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Conference Paper: Look-Ahead Strategic Offering for a Virtual Power Plant: A Multi-Stage Stochastic Programming Approach

TitleLook-Ahead Strategic Offering for a Virtual Power Plant: A Multi-Stage Stochastic Programming Approach
Authors
KeywordsVirtual power plant
strategic offering
look-ahead operation
real-time electricity market
multi-stage stochastic programming
Issue Date2019
PublisherIEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome/1801868/all-proceedings
Citation
Proceedings of 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), Chengdu, China, 21-24 May 2019, p. 2991-2996 How to Cite?
AbstractThe increasing number of distributed energy resources on the distribution side has promoted the development of virtual power plants to become active market participants. Considering the uncertainty in the market price and the wind generation in a virtual power plant (VPP) in the real-time operation, this paper proposes a look-ahead real-time offering strategy using a multistage stochastic programming formulation within each look-ahead horizon. We test the proposed model on a small virtual power plant. The supply offer curve and the demand offer curve for different market price cases are determined, and the operating states for the VPP system and its components under different scenarios are also obtained. Using the proposed look-ahead approach, the VPP can determine the rolling offer curves continuously to participate in the real-time electricity market.
Persistent Identifierhttp://hdl.handle.net/10722/289411
ISSN

 

DC FieldValueLanguage
dc.contributor.authorZhao, Y-
dc.contributor.authorLiu, R-
dc.contributor.authorLei, S-
dc.contributor.authorHou, Y-
dc.date.accessioned2020-10-22T08:12:17Z-
dc.date.available2020-10-22T08:12:17Z-
dc.date.issued2019-
dc.identifier.citationProceedings of 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), Chengdu, China, 21-24 May 2019, p. 2991-2996-
dc.identifier.issn2378-8534-
dc.identifier.urihttp://hdl.handle.net/10722/289411-
dc.description.abstractThe increasing number of distributed energy resources on the distribution side has promoted the development of virtual power plants to become active market participants. Considering the uncertainty in the market price and the wind generation in a virtual power plant (VPP) in the real-time operation, this paper proposes a look-ahead real-time offering strategy using a multistage stochastic programming formulation within each look-ahead horizon. We test the proposed model on a small virtual power plant. The supply offer curve and the demand offer curve for different market price cases are determined, and the operating states for the VPP system and its components under different scenarios are also obtained. Using the proposed look-ahead approach, the VPP can determine the rolling offer curves continuously to participate in the real-time electricity market.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome/1801868/all-proceedings-
dc.relation.ispartofIEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Conference Proceedings-
dc.rightsIEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Conference Proceedings. Copyright © IEEE.-
dc.rights©2019 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.-
dc.subjectVirtual power plant-
dc.subjectstrategic offering-
dc.subjectlook-ahead operation-
dc.subjectreal-time electricity market-
dc.subjectmulti-stage stochastic programming-
dc.titleLook-Ahead Strategic Offering for a Virtual Power Plant: A Multi-Stage Stochastic Programming Approach-
dc.typeConference_Paper-
dc.identifier.emailHou, Y: yhhou@hku.hk-
dc.identifier.authorityHou, Y=rp00069-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ISGT-Asia.2019.8881545-
dc.identifier.scopuseid_2-s2.0-85074949564-
dc.identifier.hkuros316702-
dc.identifier.spage2991-
dc.identifier.epage2996-
dc.publisher.placeUnited States-
dc.identifier.issnl2378-8534-

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