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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/21242
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dc.contributor.authorLi, Z-
dc.contributor.authorLai, CS-
dc.contributor.authorXu, X-
dc.contributor.authorZhao, Z-
dc.contributor.authorLai, LL-
dc.date.accessioned2020-07-20T13:00:34Z-
dc.date.available2020-07-20T13:00:34Z-
dc.date.issued2020-07-17-
dc.identifierORCiD: Chun Sing Lai https://orcid.org/0000-0002-4169-4438-
dc.identifierArticle number: 106322-
dc.identifier.citationLi, Z. et al. (2021) 'Electricity trading based on distribution locational marginal price', International Journal of Electrical Power & Energy Systems, 124, 106322, pp. 1 - 13. doi: 10.1016/j.ijepes.2020.106322.en_US
dc.identifier.issn0142-0615-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/21242-
dc.description.abstractThis paper presents a novel day-ahead power market for distribution systems. Based on the linearized AC power flow model, the distribution locational marginal price for coupled active and reactive power can be calculated and decomposed into five components, i.e. (1) energy price; (2) loss price caused by nodal active power; (3) loss price caused by nodal reactive power; (4) congestion price and (5) voltage support price, which can provide price signals for distributed generator and aggregator in a distribution system to respond. The energy hub at different nodes can trade with each other and optimize their profit based on distribution locational marginal prices. Game theory is applied to solve the energy trading payment problem. The energy trading problem is decomposed into two subproblems, i.e. operation cost minimization problem and trading payment bargaining problem. The effectiveness and validity of the proposed method are illustrated with a modified IEEE 33-bus system.-
dc.description.sponsorshipThis work is sponsored by the Department of Finance and Education of Guangdong Province 2016 [202]: Key Discipline Construction Program, China; the Education Department of Guangdong Province: New and Integrated Energy System Theory and Technology Research Group [Project Number 2016KCXTD022]; Brunel University London BRIEF Funding; National Natural Science Foundation of China (51907031).en_US
dc.format.extent1 - 13-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 International-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectdistribution locational marginal priceen_US
dc.subjectday-ahead marketen_US
dc.subjectenergy huben_US
dc.subjectelectricity tradingen_US
dc.titleElectricity trading based on distribution locational marginal priceen_US
dc.typeArticleen_US
dc.date.dateAccepted2020-06-22-
dc.identifier.doihttps://doi.org/10.1016/j.ijepes.2020.106322-
dc.relation.isPartOfInternational Journal of Electrical Power & Energy Systems-
pubs.publication-statusPublished-
pubs.volume124-
dc.identifier.eissn1879-3517-
dc.rights.licensehttps://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.en-
dcterms.dateAccepted2020-06-22-
dc.rights.holderElsevier Ltd.-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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