Vis enkel innførsel

dc.contributor.authorSun, Yaoqiang
dc.contributor.authorLiu, Nan
dc.contributor.authorKhan, Imran
dc.contributor.authorPark, Youn-Cheol
dc.contributor.authorByun, Yung-Cheol
dc.contributor.authorMadsen, Dag Øivind
dc.date.accessioned2024-05-22T12:52:23Z
dc.date.available2024-05-22T12:52:23Z
dc.date.created2024-01-29T07:30:00Z
dc.date.issued2023
dc.identifier.citationSun, Y., Liu, N., Khan, I., Park, Y.-C., Byun, Y.-C., & Madsen, D. Ø. (2023). A novel framework for photovoltaic energy optimization based on supply–demand constraints. Frontiers in Energy Research, 11, Artikkel 1267579.en_US
dc.identifier.issn2296-598X
dc.identifier.urihttps://hdl.handle.net/11250/3131141
dc.description.abstractIntroduction: Distributed power supply has increasingly taken over as the energy industry’s primary development direction as a result of the advancement of new energy technology and energy connectivity technology. In order to build isolated island microgrids, such as villages, islands, and remote mountainous places, the distributed power supply design is frequently employed. Due to government subsidies and declining capital costs, the configured capacity of new energy resources like solar and wind energy has been substantially rising in recent years. However, the new energy sources might lead to a number of significant operational problems, including over-voltage and ongoing swings in the price of power. Additionally, the economic advantages availed by electricity consumers may be impacted by the change in electricity costs and the unpredictability of the output power of renewable energy sources. Methods: This paper proposes a novel framework for enhancing renewable energy management and reducing the investment constraint of energy storage. First, the energy storage incentive is determined through a bi-level game method. Then, the net incentive of each element is maximized by deploying a master–slave approach. Finally, a reward and punishment strategy is employed to optimize the energy storage in the cluster. Results: Simulation results show that the proposed framework has better performance under different operating conditions. Discussion: The energy storage operators and numerous energy storage users can implement master–slave game-based energy storage pricing and capacity optimization techniques to help each party make the best choices possible and realize the multi-subject interests of energy storage leasing supply and demand win–win conditions.en_US
dc.language.isoengen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleA novel framework for photovoltaic energy optimization based on supply–demand constraintsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2023 Sun, Liu, Khan, Park, Byun and Madsen.en_US
dc.source.volume11en_US
dc.source.journalFrontiers in Energy Researchen_US
dc.identifier.doihttps://doi.org/10.3389/fenrg.2023.1267579
dc.identifier.cristin2236375
dc.source.articlenumber1267579en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Navngivelse 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Navngivelse 4.0 Internasjonal