IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i8p2091-d1637644.html
   My bibliography  Save this article

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

Author

Listed:
  • Carlos Henrique Silva

    (Electrical, Mechanical and Computer Engineering School, Federal University of Goiás (UFG), Av. Universitária No. 1488, Goiânia 74605-010, Brazil)

  • Saymon Fonseca Santos Mendes

    (Electrical, Mechanical and Computer Engineering School, Federal University of Goiás (UFG), Av. Universitária No. 1488, Goiânia 74605-010, Brazil)

  • Lina P. Garcés Negrete

    (Electrical, Mechanical and Computer Engineering School, Federal University of Goiás (UFG), Av. Universitária No. 1488, Goiânia 74605-010, Brazil)

  • Jesús M. López-Lezama

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Calle 67 No. 53–108, Medellín 050010, Colombia)

  • Nicolás Muñoz-Galeano

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Calle 67 No. 53–108, Medellín 050010, Colombia)

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.

Suggested Citation

  • Carlos Henrique Silva & Saymon Fonseca Santos Mendes & Lina P. Garcés Negrete & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2025. "Optimizing Photovoltaic Generation Placement and Sizing Using Evolutionary Strategies Under Spatial Constraints," Energies, MDPI, vol. 18(8), pages 1-34, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:2091-:d:1637644
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/8/2091/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/8/2091/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:2091-:d:1637644. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.