Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93951
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dc.contributorDepartment of Electrical Engineeringen_US
dc.creatorMohan, Ven_US
dc.creatorBu, Sen_US
dc.creatorJisma, Men_US
dc.creatorRijinlal, VCen_US
dc.creatorThirumala, Ken_US
dc.creatorThomas, MSen_US
dc.creatorXu, Zen_US
dc.date.accessioned2022-08-03T08:49:28Z-
dc.date.available2022-08-03T08:49:28Z-
dc.identifier.issn0142-0615en_US
dc.identifier.urihttp://hdl.handle.net/10397/93951-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2020 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Mohan, V., Bu, S., Jisma, M., Rijinlal, V. C., Thirumala, K., Thomas, M. S., & Xu, Z. (2021). Realistic energy commitments in peer-to-peer transactive market with risk adjusted prosumer welfare maximization. International Journal of Electrical Power & Energy Systems, 124, 106377 is available at https://doi.org/10.1016/j.ijepes.2020.106377.en_US
dc.subjectMulti-objective optimizationen_US
dc.subjectPeer-to-peeren_US
dc.subjectPortfolioen_US
dc.subjectPSOen_US
dc.subjectRisken_US
dc.subjectTransactive energy marketen_US
dc.titleRealistic energy commitments in peer-to-peer transactive market with risk adjusted prosumer welfare maximizationen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationTitle on author’s file: Realistic Energy Commitments in P2P Transactive Market with Risk Adjusted Prosumer Welfare Trade-offen_US
dc.identifier.volume124en_US
dc.identifier.doi10.1016/j.ijepes.2020.106377en_US
dcterms.abstractAs the local energy sources are mostly uncertain and fluctuating in nature, the ‘energy risk’ due to discrepancies between committed energy transactions and metered measurements is prominent in peer to peer (P2P) markets. We propose a P2P market settlement mechanism which lowers this risk and maximizes the welfare of buyers and sellers. The risk in energy production is modelled using Markowitz portfolio theory and the best point where energy return per unit risk is maximum is obtained from the efficient frontier by using the modified Sharpe ratio. The energy portfolio thus obtained is used as a constraint while optimizing the conflicting prosumer benefits using multi-objective stochastic weight trade-off chaotic non-dominated sorting particle swarm optimization (SWTC-NSPSO). In effect, only a reliable proportion of total energy demand submitted in the bid is cleared in the market, foreseeing the real-time fluctuations. The proposed market settlement mechanism also gives room to the existing distribution system operators by assigning them the duty of 1) optimally allocating energy among buyers and sellers in accordance with their competitive bids 2) providing the infrastructure, managing the market and charging for the service and 3) checking the technical feasibility by performing load flow and monitoring power transfer sensitivities to encourage short distance transactions. The energy allocation is done in CIGRE LV benchmark microgrid with ten peers having solar and wind generation. The allocated energy is found to be closer to the metered measurements and hence the reserve cost is observed to be less.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of electrical power and energy systems, Jan. 2021, v. 124, 106377en_US
dcterms.isPartOfInternational journal of electrical power and energy systemsen_US
dcterms.issued2021-01-
dc.identifier.scopus2-s2.0-85088813585-
dc.identifier.artn106377en_US
dc.description.validate202205 bchyen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEE-0047-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextSPARC, Ministry of Human Resources and Development, Government of Indiaen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS53061699-
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