Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/100628
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dc.contributorDepartment of Electrical and Electronic Engineering-
dc.creatorXia, Sen_US
dc.creatorLuo, Xen_US
dc.creatorChan, KWen_US
dc.creatorZhou, Men_US
dc.creatorLi, Gen_US
dc.date.accessioned2023-08-11T03:11:15Z-
dc.date.available2023-08-11T03:11:15Z-
dc.identifier.issn1949-3029en_US
dc.identifier.urihttp://hdl.handle.net/10397/100628-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication S. Xia, X. Luo, K. W. Chan, M. Zhou and G. Li, "Probabilistic Transient Stability Constrained Optimal Power Flow for Power Systems With Multiple Correlated Uncertain Wind Generations," in IEEE Transactions on Sustainable Energy, vol. 7, no. 3, pp. 1133-1144, July 2016 is available at https://doi.org/10.1109/TSTE.2016.2520481.en_US
dc.subjectCorrelated wind poweren_US
dc.subjectImproved group search optimizationen_US
dc.subjectOptimal power flowen_US
dc.subjectPoint estimated methoden_US
dc.subjectProbabilistic transient stabilityen_US
dc.subjectUncertaintiesen_US
dc.titleProbabilistic transient stability constrained optimal power flow for power systems with multiple correlated uncertain wind generationsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1133en_US
dc.identifier.epage1144en_US
dc.identifier.volume7en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1109/TSTE.2016.2520481en_US
dcterms.abstractThis paper proposes a novel probabilistic transient stability constrained optimal power flow (P-TSCOPF) model to simultaneously consider uncertainties and transient stability for power system preventive control. While detailed wind generator model with rotor flux magnitude and angle control strategy is used to describe the dynamic behaviors of wind generators, uncertain factors with correlations, such as probabilistic load injections, stochastic fault clearing time, and multiple correlated wind generations, are also included to form a representative P-TSCOPF model. A new GSO-PE approach, consisting of an improved group search optimization (GSO) and 2m + 1 point estimated (PE) method with Cholesky decomposition, is then designed to effectively solve this challenging P-TSCOPF problem. The proposed P-TSCOPF model and GSO-PE solution approach have been thoroughly tested on a modified New England 39-bus system with correlated uncertain wind generations. Comparative results with Monte Carlo (MC) simulations have confirmed the validity of the P-TSCOPF model and demonstrated the effectiveness of GSO-PE method.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on sustainable energy, July 2016, v. 7, no. 3, p. 1133-1144en_US
dcterms.isPartOfIEEE transactions on sustainable energyen_US
dcterms.issued2016-07-
dc.identifier.scopus2-s2.0-84979468569-
dc.identifier.eissn1949-3037en_US
dc.description.validate202308 bckw-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEE-0674-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe Hong Kong Polytechnic University; National Basic Research Program of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6662740-
dc.description.oaCategoryGreen (AAM)en_US
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