Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93959
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Electrical Engineeringen_US
dc.creatorGao, Xen_US
dc.creatorChan, KWen_US
dc.creatorXia, Sen_US
dc.creatorZhou, Ben_US
dc.creatorLu, Xen_US
dc.creatorXu, Den_US
dc.date.accessioned2022-08-03T08:49:31Z-
dc.date.available2022-08-03T08:49:31Z-
dc.identifier.issn0360-5442en_US
dc.identifier.urihttp://hdl.handle.net/10397/93959-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Gao, X., Chan, K. W., Xia, S., Zhou, B., Lu, X., & Xu, D. (2019). Risk-constrained offering strategy for a hybrid power plant consisting of wind power producer and electric vehicle aggregator. Energy, 177, 183-191 is available at https://doi.org/10.1016/j.energy.2019.04.048.en_US
dc.subjectElectric vehicleen_US
dc.subjectHybrid power planten_US
dc.subjectOffering strategyen_US
dc.subjectRenewable energyen_US
dc.titleRisk-constrained offering strategy for a hybrid power plant consisting of wind power producer and electric vehicle aggregatoren_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage183en_US
dc.identifier.epage191en_US
dc.identifier.volume177en_US
dc.identifier.doi10.1016/j.energy.2019.04.048en_US
dcterms.abstractRenewable energy producers such as wind power producers (WPP) and electric vehicle (EV) aggregators are playing an increasingly important role in the electricity market as their large capacity could strategically influence the electricity price. This paper proposes a bi-level stochastic optimization model of offering strategy for an aggregated WPP-EV hybrid power plant (HPP) as a price maker in the day-ahead (DA) market while considering the uncertainties of the energy production and spot price in the real-time (RT) market. While the HPP's profits is maximized in the upper level of the proposed model with the use of conditional-value-at-risk (CVaR) to manage the risk of expected revenues, the social welfare from the perspective of the grid is maximized in the lower level. The formulated bi-level model is first transformed into a single-level mathematical program with equilibrium constraints (MPEC) and then further transformed into a mixed integer linear programming (MILP) problem for solution. Simulation results have demonstrated the effectiveness of the proposed HPP model with strategically bidding price to increase profits and reduce volatility of profits by considering the risk-metric.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnergy, 15 June 2019, v. 177, p. 183-191en_US
dcterms.isPartOfEnergyen_US
dcterms.issued2019-06-15-
dc.identifier.scopus2-s2.0-85064562095-
dc.identifier.eissn1873-6785en_US
dc.description.validate202205 bchyen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEE-0212-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe Hong Kong Polytechnic University; National Natural Science Foundation of China; Jiangsu Basic Research Projecten_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS26686245-
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Gao_Risk-Constrained_Offering_Strategy.pdfPre-Published version1.19 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

51
Last Week
1
Last month
Citations as of May 12, 2024

Downloads

62
Citations as of May 12, 2024

SCOPUSTM   
Citations

30
Citations as of May 17, 2024

WEB OF SCIENCETM
Citations

26
Citations as of May 16, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.