Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study
Many countries have set a goal for a carbon neutral future, and the adoption of solar energy as an alternative energy source to fossil fuel is one of the major measures planned. Yet not all locations are equally suitable for solar energy generation. This is due to uneven solar radiation distribution...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/1/312 |
| _version_ | 1797499126274850816 |
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| author | Abdulaziz Alhammad Qian (Chayn) Sun Yaguang Tao |
| author_facet | Abdulaziz Alhammad Qian (Chayn) Sun Yaguang Tao |
| author_sort | Abdulaziz Alhammad |
| collection | DOAJ |
| description | Many countries have set a goal for a carbon neutral future, and the adoption of solar energy as an alternative energy source to fossil fuel is one of the major measures planned. Yet not all locations are equally suitable for solar energy generation. This is due to uneven solar radiation distribution as well as various environmental factors. A number of studies in the literature have used multicriteria decision analysis (MCDA) to determine the most suitable places to build solar power plants. To the best of our knowledge, no study has addressed the subject of optimal solar plant site identification for the Al-Qassim region, although developing renewable energy in Saudi Arabia has been put on the agenda. This paper developed a spatial MCDA framework catering to the characteristics of the Al-Qassim region. The framework adopts several tools used in Geographic Information Systems (GIS), such as Random Forest (RF) raster classification and model builder. The framework aims to ascertain the ideal sites for solar power plants in the Al-Qassim region in terms of the amount of potential photovoltaic electricity production (PVOUT) that could be produced from solar energy. For that, a combination of GIS and Analytical Hierarchy Process (AHP) techniques were employed to determine five sub-criteria weights (Slope, Global Horizontal Irradiance (GHI), proximity to roads, proximity to residential areas, proximity to powerlines) before performing spatial MCDA. The result showed that ‘the most suitable’ and ‘suitable’ areas for the establishment of solar plants are in the south and southwest of the region, representing about 17.53% of the study area. The ‘unsuitable’ areas account for about 10.17% of the total study area, which is mainly concentrated in the northern part. The rest of the region is further classified into ‘moderate’ and ‘restricted’ areas, which account for 46.42% and 25.88%, respectively. The most suitable area for potential solar energy, yields approximately 1905 Kwh/Kwp in terms of PVOUT. The proposed framework also has the potential to be applied to other regions nationally and internationally. This work contributes a reproducible GIS workflow for a low-cost but accurate adoption of a solar energy plan to achieve sustainable development goals. |
| first_indexed | 2024-03-10T03:42:59Z |
| format | Article |
| id | doaj.art-eda62b73a9084936a879f40fef01e066 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T03:42:59Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-eda62b73a9084936a879f40fef01e0662023-11-23T11:28:46ZengMDPI AGEnergies1996-10732022-01-0115131210.3390/en15010312Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case StudyAbdulaziz Alhammad0Qian (Chayn) Sun1Yaguang Tao2Geospatial Sciences, School of Science, RMIT University, Melbourne 3000, AustraliaGeospatial Sciences, School of Science, RMIT University, Melbourne 3000, AustraliaGeospatial Sciences, School of Science, RMIT University, Melbourne 3000, AustraliaMany countries have set a goal for a carbon neutral future, and the adoption of solar energy as an alternative energy source to fossil fuel is one of the major measures planned. Yet not all locations are equally suitable for solar energy generation. This is due to uneven solar radiation distribution as well as various environmental factors. A number of studies in the literature have used multicriteria decision analysis (MCDA) to determine the most suitable places to build solar power plants. To the best of our knowledge, no study has addressed the subject of optimal solar plant site identification for the Al-Qassim region, although developing renewable energy in Saudi Arabia has been put on the agenda. This paper developed a spatial MCDA framework catering to the characteristics of the Al-Qassim region. The framework adopts several tools used in Geographic Information Systems (GIS), such as Random Forest (RF) raster classification and model builder. The framework aims to ascertain the ideal sites for solar power plants in the Al-Qassim region in terms of the amount of potential photovoltaic electricity production (PVOUT) that could be produced from solar energy. For that, a combination of GIS and Analytical Hierarchy Process (AHP) techniques were employed to determine five sub-criteria weights (Slope, Global Horizontal Irradiance (GHI), proximity to roads, proximity to residential areas, proximity to powerlines) before performing spatial MCDA. The result showed that ‘the most suitable’ and ‘suitable’ areas for the establishment of solar plants are in the south and southwest of the region, representing about 17.53% of the study area. The ‘unsuitable’ areas account for about 10.17% of the total study area, which is mainly concentrated in the northern part. The rest of the region is further classified into ‘moderate’ and ‘restricted’ areas, which account for 46.42% and 25.88%, respectively. The most suitable area for potential solar energy, yields approximately 1905 Kwh/Kwp in terms of PVOUT. The proposed framework also has the potential to be applied to other regions nationally and internationally. This work contributes a reproducible GIS workflow for a low-cost but accurate adoption of a solar energy plan to achieve sustainable development goals.https://www.mdpi.com/1996-1073/15/1/312GISsolar energysite suitabilityAHPAl-Qassim region |
| spellingShingle | Abdulaziz Alhammad Qian (Chayn) Sun Yaguang Tao Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study Energies GIS solar energy site suitability AHP Al-Qassim region |
| title | Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study |
| title_full | Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study |
| title_fullStr | Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study |
| title_full_unstemmed | Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study |
| title_short | Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study |
| title_sort | optimal solar plant site identification using gis and remote sensing framework and case study |
| topic | GIS solar energy site suitability AHP Al-Qassim region |
| url | https://www.mdpi.com/1996-1073/15/1/312 |
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