Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah Province
Abstract This study utilizes an integrated Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach to perform Solar Power Plant Site Selection (SPPSS) in Kermanshah Province, Iran. It introduces a novel group weighting method, the Dempster-based Best-Worst Method (DB...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-87476-9 |
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| author | Iman Zandi Aynaz Lotfata |
| author_facet | Iman Zandi Aynaz Lotfata |
| author_sort | Iman Zandi |
| collection | DOAJ |
| description | Abstract This study utilizes an integrated Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach to perform Solar Power Plant Site Selection (SPPSS) in Kermanshah Province, Iran. It introduces a novel group weighting method, the Dempster-based Best-Worst Method (DBWM), which combines weights vectors derived from experts’ opinions. The study also conducts a comprehensive sensitivity analysis comparing four GIS-based models for SPPSS. Findings indicate that the Inverse Distance Weighted (IDW) method is the most precise for interpolation, which was subsequently applied in the analysis. Results demonstrate that the GIS-based DBWM-Technique for Order Preference by Similarity to Ideal Solution (GIS-based DBWM-TOPSIS) model is the most stable, identifying slope as the primary criterion for SPPSS. Based on this model, 3% of the area is classified as very low suitability, 9% as low, 24% as moderate, 33% as high, and 31% as very high suitability. The study highlights the substantial impact of selecting appropriate spatial analysis techniques and uses normalization to standardize input criteria with varied units and ranges, enhancing comparability within the MCDM process. Eslamabad-e Gharb, Kangavar, and Gilan-e Gharb counties emerged as the most suitable locations for solar power plant (SPP) development. |
| format | Article |
| id | doaj-art-897bcf680bbf45d18d021b9e35600715 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-897bcf680bbf45d18d021b9e356007152025-01-26T12:24:09ZengNature PortfolioScientific Reports2045-23222025-01-0115112510.1038/s41598-025-87476-9Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah ProvinceIman Zandi0Aynaz Lotfata1Department of GIS, School of Surveying and Geospatial Engineering, College of Engineering, University of TehranDepartment of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of CaliforniaAbstract This study utilizes an integrated Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach to perform Solar Power Plant Site Selection (SPPSS) in Kermanshah Province, Iran. It introduces a novel group weighting method, the Dempster-based Best-Worst Method (DBWM), which combines weights vectors derived from experts’ opinions. The study also conducts a comprehensive sensitivity analysis comparing four GIS-based models for SPPSS. Findings indicate that the Inverse Distance Weighted (IDW) method is the most precise for interpolation, which was subsequently applied in the analysis. Results demonstrate that the GIS-based DBWM-Technique for Order Preference by Similarity to Ideal Solution (GIS-based DBWM-TOPSIS) model is the most stable, identifying slope as the primary criterion for SPPSS. Based on this model, 3% of the area is classified as very low suitability, 9% as low, 24% as moderate, 33% as high, and 31% as very high suitability. The study highlights the substantial impact of selecting appropriate spatial analysis techniques and uses normalization to standardize input criteria with varied units and ranges, enhancing comparability within the MCDM process. Eslamabad-e Gharb, Kangavar, and Gilan-e Gharb counties emerged as the most suitable locations for solar power plant (SPP) development.https://doi.org/10.1038/s41598-025-87476-9Best-worst methodDempster’s combination ruleGIS-based multi-criteria decision-makingSolar power plant site selection |
| spellingShingle | Iman Zandi Aynaz Lotfata Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah Province Scientific Reports Best-worst method Dempster’s combination rule GIS-based multi-criteria decision-making Solar power plant site selection |
| title | Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah Province |
| title_full | Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah Province |
| title_fullStr | Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah Province |
| title_full_unstemmed | Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah Province |
| title_short | Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah Province |
| title_sort | evaluating solar power plant sites using integrated gis and mcdm methods a case study in kermanshah province |
| topic | Best-worst method Dempster’s combination rule GIS-based multi-criteria decision-making Solar power plant site selection |
| url | https://doi.org/10.1038/s41598-025-87476-9 |
| work_keys_str_mv | AT imanzandi evaluatingsolarpowerplantsitesusingintegratedgisandmcdmmethodsacasestudyinkermanshahprovince AT aynazlotfata evaluatingsolarpowerplantsitesusingintegratedgisandmcdmmethodsacasestudyinkermanshahprovince |