Agronomy Science, przyrodniczy lublin, czasopisma up, czasopisma uniwersytet przyrodniczy lublin
Skip to main navigation menu Skip to main content Skip to site footer
Agronomy Science Baner text

Vol. 80 No. 3 (2025)

Articles

AHP-based site suitability for agrivoltaics in Lublin Voivodeship, Poland

DOI: https://doi.org/10.24326/as.2025.5550
Submitted: May 22, 2025
Published: 13.11.2025

Abstract

In Poland, as in the global energy market, the popularity of renewable energy sources, whose main advantage over fossil fuels is climate neutrality, is growing. An alternative to dedicating land exclusively to renewable energy is agrivoltaics, which involves dual use of land: for agricultural production and for photovoltaic installations that convert solar energy into usable energy simultaneously. The study's main purpose was to answer two questions: to what extent are the agricultural lands of eastern Poland suitable for the development of agrivoltaics, and how does the selection of criteria affect the final result of the analysis in light of the Analytic Hierarchy Process. The study area was the Lublin Voivodeship, whose potential was evaluated based on 8 orography and land use criteria. The study focuses on spatial conditions, whereas legal and economic conditions have not been considered. The analysis showed that implementing agrivoltaics is theoretically feasible on 79% of the Voivodeship’s total agricultural land, of which 9,961 km2 can be considered at least moderately highly suitable. Additionally, two alternative scenarios were analysed: in the first, only orography criteria were assessed, and in the second, only land use. The comparative analysis revealed that the choice of criteria significantly impacts the results. The highest area suitability was obtained in the assessment considering land use only, and the lowest for orography.

References

  1. Adjiski V., Serafimovski D., 2024. GIS – and AHP-based decision systems for evaluating optimal locations of photovoltaic power plants: case study of Republic of North Macedonia. Geomat. Environ. Eng. 18(1), 51–82. https://doi.org/10.7494/geom.2024.18.1.51
  2. Alami Merrouni A., Elwali Elalaoui F., Mezrhab A., Mezrhab A., Ghennioui A., 2018. Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco. Renew. Energy 119, 863–873. https://doi.org/10.1016/j.renene.2017.10.044
  3. Albraheem L., Alabdulkarim L., 2021. Geospatial analysis of solar energy in Riyadh using GIS-AHP-based technique. Int. J. Geo-Inf. 10(5), 291. https://doi.org/10.3390/ijgi10050291
  4. Almasad A., Pavlak G., Alquthami T., Kumara S., 2023. Site suitability analysis for implementing solar PV power plants using GIS and fuzzy MCDM based approach. Sol. Energy 249, 642–650. https://doi.org/10.1016/j.solener.2022.11.046
  5. Amaducci S., Yin X., Colauzzi M., 2019. Agrivoltaic systems to optimise land use for electric ener-gy production. Appl. Energy 220, 545–561. https://doi.org/10.1016/j.apenergy.2018.03.081
  6. Barbón A., Fortuny Ayuso P., Bayón L., Silva C.A., 2023. Experimental and numerical investiga-tion of the influence of terrain slope on the performance of single-axis trackers. Appl. Energy 348, 121524. https://doi.org/10.1016/j.apenergy.2023.121524
  7. Binduhewa P.J., 2021. Sizing algorithm for a photovoltaic system along an urban railway network towards net zero emission. Int. J. Photoenergy 1, 5523448. https://doi.org/10.1155/2021/5523448
  8. Campana P.E., Lawford R., 2022. Renewable energies in the context of the water–food–energy nexus. In: J. Jurasz, A. Beluco (eds), Complementarity of variable renewable energy sources. Academic Press, 571–614. https://doi.org/10.1016/B978-0-323-85527-3.00010-8
  9. Cansino-Loeza B., Del Carmen Munguía-López A., Ponce-Ortega J.M., 2022. Optimizing the allo-cation of resources for the security of the water-energy-food nexus. In: L. Montastruc, S. Negny, Computer Aided Chemical Engineering, vol. 51, 1579–1584. https://doi.org/10.1016/B978-0-323-95879-0.50264-2
  10. Chikate B.V., Sadawarte Y.A., 2015. The factors affecting the performance of solar cell. Internation-al Conference on Advancements in Engineering and Technology 2015, ICQUEST2015(1), 4–8.
  11. Colak H.E., Memisoglu T., Gercek Y., 2020. Optimal site selection for solar photovoltaic (PV) power plants using GIS and AHP: A case study of Malatya Province, Turkey. Renew. Energy 149, 565–576. https://doi.org/10.1016/j.renene.2019.12.078
  12. Copernicus Land Monitoring Service. https://doi.org/10.2909/cd534ebf-f553-42f0-9ac1-62c1dc36d32c
  13. Doorga J.R.S, Rughooputh S.D.D.V., Boojhawon R., 2019. Multi-criteria GIS-based modelling technique for identifying potential solar farm sites: A case study in Mauritius. Renew. Energy 133, 1201–1219. https://doi.org/10.1016/j.renene.2018.08.105
  14. Elboshy B., Alwetaishi M., Aly R., Zalhaf A.S., 2022. A suitability mapping for the PV solar farms in Egypt based on GIS-AHP to optimize multi-criteria feasibility. Ain Shams Eng. J. 13(3), 101618. https://doi.org/10.1016/j.asej.2021.10.013
  15. Global Solar Atlas, https://globalsolaratlas.info/ [access: 04.05.2025].
  16. Golden B.L., Wang Q.,1989. An alternate measure of consistency. In: B.L. Golden, E.A. Wasil, P.T. Harker (eds), Analytic hierarchy process: applications and studies. New York, 68–81. https://doi.org/10.1007/978-3-642-50244-6_5
  17. Günen M.A., 2021. A comprehensive framework based on GIS-AHP for the installation of solar PV farms in Kahramanmaraş, Turkey. Renew. Energy 178, 212–225. https://doi.org/10.1016/ j.renene.2021.06.078
  18. Harinarayana T., Vasavi K.S.V., 2014. Solar energy generation using agriculture cultivated lands. Smart Grid Renew. Energy 05(02), 31–42. http://dx.doi.org/10.4236/sgre.2014.52004
  19. IEA, 2023. World energy outlook 2023, France.
  20. IEA, IRENA, UNSD, World Bank, WHO, 2023. Tracking SDG 7: The energy progress report. Washington DC.
  21. IEA, 2024. Renewables 2023. Paris.
  22. Jo H., Asekova S., Bayat M.A., Ali L., Song J.T., Ha Y.-S., Hong D.-H., Lee J.-D., 2022. Compar-ison of yield and yield components of several crops grown under agro-photovoltaic system in Korea. Agriculture 12(5), 619. https://doi.org/10.3390/agriculture12050619
  23. Klugmann-Radziemska E., 2014, Photovoltaic-installation performance in Central Europe on the example of Poland., J. Solar Eneg. Res. Updat. 1, 3–11. https://doi.org/10.15377/2410-2199.2014.01.01.1
  24. Kottek M., Grieser J., Beck C., Rudolf B., Rubel F., 2006. World map of the Köppen-Geiger climate classification updated. Meteorol. Z. 15(3). 259–263. https://dx.doi.org/10.1127/0941-2948/2006/0130
  25. Kurowska K., Kryszk H., Bielski S., 2022. Location and technical requirements for photovoltaic power stations in Poland. Energies 15(7), 2701. https://doi.org/10.3390/en15072701
  26. Malu P.R., Sharma U.S., Pearce J.M., 2017. Agrivoltaic potential on grape farms in India. Sustain. Energy Technol. Assess. 104–110. https://doi.org/10.1016/j.seta.2017.08.004
  27. Mamun M.A.A., Dargusch P., Wadley D., Zulkarnain N.A., Aziz A.A., 2022. A review of research on agrivoltaic systems. Renew. Sustain. Energy Rev. 161, 112351. https://doi.org/10.1016/j.rser.2022.112351
  28. Matuszczyk P., Popławski T., Flasza J., 2015. The influence of solar radiation and temperature module on selected parameters and the power rating of photovoltaic panels. Prz. Elektrotech. 91(12), 161–164. https://doi.org/10.15199/48.2015.12.40
  29. Mbah R.E., Wasum D., 2022. Russian-Ukraine 2022 war: a review of the economic impact of Rus-sian-Ukraine crisis on the USA, UK, Canada, and Europe. Adv. Soc. Sci. Res. J. 9(3), 144–153. https://doi.org/10.14738/assrj.93.12005
  30. Munkhbat U., Choi Y., 2021. GIS-based site suitability analysis for solar power systems in Mongo-lia. Appl. Sci. 11(9), 3748. https://doi.org/10.3390/app11093748
  31. Nájera-Ruiz O., Martínez-Gamboa I., Sellschopp-Sánchez S., Santana G., Escalante G., Álvarez-
  32. -Macías C., 2018. Efficiency improvement of photovoltaic cells by cooling using Peltier effect. 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC), 0438–0441. https://doi.org/10.1109/PVSC.2018.8547996
  33. Ouchani F., Jbaihi O., Maaroufi M., Ghennioui A., 2021. Identification of suitable sites for large‐scale photo-voltaic installations through a geographic information system and analytical hierar-chy process combination: A case study in Marrakesh‐Safi region, Morocco. Prog. Photovolt. 29(7), 714–724. https://doi.org/10.1002/pip.3357
  34. Pedrero J., Hermoso N., Hernández P., Muñoz I., Arrizabalaga E., Mabe L., Prieto I., Izkara J.L., 2019. Assessment of urban-scale potential for solar PV generation and consumption. IOP Conf. Series: Earth and Environmental Science 323, 012066. https://doi.org/10.1088/1755-1315/
  35. 323/1/012066
  36. Polish Central Office of Geodesy and Cartography, https://www.geoportal.gov.pl/ [access: 04.05.2025].
  37. Prieto-Amparán J.A., Pinedo-Alvarez A., Morales-Nieto C.R., Valles-Aragón M.C., Álvarez-Holguín A., Villarreal-Guerrero F., 2021. A regional GIS-assisted multi-criteria evaluation of site-suitability for the development of solar farms. Land 10(2), 217. https://doi.org/10.3390/land10020217
  38. Raza M.A., Yousif M., Hassan M., Numan M., Abbas Kazmi S.A., 2023. Site suitability for solar and wind energy in developing countries using combination of GIS-AHP; a case study of Paki-stan. Renew. Energy 206, 180–191. https://doi.org/10.1016/j.renene.2023.02.010
  39. Redi S., Aglietti G.S., Tatnall A.R., Markvart T., 2010. An evaluation of a high altitude solar radia-tion platform. J. Sol. Energy Eng. 132(1), 011004. http://dx.doi.org/10.1115/1.4000327
  40. Rekik S., El Alimi S., 2023. Optimal wind-solar site selection using a GIS-AHP based approach: A case of Tunisia. Energ. Convers. Man-X 18, 100355. https://doi.org/10.1016/j.ecmx.2023.100355
  41. Rios R., Duarte S., 2021. Selection of ideal sites for the development of large-scale solar photovolta-ic projects through Analytical Hierarchical Process – Geographic information systems (AHP-GIS) in Peru. Renew. Sust. Energy Rev. 149, 111310. https://doi.org/10.1016/j.rser.2021.111310
  42. Ruiz H.S., Sunarso A., Ibrahim-Bathis K., Murti S.A., Budiarto I., 2020. GIS-AHP Multi Criteria Decision Analysis for the optimal location of solar energy plants at Indonesia. Energy Rep. 6, 3249–3263. https://doi.org/10.1016/j.egyr.2020.11.198
  43. Saaty R.W., 1987. The analytic hierarchy process – what it is and how it is used. Math. Mod. 9(3–5), 161–176. https://doi.org/10.1016/0270-0255(87)90473-8
  44. Settou B., Settou N., Gouareh A., Negrou B., Mokhtara C., Messaoudi D., 2021. A high-resolution geographic information system-analytical hierarchy process-based method for solar PV power plant site selection: a case study Algeria. Clean. Techn. Environ. Policy 23(1), 219–234. https://doi.org/10.1007/s10098-020-01971-3
  45. Shehab Z.N., Faisal R.M., Ahmed S.W., 2024. Multi-criteria decision making (MCDM) approach for identifying optimal solar farm locations: A multi-technique comparative analysis. Rene. En-ergy 237, 121787. https://doi.org/10.1016/j.renene.2024.121787
  46. Shen X., Wei H., Wei L., 2020. Study of trackside photovoltaic power integration into the traction power system of suburban elevated urban rail transit line. Appl. Energy 260, 114177. https://doi.org/10.1016/j.apenergy.2019.114177
  47. Solon J., Borzyszkowski J.; Bidłasik M., Richling A., Badora K., Balon J., Brzezińska-Wójcik T., Chabudziński Ł., Dobrowolski R., Grzegorczyk I., Jodłowski M., Kistowski M., Kot R., Krąż P., Lechnio J., Macias A., Majchrowska A., Malinowska E., Migoń P., Myga-Piątek U., Nita J., Papińska E., Rodzik J., Strzyż M., Terpiłowski S., Ziaja W., 2018. Physico-geographical mesoregions of Poland: Verification and adjustment of boundaries on the basis of contempo-rary spatial data. Geogr. Pol. 91(2), 143–170. https://doi.org/10.7163/GPol.0115
  48. Statistics Poland, 2023a. Energy 2023. Rzeszów.
  49. Statistics Poland, 2023b. Statistical yearbook of the regions – Poland. Warsaw.
  50. Statistical Office in Lublin, 2021. Report on the socio-economic situation of Lubelskie Voivodship 2021. Lublin.
  51. Statistical Office in Lublin, 2023a. Demographic situation of Lubelskie Voivodship in 2022. Lublin.
  52. Statistical Office in Lublin, 2023b. Agriculture in Lubelskie Voivodship in 2022. Lublin.
  53. Sun L., Jiang Y., Guo Q., Ji L., Xie Y., Qiao Q., Huang G, Xiao K., 2021. A GIS-based multi-criteria decision making method for the potential assessment and suitable sites selection of PV and CSP plants. Resour. Conserv. Recycl. 168, 105306. https://doi.org/10.1016/j.resconrec.2020.105306
  54. Tomczyk A.M., Bednorz E. (eds), 2022. Atlas klimatu Polski (1991–2020) [Atlas of the Climate of Poland (1991-2020)]. Bogucki Wydawnictwo Naukowe. Poznań.
  55. Trommsdorff M., Kang J., Reise C., Schindele S., Bopp G., Ehmann A., Weselek A., Högy P., Obergfell T., 2021. Combining food and energy production: Design of an agrivoltaic system applied in arable and vegetable farming in Germany. Renew. Sustain. Energy Rev. 140, 110694. https://doi.org/10.1016/j.rser.2020.110694
  56. U.S. Geological Survey, https://earthexplorer.usgs.gov [access: 04.05.2025].
  57. Vrînceanu A., Dumitrașcu M., Kucsicsa G., 2022. Site suitability for photovoltaic farms and current investment in Romania. Renew. Energy 187, 320–330. https://doi.org/10.1016/j.renene.2022.01.087
  58. Weselek A., Bauerle A., Hartung J., Zikeli S., Lewandowski I., Högy P., 2021. Agrivoltaic system impacts on microclimate and yield of different crops within an organic crop rotation in a temperate climate. Agron. Sustain. Dev. 41(5), 59. https://doi.org/10.1007/s13593-021-00714-y
  59. Weselek A., Ehmann A., Zikeli S., Lewandowski I., 2019. Agrophotovoltaic systems: applications, challenges, and opportunities. A review. Agron. Sustain. Dev. 39(4), 35. https://doi.org/10.1007/s13593-019-0581-3
  60. Zondag H., 2008. Flat-plate PV-Thermal collectors and systems: A review. Renew. Sustain. Energy Rev. 12(4), 891–959. https://doi.org/10.1016/j.rser.2005.12.012
  61. Yang Q., Huang T., Wang S., Li J., Dai S., Wright S., Wang Y., Peng H., 2019. A GIS-based high spatial resolution assessment of large-scale PV generation potential in China. Appl. Energy 247, 254–269. https://doi.org/10.1016/j.apenergy.2019.04.005
  62. Yousefi H., Hafeznia H., Yousefi-Sahzabi A., 2018. Spatial site selection for solar power plants using a GIS-based boolean-fuzzy logic model: a case study of Markazi Province, Iran. Energies 11(7), 1648. https://doi.org/10.3390/en11071648

Downloads

Download data is not yet available.

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.