File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: A Robust Operation Strategy for Energy Storage Considering Uncertainty in Electricity Price

TitleA Robust Operation Strategy for Energy Storage Considering Uncertainty in Electricity Price
Authors
Keywordsenergy storage
uncertainty
electricity market
robust optimization
max-min model
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. 3032-3036 How to Cite?
AbstractInaccurate price prediction may cause improper charging/discharging schedules of battery energy storage (BES) in electricity market, which further leads to less or even negative market profits of BES. On this condition, uncertainty in market prices should be fully considered when making operation strategies. In this paper, focusing on an independently operated BES in day-ahead and hour-ahead markets, a multi-stage robust optimal operation strategy is formulated considering uncertainty in multi-periods market prices. The robust optimization model is formulated seeking to maximize market revenues of BES within a given confidence level of price deviation. The max-min model can be converted into a mixed-integer linear programming (MILP) problem which can be easily computable. Case study results demonstrated the validity of the presented robust operation strategy of BES.
Persistent Identifierhttp://hdl.handle.net/10722/289877
ISSN

 

DC FieldValueLanguage
dc.contributor.authorShang, J-
dc.contributor.authorJiang, X-
dc.contributor.authorYin, W-
dc.contributor.authorHou, Y-
dc.contributor.authorYang, Z-
dc.contributor.authorLiu, H-
dc.date.accessioned2020-10-22T08:18:45Z-
dc.date.available2020-10-22T08:18:45Z-
dc.date.issued2019-
dc.identifier.citationProceedings of 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), Chengdu, China, 21-24 May 2019, p. 3032-3036-
dc.identifier.issn2378-8534-
dc.identifier.urihttp://hdl.handle.net/10722/289877-
dc.description.abstractInaccurate price prediction may cause improper charging/discharging schedules of battery energy storage (BES) in electricity market, which further leads to less or even negative market profits of BES. On this condition, uncertainty in market prices should be fully considered when making operation strategies. In this paper, focusing on an independently operated BES in day-ahead and hour-ahead markets, a multi-stage robust optimal operation strategy is formulated considering uncertainty in multi-periods market prices. The robust optimization model is formulated seeking to maximize market revenues of BES within a given confidence level of price deviation. The max-min model can be converted into a mixed-integer linear programming (MILP) problem which can be easily computable. Case study results demonstrated the validity of the presented robust operation strategy of BES.-
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.subjectenergy storage-
dc.subjectuncertainty-
dc.subjectelectricity market-
dc.subjectrobust optimization-
dc.subjectmax-min model-
dc.titleA Robust Operation Strategy for Energy Storage Considering Uncertainty in Electricity Price-
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.2019.8881148-
dc.identifier.scopuseid_2-s2.0-85074911301-
dc.identifier.hkuros316705-
dc.identifier.spage3032-
dc.identifier.epage3036-
dc.publisher.placeUnited States-
dc.identifier.issnl2378-8534-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats