Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/100538
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dc.contributorDepartment of Electrical and Electronic Engineeringen_US
dc.creatorXu, Xen_US
dc.creatorLi, Jen_US
dc.creatorXu, Zen_US
dc.creatorZhao, Jen_US
dc.creatorLai, CSen_US
dc.date.accessioned2023-08-11T03:10:12Z-
dc.date.available2023-08-11T03:10:12Z-
dc.identifier.issn0306-2619en_US
dc.identifier.urihttp://hdl.handle.net/10397/100538-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2019 Published by Elsevier Ltd.en_US
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Xu, X., Li, J., Xu, Z., Zhao, J., & Lai, C. S. (2019). Enhancing photovoltaic hosting capacity—A stochastic approach to optimal planning of static var compensator devices in distribution networks. Applied energy, 238, 952-962 is available at https://doi.org/10.1016/j.apenergy.2019.01.135.en_US
dc.subjectBenders decompositionen_US
dc.subjectPhotovoltaic hosting capacityen_US
dc.subjectStatic var compensator planning modelen_US
dc.subjectTwo-stage stochastic programmingen_US
dc.subjectUncertainty scenariosen_US
dc.titleEnhancing photovoltaic hosting capacity—A stochastic approach to optimal planning of static var compensator devices in distribution networksen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationTitle on author’s file: Enhancing Photovoltaic Hosting Capacity—A Stochastic Approach to Optimal Planning of SVC in Distribution Networken_US
dc.identifier.spage952en_US
dc.identifier.epage962en_US
dc.identifier.volume238en_US
dc.identifier.doi10.1016/j.apenergy.2019.01.135en_US
dcterms.abstractTo improve photovoltaic hosting capacity of distribution networks, this paper proposes a novel optimal static var compensator planning model which is formulated as a two-stage stochastic programming problem. Specifically, the first stage of our model determines the static var compensator planning decisions and the corresponding photovoltaic hosting capacity. In the second stage, the feasibility of the first stage results is evaluated under different uncertainty scenarios of load demand and photovoltaic output to ensure no constraint violations, especially no voltage constraint violations. In addition, we simultaneously consider the minimization of static var compensator planning cost and the maximization of photovoltaic hosting capacity by formulating a multi-objective function. To improve the computational efficiency, a solution method based on Benders decomposition is developed by decomposing the two-stage problem into a master problem and multiple subproblems. The effectiveness of the proposed model and solution method is validated on modified IEEE 37-node and 123-node distribution systems. Last, our results show that the proposed model can significantly improve the photovoltaic hosting capacity. The case studies also demonstrate that the PV hosting capacity becomes insensitive to the additional SVC planning cost when the total cost exceeds about $175,000.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationApplied energy, 15 Mar. 2019, v. 238, p. 952-962en_US
dcterms.isPartOfApplied energyen_US
dcterms.issued2019-03-15-
dc.identifier.scopus2-s2.0-85060484108-
dc.identifier.eissn1872-9118en_US
dc.description.validate202307 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEE-0243-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS24273139-
dc.description.oaCategoryGreen (AAM)en_US
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