Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103152
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Building and Real Estateen_US
dc.creatorAn, Jen_US
dc.creatorHong, Ten_US
dc.creatorLee, Men_US
dc.date.accessioned2023-12-11T00:31:57Z-
dc.date.available2023-12-11T00:31:57Z-
dc.identifier.issn0959-6526en_US
dc.identifier.urihttp://hdl.handle.net/10397/103152-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rights© 2021 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2021. 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 An, J., Hong, T., & Lee, M. (2021). Development of the business feasibility evaluation model for a profitable P2P electricity trading by estimating the optimal trading price. Journal of Cleaner Production, 295, 126138 is available at https://doi.org/10.1016/j.jclepro.2021.126138.en_US
dc.subjectBusiness feasibility evaluationen_US
dc.subjectEnergy prosumeren_US
dc.subjectGenetic algorithmen_US
dc.subjectLevelized cost of electricityen_US
dc.subjectOptimal trading price of electricityen_US
dc.subjectPeer-to-Peer electricity tradingen_US
dc.titleDevelopment of the business feasibility evaluation model for a profitable P2P electricity trading by estimating the optimal trading priceen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume295en_US
dc.identifier.doi10.1016/j.jclepro.2021.126138en_US
dcterms.abstractFor the market participants (i.e., energy consumers and prosumers) in a microgrid to acquire profits via trading surplus electricity, it is essential to determine an appropriate trading price of electricity. Therefore, this study developed a business feasibility evaluation model to predict the optimal trading price of electricity that maximizes the profits of both the market participants participating in the Peer-to-Peer (P2P) electricity trading, by reflecting the structure of electricity market in South Korea. The residential areas located in the seven metropolitan cities in South Korea (Seoul, Incheon, Daejeon, Daegu, Ulsan, Busan, and Gwangju) were selected for the model application. The main findings from the model application are as follows. First, the annual electricity generation of the solar photovoltaic (PV) panel was highest in Daegu (5,541 kWh) and lowest in Seoul (3,569 kWh). In addition, the electricity generation was generally shown to be higher in spring (March–May) and relatively lower in summer and winter. Second, the estimated annual maximum profit of the energy prosumer was highest in Daegu (US$995.5) and lowest in Seoul (US$638.1). Furthermore, it was determined to be beneficial to the energy prosumers to reduce their self-use rate to the extent possible. By using the developed business feasibility evaluation model, decision makers, including specialists and non-specialists, can determine the optimal trading price of electricity and whether to participate in the market of P2P electricity trading.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of cleaner production, 1 May 2021, v. 295, 126138en_US
dcterms.isPartOfJournal of cleaner productionen_US
dcterms.issued2021-05-01-
dc.identifier.scopus2-s2.0-85101206767-
dc.identifier.artn126138en_US
dc.description.validate202312 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberBRE-0085-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextKorea Agency for Infrastructure Technology Advancement (KAIA)en_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS45656374-
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Lee_Development_Business_Feasibility.pdfPre-Published version2.03 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

110
Last Week
3
Last month
Citations as of Nov 30, 2025

Downloads

145
Citations as of Nov 30, 2025

SCOPUSTM   
Citations

30
Citations as of Dec 19, 2025

WEB OF SCIENCETM
Citations

25
Citations as of Dec 18, 2025

Google ScholarTM

Check

Altmetric


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