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An Enhanced MILP Model for Multistage Reliability-Constrained Distribution Network Expansion Planning

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Jooshaki, Mohammad
dc.contributor.author Abbaspour, Ali
dc.contributor.author Fotuhi-Firuzabad, Mahmud
dc.contributor.author Munoz-Delgado, Gregorio
dc.contributor.author Contreras, Javier
dc.contributor.author Lehtonen, Matti
dc.contributor.author Arroyo, Jose M.
dc.date.accessioned 2021-08-25T06:54:37Z
dc.date.available 2021-08-25T06:54:37Z
dc.date.issued 2022-01-01
dc.identifier.citation Jooshaki , M , Abbaspour , A , Fotuhi-Firuzabad , M , Munoz-Delgado , G , Contreras , J , Lehtonen , M & Arroyo , J M 2022 , ' An Enhanced MILP Model for Multistage Reliability-Constrained Distribution Network Expansion Planning ' , IEEE Transactions on Power Systems , vol. 37 , no. 1 , pp. 118-131 . https://doi.org/10.1109/TPWRS.2021.3098065 en
dc.identifier.issn 0885-8950
dc.identifier.issn 1558-0679
dc.identifier.other PURE UUID: db940886-8ef3-4183-bd3b-0b67cc101674
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/db940886-8ef3-4183-bd3b-0b67cc101674
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85111027930&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/78143418/ELEC_Jooshaki_etal_An_Enhanced_MILP_Model_IEEE_TPWRS_2021.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/109187
dc.description Publisher Copyright: IEEE
dc.description.abstract Reliability is an essential factor in distribution networkt expansion planning. However, standard distribution reliability assessment techniques rely on quantifying the impact of a pre-specified set of events on service continuity through the simulation of component outages, one at a time. Due to such a simulation-based nature, the incorporation of reliability into distribution network expansion planning has customarily required the application of heuristic and metaheuristic approaches. Recently, alternative mixed-integer linear programming (MILP) models have been proposed for distribution network expansion planning considering reliability. Nonetheless, such models suffer from either low computational efficiency or over-simplification. To overcome these shortcomings, this paper proposes an enhanced MILP model for multistage reliability-constrained distribution network expansion planning. Leveraging an efficient, yet accurate reliability evaluation model, proposing a customized technique for effectively imposing radial operation, as well as utilizing pragmatic measures to model reliability-related costs are the salient features of this work. In this respect, practical reliability-related costs are considered based on reliability incentive schemes and the revenue lost due to undelivered energy during customer outages. The proposed planning approach is tested on four networks with 24, 54, 86, and 138 nodes to illustrate its efficiency and applicability. en
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries IEEE Transactions on Power Systems en
dc.rights openAccess en
dc.title An Enhanced MILP Model for Multistage Reliability-Constrained Distribution Network Expansion Planning en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Electrical Engineering and Automation
dc.contributor.department Sharif University of Technology
dc.contributor.department University of Castilla-La Mancha
dc.contributor.department Universidad de Castilla-La Mancha
dc.subject.keyword Distribution network expansion planning
dc.subject.keyword Distribution networks
dc.subject.keyword Indexes
dc.subject.keyword Investment
dc.subject.keyword mixed-integer linear programming
dc.subject.keyword multistage
dc.subject.keyword Planning
dc.subject.keyword Power system reliability
dc.subject.keyword Reliability
dc.subject.keyword reliability
dc.subject.keyword Substations
dc.identifier.urn URN:NBN:fi:aalto-202108258424
dc.identifier.doi 10.1109/TPWRS.2021.3098065
dc.type.version acceptedVersion

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