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Optimising Photovoltaic Farm Location Using a Capabilities Matrix and GIS

Author

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  • Anna Maria Kowalczyk

    (Department of Geodesy, Institute of Geodesy and Civil Engineering, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-724 Olsztyn, Poland)

  • Szymon Czyża

    (Department of Geoinformation and Cartography, Institute of Geodesy and Civil Engineering, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-724 Olsztyn, Poland)

Abstract

Renewable energy sources provide an important solution in environmental protection activities and in the process of shaping sustainable development. The search for optimal locations enabling full exploitation of the energy intensity of real estate presents a significant challenge in terms of geoinformation analysis methods in a GIS environment. The aim of the study was to develop a capabilities matrix for the location of photovoltaic farms and, based on this, to compile a map of decision alternatives for these locations. The first stage involved the determination of the spatial features (stimulants and destimulants), which were significant in the context of photovoltaic (PV) farm location. During the analysis, the scope of the necessary data and their sources, which included topographic vector studies, aerial images, and the OpenStreetMap open data, were determined. The next stage was to determine the weights of the features which were significant in the context of photovoltaic (PV) farm location. To this end, the Multicriteria Decision Making (MCDM) method, including the Analytic Hierarchy Process (AHP) method, was employed. For the verification of the results, the entropy measure was also used. Entropy was calculated based on the diversity of previously identified geospatial features that shape the optimum conditions for their location, based on the photovoltaic farms already existing in Poland. A total of 555 photovoltaic farms were analysed. The next stage assumed the performance of geoinformation analyses using GIS tools and the development of a capabilities matrix for the PV farm location for the selected commune in Poland. The final stage involved the compilation of a PV decision alternative map for the selected commune based on the capabilities matrix. As a result, as an example, a ranking of plots was developed as decision-making alternatives for the municipality of Czarnia located in the northeastern part of Poland. It shows which parcels of land primarily have the dimension of spatial features that are favourable for the location of PV. More than 6900 parcels were analysed, in which 176 presented the highest value of the index of optimal PV location generated using the AHP method. This method provides a basis for further work by identifying optimal locations taking into account existing spatial conditions. The analyses carried out can be an important document in the future for spatial management, in particular for the location of new PV farms. As a continuation of the research, the authors will work on expanding the scope of the analyses and automating the entire process.

Suggested Citation

  • Anna Maria Kowalczyk & Szymon Czyża, 2022. "Optimising Photovoltaic Farm Location Using a Capabilities Matrix and GIS," Energies, MDPI, vol. 15(18), pages 1-32, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6693-:d:913579
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    1. Thomas L. Saaty & Luis G. Vargas, 2012. "The Seven Pillars of the Analytic Hierarchy Process," International Series in Operations Research & Management Science, in: Models, Methods, Concepts & Applications of the Analytic Hierarchy Process, edition 2, chapter 0, pages 23-40, Springer.
    2. Janke, Jason R., 2010. "Multicriteria GIS modeling of wind and solar farms in Colorado," Renewable Energy, Elsevier, vol. 35(10), pages 2228-2234.
    3. Bieda, Agnieszka & Dybał, Łukasz, 2021. "Assessing correctness of local spatial policy using information on commencement of construction investment process," Land Use Policy, Elsevier, vol. 100(C).
    4. Grassi, Stefano & Chokani, Ndaona & Abhari, Reza S., 2012. "Large scale technical and economical assessment of wind energy potential with a GIS tool: Case study Iowa," Energy Policy, Elsevier, vol. 45(C), pages 73-85.
    5. 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.
    6. Höhn, J. & Lehtonen, E. & Rasi, S. & Rintala, J., 2014. "A Geographical Information System (GIS) based methodology for determination of potential biomasses and sites for biogas plants in southern Finland," Applied Energy, Elsevier, vol. 113(C), pages 1-10.
    7. 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.
    8. Arika Ligmann-Zielinska & Piotr Jankowski, 2012. "Impact of proximity-adjusted preferences on rank-order stability in geographical multicriteria decision analysis," Journal of Geographical Systems, Springer, vol. 14(2), pages 167-187, April.
    9. Mondal, Md. Alam Hossain & Denich, Manfred, 2010. "Assessment of renewable energy resources potential for electricity generation in Bangladesh," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2401-2413, October.
    10. Ram Avtar & Netrananda Sahu & Ashwani Kumar Aggarwal & Shamik Chakraborty & Ali Kharrazi & Ali P. Yunus & Jie Dou & Tonni Agustiono Kurniawan, 2019. "Exploring Renewable Energy Resources Using Remote Sensing and GIS—A Review," Resources, MDPI, vol. 8(3), pages 1-23, August.
    11. Serrano-Luján, Lucía & Espinosa, Nieves & Abad, Jose & Urbina, Antonio, 2017. "The greenest decision on photovoltaic system allocation," Renewable Energy, Elsevier, vol. 101(C), pages 1348-1356.
    12. Sorin Avram & Corina Cipu & Ana-Maria Corpade & Carmen Adriana Gheorghe & Nicolae Manta & Mihaita-Iulian Niculae & Ionuţ Silviu Pascu & Róbert Eugen Szép & Steliana Rodino, 2021. "GIS-Based Multi-Criteria Analysis Method for Assessment of Lake Ecosystems Degradation—Case Study in Romania," IJERPH, MDPI, vol. 18(11), pages 1-23, May.
    13. 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.
    14. Voivontas, D. & Assimacopoulos, D. & Mourelatos, A. & Corominas, J., 1998. "Evaluation of Renewable Energy potential using a GIS decision support system," Renewable Energy, Elsevier, vol. 13(3), pages 333-344.
    15. Thomas L. Saaty & Luis G. Vargas, 2012. "Models, Methods, Concepts & Applications of the Analytic Hierarchy Process," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4614-3597-6, September.
    16. Zanakis, Stelios H. & Solomon, Anthony & Wishart, Nicole & Dublish, Sandipa, 1998. "Multi-attribute decision making: A simulation comparison of select methods," European Journal of Operational Research, Elsevier, vol. 107(3), pages 507-529, June.
    17. Derya Ozturk & Fatmagul Batuk, 2011. "IMPLEMENTATION OF GIS-BASED MULTICRITERIA DECISION ANALYSIS WITH VB IN ArcGIS," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 10(06), pages 1023-1042.
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