A Mixed Integer Conic Model for Distribution Expansion Planning: Matheuristic Approach

dc.contributor.authorHome Ortiz, Juan Manoel [UNESP]
dc.contributor.authorKasmaei, Mahdi Porakbari
dc.contributor.authorLethonen, Matti
dc.contributor.authorMantovani, José Roberto Sanches [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-05-14T18:01:22Z
dc.date.available2020-05-14T18:01:22Z
dc.date.issued2020-03-19
dc.description.abstractThis paper presents a mixed-integer conic programming model (MICP) and a hybrid solution approach based on classical and heuristic optimization techniques, namely matheuristic, to handle long-term distribution systems expansion planning (DSEP) problems. The model considers conventional planning actions as well as sizing and allocation of dispatchable/renewable distributed generation (DG) and energy storage devices (ESD). The existing uncertainties in the behavior of renewable sources and demands are characterized by grouping the historical data via the k-means. Since the resulting stochastic MICP is a convex-based formulation, finding the global solution of the problem using a commercial solver is guaranteed while the computational efficiency in simulating the planning problem of medium-or large-scale systems might not be satisfactory. To tackle this issue, the subproblems of the proposed mathematical model are solved iteratively via a specialized optimization technique based on variable neighborhood descent (VND) algorithm. To show the effectiveness of the proposed model and solution technique, the 24-node distribution system is profoundly analyzed, while the applicability of the model is tested on a 182-node distribution system. The results reveal the essential requirement of developing specialized solution techniques for large-scale systems where classical optimization techniques are no longer an alternative to solve such planning problems.pt
dc.description.affiliationSão Paulo State University - Ilha Solteira - SP - Brazil
dc.description.affiliationSão Paulo State University - Ilha Solteira - SP - Brazil
dc.description.affiliationDepartment of Electrical Engineering and Automation, Aalto University, Finland
dc.description.affiliationDepartment of Electrical Engineering and Automation, Aalto University, Finland
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdFapesp 2019/01841-5
dc.description.sponsorshipIdCNPq 305318/2016-0
dc.description.sponsorshipIdFapesp 2015/21972-6
dc.description.versionPreprintpt
dc.identifier.doi10.1109/TSG.2020.2982129
dc.identifier.issn1949-3061
dc.identifier.lattesK4767272J6
dc.identifier.orcid0000-0002-7149-6184
dc.identifier.urihttp://hdl.handle.net/11449/192563
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronic Engineers
dc.relation.ispartofTransactions on Smart Gridspt
dc.rights.accessRightsAcesso restrito
dc.subjectDistribution systems expansion planningpt
dc.subjectstochastic programming.pt
dc.subjectenergy storage devicespt
dc.subjectVND-based matheuristic algorithmpt
dc.subjectmixed-integer conic programmingpt
dc.titleA Mixed Integer Conic Model for Distribution Expansion Planning: Matheuristic Approachpt
dc.typeArtigo
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Engenharia, Ilha Solteirapt

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