Optimizing photovoltaic generation placement and sizing using evolutionary strategies under spatial constraints

dc.creatorSilva, Carlos Henrique dos Santos
dc.creatorMendes, Saymon Fonseca Santos
dc.creatorGarces Negrete, Lina Paola
dc.creatorLopez Lezama, Jesus Maria
dc.creatorMuñoz Galeano, Nicolás
dc.date.accessioned2026-06-09T13:17:44Z
dc.date.available2026-06-09T13:17:44Z
dc.date.issued2025
dc.description.abstractThis study presents a methodology for optimizing the placement and sizing of photovoltaic generation in power distribution networks. In addition to technical and budgetary constraints, the proposed approach incorporates georeferenced spatial restrictions to determine the optimal location and capacity of the generation units. These spatial constraints are not commonly considered in similar studies, which make them the main contribution in the proposed methodology. The proposed approach is divided into three stages and utilizes simulations in OpenDSS and QGIS, which employ optimization strategies such as the Hybrid Evolutionary Strategy and the Hybrid Genetic Algorithm. The methodology was evaluated on the IEEE 34-bus system and a real feeder. The results demonstrate the effectiveness of the proposed approach, which achieves significant reductions in system losses—14.48% for the IEEE 34-bus system and 14.08% for the real feeder—while also improving voltage profiles. These findings validate its applicability in the efficient and sustainable planning of power distribution systems.
dc.identifier.citationSILVA, Carlos Henrique et al. Optimizing photovoltaic generation placement and sizing using evolutionary strategies under spatial constraints. Energies, Basel, v. 18, e2091, 2025. DOI: 10.3390/en18082091. Disponível em: https://www.mdpi.com/1996-1073/18/8/2091. Acesso em: 3 jun. 2026.
dc.identifier.doi10.3390/en18082091
dc.identifier.issne- 1996-1073
dc.identifier.urihttps://repositorio.bc.ufg.br//handle/ri/30617
dc.language.isoeng
dc.publisher.countrySuica
dc.publisher.departmentEscola de Engenharia Elétrica, Mecânica e de Computação - EMC (RMG)
dc.publisher.programPrograma de Pós-graduação em Engenharia Elétrica e da Computação
dc.rightsAcesso Aberto
dc.subjectElectric power distribution systems
dc.subjectEvolutionary strategies
dc.subjectGenetic algorithms
dc.subjectOpenDSS
dc.subjectPhotovoltaic generation
dc.subjectQGIS
dc.subjectSpatial constraints
dc.subject.ODS9 - Industria, inovação e infraestrutura
dc.titleOptimizing photovoltaic generation placement and sizing using evolutionary strategies under spatial constraints
dc.typeArtigo

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