IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12602-d932991.html
   My bibliography  Save this article

Genetic Algorithms-Based Optimum PV Site Selection Minimizing Visual Disturbance

Author

Listed:
  • Nikolaos Nagkoulis

    (Department of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Eva Loukogeorgaki

    (Department of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Michela Ghislanzoni

    (Territoria, Análisis y Gestión del Medio SLU, Calle Inocentes, 41003 Seville, Spain)

Abstract

In this paper, an integrated methodology is developed to determine optimum areas for Photovoltaic (PV) installations that minimize the relevant visual disturbance and satisfy spatial constraints associated with land use, as well as environmental and techno-economic siting factors. The visual disturbance due to PV installations is quantified by introducing and calculating the “Social Disturbance” (SDIS) indicator, whereas optimum locations are determined for predefined values of two siting preferences (maximum allowable PV locations—grid station distance and minimum allowable total coverage area of PV installations). Thematic maps of appropriate selected exclusion criteria are produced, followed by a cumulative weighted viewshed analysis, where the SDIS indicator is calculated. Optimum solutions are then determined by developing and employing a Genetic Algorithms (GAs) optimization process. The methodology is applied for the municipality of La Palma Del Condado in Spain for 100 different combinations of the two siting preferences. The optimization results are also employed to create a flexible and easy-to-use web-GIS application, facilitating policy-makers to choose the set of solutions that better fulfils their preferences. The GAs algorithm offers the ability to determine distinguishable, but compact, regions of optimum locations in the region, whereas the results indicate the strong dependence of the optimum areas upon the two siting preferences.

Suggested Citation

  • Nikolaos Nagkoulis & Eva Loukogeorgaki & Michela Ghislanzoni, 2022. "Genetic Algorithms-Based Optimum PV Site Selection Minimizing Visual Disturbance," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12602-:d:932991
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12602/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/19/12602/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ibarloza, Ander & Heras-Saizarbitoria, Iñaki & Allur, Erlantz & Larrea, Ainara, 2018. "Regulatory cuts and economic and financial performance of Spanish solar power companies: An empirical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 784-793.
    2. Lefore, N. & Closas, Alvar & Schmitter, Petra, 2021. "Solar for all: a framework to deliver inclusive and environmentally sustainable solar irrigation for smallholder agriculture," Papers published in Journals (Open Access), International Water Management Institute, pages 154:112313..
    3. de la Hoz, Jordi & Martín, Helena & Martins, Blanca & Matas, José & Miret, Jaume, 2013. "Evaluating the impact of the administrative procedure and the landscape policy on grid connected PV systems (GCPVS) on-floor in Spain in the period 2004–2008: To which extent a limiting factor?," Energy Policy, Elsevier, vol. 63(C), pages 147-167.
    4. Sergio Coronas & Jordi de la Hoz & Àlex Alonso & Helena Martín, 2022. "23 Years of Development of the Solar Power Generation Sector in Spain: A Comprehensive Review of the Period 1998–2020 from a Regulatory Perspective," Energies, MDPI, vol. 15(4), pages 1-53, February.
    5. Ren, Haoshan & Xu, Chengliang & Ma, Zhenjun & Sun, Yongjun, 2022. "A novel 3D-geographic information system and deep learning integrated approach for high-accuracy building rooftop solar energy potential characterization of high-density cities," Applied Energy, Elsevier, vol. 306(PA).
    6. Daniel Gabaldón-Estevan & Elisa Peñalvo-López & David Alfonso Solar, 2018. "The Spanish Turn against Renewable Energy Development," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
    7. Sun, Tao & Shan, Ming & Rong, Xing & Yang, Xudong, 2022. "Estimating the spatial distribution of solar photovoltaic power generation potential on different types of rural rooftops using a deep learning network applied to satellite images," Applied Energy, Elsevier, vol. 315(C).
    8. Meryem Tahri & Mustapha Hakdaoui & Mohamed Maanan, 2015. "The evaluation of solar farm locations applying Geographic Information System and Multi-Criteria Decision-Making methods: Case study in southern Morocco," Post-Print hal-01185533, HAL.
    9. Carrión, J. Arán & Espín Estrella, A. & Aznar Dols, F. & Ridao, A. Ramos, 2008. "The electricity production capacity of photovoltaic power plants and the selection of solar energy sites in Andalusia (Spain)," Renewable Energy, Elsevier, vol. 33(4), pages 545-552.
    10. Raman, P. & Murali, J. & Sakthivadivel, D. & Vigneswaran, V.S., 2012. "Opportunities and challenges in setting up solar photo voltaic based micro grids for electrification in rural areas of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3320-3325.
    11. Lindberg, O. & Birging, A. & Widén, J. & Lingfors, D., 2021. "PV park site selection for utility-scale solar guides combining GIS and power flow analysis: A case study on a Swedish municipality," Applied Energy, Elsevier, vol. 282(PA).
    12. Zoellner, Jan & Schweizer-Ries, Petra & Wemheuer, Christin, 2008. "Public acceptance of renewable energies: Results from case studies in Germany," Energy Policy, Elsevier, vol. 36(11), pages 4136-4141, November.
    13. Carlos Toledo & Alessandra Scognamiglio, 2021. "Agrivoltaic Systems Design and Assessment: A Critical Review, and a Descriptive Model towards a Sustainable Landscape Vision (Three-Dimensional Agrivoltaic Patterns)," Sustainability, MDPI, vol. 13(12), pages 1-38, June.
    14. Tahri, Meryem & Hakdaoui, Mustapha & Maanan, Mohamed, 2015. "The evaluation of solar farm locations applying Geographic Information System and Multi-Criteria Decision-Making methods: Case study in southern Morocco," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1354-1362.
    15. Brewer, Justin & Ames, Daniel P. & Solan, David & Lee, Randy & Carlisle, Juliet, 2015. "Using GIS analytics and social preference data to evaluate utility-scale solar power site suitability," Renewable Energy, Elsevier, vol. 81(C), pages 825-836.
    16. Sofia Spyridonidou & Georgia Sismani & Eva Loukogeorgaki & Dimitra G. Vagiona & Hagit Ulanovsky & Daniel Madar, 2021. "Sustainable Spatial Energy Planning of Large-Scale Wind and PV Farms in Israel: A Collaborative and Participatory Planning Approach," Energies, MDPI, vol. 14(3), pages 1-23, January.
    17. Zhong, Qing & Nelson, Jake R. & Tong, Daoqin & Grubesic, Tony H., 2022. "A spatial optimization approach to increase the accuracy of rooftop solar energy assessments," Applied Energy, Elsevier, vol. 316(C).
    18. Lefore, Nicole & Closas, Alvar & Schmitter, Petra, 2021. "Solar for all: A framework to deliver inclusive and environmentally sustainable solar irrigation for smallholder agriculture," Energy Policy, Elsevier, vol. 154(C).
    19. Fernandez-Jimenez, L. Alfredo & Mendoza-Villena, Montserrat & Zorzano-Santamaria, Pedro & Garcia-Garrido, Eduardo & Lara-Santillan, Pedro & Zorzano-Alba, Enrique & Falces, Alberto, 2015. "Site selection for new PV power plants based on their observability," Renewable Energy, Elsevier, vol. 78(C), pages 7-15.
    20. Arán Carrión, J. & Espín Estrella, A. & Aznar Dols, F. & Zamorano Toro, M. & Rodríguez, M. & Ramos Ridao, A., 2008. "Environmental decision-support systems for evaluating the carrying capacity of land areas: Optimal site selection for grid-connected photovoltaic power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(9), pages 2358-2380, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hossein Yousefi & Hamed Hafeznia & Amin Yousefi-Sahzabi, 2018. "Spatial Site Selection for Solar Power Plants Using a GIS-Based Boolean-Fuzzy Logic Model: A Case Study of Markazi Province, Iran," Energies, MDPI, vol. 11(7), pages 1-18, June.
    2. Kim, Byungil & Han, SangUk & Heo, Jae & Jung, Jaehoon, 2020. "Proof-of-concept of a two-stage approach for selecting suitable slopes on a highway network for solar photovoltaic systems: A case study in South Korea," Renewable Energy, Elsevier, vol. 151(C), pages 366-377.
    3. Finn, Thomas & McKenzie, Paul, 2020. "A high-resolution suitability index for solar farm location in complex landscapes," Renewable Energy, Elsevier, vol. 158(C), pages 520-533.
    4. Rogna, Marco, 2020. "A first-phase screening method for site selection of large-scale solar plants with an application to Italy," Land Use Policy, Elsevier, vol. 99(C).
    5. Colak, H. Ebru & Memisoglu, Tugba & Gercek, Yasin, 2020. "Optimal site selection for solar photovoltaic (PV) power plants using GIS and AHP: A case study of Malatya Province, Turkey," Renewable Energy, Elsevier, vol. 149(C), pages 565-576.
    6. Li, Xiao-Ya & Dong, Xin-Yu & Chen, Sha & Ye, Yan-Mei, 2024. "The promising future of developing large-scale PV solar farms in China: A three-stage framework for site selection," Renewable Energy, Elsevier, vol. 220(C).
    7. Nili, Maryam & Seyedhosseini, Seyed Mohammad & Jabalameli, Mohammad Saeed & Dehghani, Ehsan, 2021. "A multi-objective optimization model to sustainable closed-loop solar photovoltaic supply chain network design: A case study in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    8. Al Garni, Hassan Z. & Awasthi, Anjali, 2017. "Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia," Applied Energy, Elsevier, vol. 206(C), pages 1225-1240.
    9. Aly, Ahmed & Jensen, Steen Solvang & Pedersen, Anders Branth, 2017. "Solar power potential of Tanzania: Identifying CSP and PV hot spots through a GIS multicriteria decision making analysis," Renewable Energy, Elsevier, vol. 113(C), pages 159-175.
    10. Shao, Meng & Han, Zhixin & Sun, Jinwei & Xiao, Chengsi & Zhang, Shulei & Zhao, Yuanxu, 2020. "A review of multi-criteria decision making applications for renewable energy site selection," Renewable Energy, Elsevier, vol. 157(C), pages 377-403.
    11. Majumdar, Debaleena & Pasqualetti, Martin J., 2019. "Analysis of land availability for utility-scale power plants and assessment of solar photovoltaic development in the state of Arizona, USA," Renewable Energy, Elsevier, vol. 134(C), pages 1213-1231.
    12. Asadi, Meysam & Ramezanzade, Mohsen & Pourhossein, Kazem, 2023. "A global evaluation model applied to wind power plant site selection," Applied Energy, Elsevier, vol. 336(C).
    13. Sahoo, Somadutta & Zuidema, Christian & van Stralen, Joost N.P. & Sijm, Jos & Faaij, André, 2022. "Detailed spatial analysis of renewables’ potential and heat: A study of Groningen Province in the northern Netherlands," Applied Energy, Elsevier, vol. 318(C).
    14. Yılmaz, Kutay & Dinçer, Ali Ersin & Ayhan, Elif N., 2023. "Exploring flood and erosion risk indices for optimal solar PV site selection and assessing the influence of topographic resolution," Renewable Energy, Elsevier, vol. 216(C).
    15. Gerardo Alcalá & Luis Fernando Grisales-Noreña & Quetzalcoatl Hernandez-Escobedo & Jose Javier Muñoz-Criollo & J. D. Revuelta-Acosta, 2021. "SHP Assessment for a Run-of-River (RoR) Scheme Using a Rectangular Mesh Sweeping Approach (MSA) Based on GIS," Energies, MDPI, vol. 14(11), pages 1-21, May.
    16. Zhang, Zhengjia & Wang, Qingxiang & Liu, Zhengguang & Chen, Qi & Guo, Zhiling & Zhang, Haoran, 2023. "Renew mineral resource-based cities: Assessment of PV potential in coal mining subsidence areas," Applied Energy, Elsevier, vol. 329(C).
    17. Alami Merrouni, Ahmed & Elwali Elalaoui, Fakhreddine & Mezrhab, Ahmed & Mezrhab, Abdelhamid & Ghennioui, Abdellatif, 2018. "Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco," Renewable Energy, Elsevier, vol. 119(C), pages 863-873.
    18. Doljak, Dejan & Stanojević, Gorica, 2017. "Evaluation of natural conditions for site selection of ground-mounted photovoltaic power plants in Serbia," Energy, Elsevier, vol. 127(C), pages 291-300.
    19. Sofia Spyridonidou & Eva Loukogeorgaki & Dimitra G. Vagiona & Teresa Bertrand, 2022. "Towards a Sustainable Spatial Planning Approach for PV Site Selection in Portugal," Energies, MDPI, vol. 15(22), pages 1-22, November.
    20. Zambrano-Asanza, S. & Quiros-Tortos, J. & Franco, John F., 2021. "Optimal site selection for photovoltaic power plants using a GIS-based multi-criteria decision making and spatial overlay with electric load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).

    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:jsusta:v:14:y:2022:i:19:p:12602-:d:932991. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.