.startPage1-
dc.citation.endPage5-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusCentralized control-
dc.subject.keywordPlusMPC-
dc.subject.keywordPlusOperation and maintenance-
dc.subject.keywordPlusPrediction time horizon-
dc.subject.keywordPlusShort-term wind power forecasting-
dc.subject.keywordPlusunit commitment-
dc.subject.keywordPlusUnit commitment problem-
dc.subject.keywordPlusWind farm-
dc.subject.keywordPlusElectric utilities-
dc.subject.keywordPlusIntegrated control-
dc.subject.keywordPlusModel predictive control-
dc.subject.keywordPlusNumerical methods-
dc.subject.keywordPlusPredictive control systems-
dc.subject.keywordPlusWeather forecasting-
dc.subject.keywordPlusWind power-
dc.subject.keywordPlusWind turbines-
dc.subject.keywordPlusProblem solving-
dc.subject.keywordAuthorCentralized control-
dc.subject.keywordAuthorMPC-
dc.subject.keywordAuthorunit commitment-
dc.subject.keywordAuthorwind farm-
dc.subject.keywordAuthorwind turbine-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/6672813-
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