Optimizing Photovoltaic Generation Placement and Sizing Using Evolutionary Strategies Under Spatial Constraints

This 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.

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Publication Details

Journal
Energies
Published
2025-04-18
DOI
https://doi.org/10.3390/en18082091
Citations
2
Primary Topic
solar cell performance optimization
Type
article
Field-Weighted Citation Impact
1.46

Funders

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article

Optimizing Photovoltaic Generation Placement and Sizing Using Evolutionary Strategies Under Spatial Constraints

Saymon Fonseca Santos Mendes, Nicolás Muñóz-Galeano, Jesús M. López‐Lezama, Lina Paola Garcés Negrete et al.
2 citations
Energies
solar cell performance optimization
1.46
article

Optimizing Photovoltaic Generation Placement and Sizing Using Evolutionary Strategies Under Spatial Constraints

Saymon Fonseca Santos Mendes, Nicolás Muñóz-Galeano, Jesús M. López‐Lezama, Lina Paola Garcés Negrete, Carlos Henrique Barbosa Silva
article en
2 citations

Abstract

This 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.

EnergiesVol. 18(8)
Universidad de Antioquia (CO), Universidade Federal de Goiás (BR)
Ministério da Ciência, Tecnologia e Inovação, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 18%
solar cell performance optimization
1.46
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