Location choice in solar power plants by applying meteorological data to multi-criteria decision-making method


Karadöl İ., YILDIRIM R.

Engineering Applications of Artificial Intelligence, vol.152, 2025 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 152
  • Publication Date: 2025
  • Doi Number: 10.1016/j.engappai.2025.110766
  • Journal Name: Engineering Applications of Artificial Intelligence
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Keywords: Analytical hierarchy process, Meteorological data, Renewable energy, Solar power plant potential
  • Isparta University of Applied Sciences Affiliated: Yes

Abstract

This study aims to determine the optimum generation locations for new solar power plants by evaluating meteorological data according to analytical hierarchy process (AHP). For this purpose, meteorological data for 2021 from three different provinces in Turkey were evaluated using AHP in order to determine which province has the best solar power plant energy potential. To test the accuracy of the obtained results, various scenarios were analyzed based on annual and seasonal data, and then compared against actual plant production data. Comparisons were made by taking into account both AHP scores and average plant production data. The AHP scores obtained for Kilis, Çanakkale, and Bursa provinces were 0.63, 0.38, and 0.16, respectively, whilst the annual average per-unit production of the plants were 0.21, 0.15, and 0.06, respectively. In both the average of real production data and AHP score results, Kilis was determined as the province with the highest potential. All these applications were realized in the same way according to seasonal periods. The AHP score for Kilis province, which was determined as the best location across all four seasons, was determined as 0.55, 0.66, 0.75, and 0.71 for spring, summer, autumn, and winter, respectively.