Dere S., Elçin Günay E., Kula U., Kremer G.E. (2024). Assessing agrivoltaics potential in Türkiye - A geographical information system (GIS)-based fuzzy multi-criteria decision making (MCDM) approach. Computers & Industrial Engineering, 01/11/2024, vol. 197, p. 110598.
https://doi.org/10.1016/j.cie.2024.110598
https://doi.org/10.1016/j.cie.2024.110598
Titre : | Assessing agrivoltaics potential in Türkiye - A geographical information system (GIS)-based fuzzy multi-criteria decision making (MCDM) approach (2024) |
Auteurs : | S. Dere ; E. Elçin Günay ; U. Kula ; G.E. Kremer |
Type de document : | Article |
Dans : | Computers & Industrial Engineering (vol. 197, November 2024) |
Article en page(s) : | p. 110598 |
Langues : | Anglais |
Langues du résumé : | Anglais |
Catégories : |
Catégories principales 16 - TRANSPORT. INFRASTRUCTURE. ENERGIE ; 16.3 - EnergieThésaurus IAMM ENERGIE RENOUVELABLE ; ENERGIE SOLAIRE ; AIDE A LA DECISION ; PRISE DE DECISION ; SYSTEME D'INFORMATION GEOGRAPHIQUE ; EVALUATION ; METHODE ; TURQUIE |
Mots-clés: | AGRIVOLTAISME |
Résumé : | To fulfill the energy requirements through solar photovoltaic (PV) systems, significant land use is needed for solar arrays, access roads, substations, and service buildings. When available land is limited, its use for PV systems creates a major conflict, particularly for crop production. Agrivoltaic (APV) systems are engineered to allocate the same land effectively for both PV energy generation and agricultural activities. Thus, they enable the simultaneous production of food and energy. This study investigates the APV potential of Türkiye using fuzzy multi-criteria decision-making (MCDM) approach and Geographic Information System (GIS) data. The top five cities with the largest cultivated area are identified for assessment of potential APV investments using the fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to the ideal solution (TOPSIS) methods. The FAHP method captures the uncertainty and vagueness in experts' judgments for criteria prioritization. Next, suitability maps are created using the criteria weights and GIS data to identify potential sites for the APV construction. Finally, the best location is selected Siverek East- Sanliurfa from fifteen candidate locations from five cities by the TOPSIS method. Sensitivity analysis is conducted to examine the impact of criteria weights on APV suitability maps. The findings of the study provide valuable insights for practitioners in selecting investment locations to harness solar energy sustainably and concurrently facilitate crop production. |
Cote : | Réservé lecteur CIHEAM |
URL / DOI : | https://doi.org/10.1016/j.cie.2024.110598 |