Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93431
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dc.contributorDepartment of Electrical Engineeringen_US
dc.creatorLu, Xen_US
dc.creatorChan, KWen_US
dc.creatorXia, Sen_US
dc.creatorZhou, Ben_US
dc.creatorLuo, Xen_US
dc.date.accessioned2022-06-21T08:23:42Z-
dc.date.available2022-06-21T08:23:42Z-
dc.identifier.issn1949-3029en_US
dc.identifier.urihttp://hdl.handle.net/10397/93431-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2018 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 X. Lu, K. W. Chan, S. Xia, B. Zhou and X. Luo, "Security-Constrained Multiperiod Economic Dispatch With Renewable Energy Utilizing Distributionally Robust Optimization," in IEEE Transactions on Sustainable Energy, vol. 10, no. 2, pp. 768-779, April 2019 is available at https://doi.org/10.1109/TSTE.2018.2847419en_US
dc.subjectDistributionally robust optimizationen_US
dc.subjectEconomic dispatchen_US
dc.subjectMulti-perioden_US
dc.subjectRenewable energyen_US
dc.subjectRobust optimizationen_US
dc.subjectTwo-stageen_US
dc.subjectUncertaintyen_US
dc.titleSecurity-constrained multiperiod economic dispatch with renewable energy utilizing distributionally robust optimizationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage768en_US
dc.identifier.epage779en_US
dc.identifier.volume10en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1109/TSTE.2018.2847419en_US
dcterms.abstractThis paper presents a security-constrained multiperiod economic dispatch model (M-SCED) for systems with renewable energy sources (RES). A two-stage framework is adopted to model initial operation plans and recourse actions before and after the uncertainty realization of RES power. For ensuring superior system economic efficiency, distributionally robust optimization (DRO) is utilized to evaluate the expectations of operation costs affected by RES uncertainty. Practical issues, including boundedness of uncertainty and inaccurate information, are considered in modeling uncertainty in DRO. Within the framework of DRO, robust optimization is integrated to enhance system security. Besides, decision variables after the first period in M-SCED are approximated by segregated linear decision rules to achieve computational tractability without substantially degrading the model accuracy. A Constraint Generation algorithm is proposed to solve this problem with comprehensive case studies illustrating the effectiveness of the proposed M-SCED.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on sustainable energy, Apr. 2019, v. 10, no. 2, p. 768-779en_US
dcterms.isPartOfIEEE transactions on sustainable energyen_US
dcterms.issued2019-04-
dc.identifier.scopus2-s2.0-85048534959-
dc.identifier.eissn1949-3037en_US
dc.description.validate202206 bchyen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEE-0241-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe Hong Kong Polytechnic University; Research Studentship RUH5; Beijing Natural Science Foundation; Support Program for the Excellent Talents in Beijing Cityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6845772-
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