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Assessment of solar energy potential over the United Arab Emirates using remote sensing and weather forecast data

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  • Gherboudj, Imen
  • Ghedira, Hosni

Abstract

This research proposes innovative maps to describe the land relative suitability indices for the implementation of solar energy systems (PV and CSP) over the United Arab Emirates. These maps have been developed by combining the solar irradiances maps (global horizontal irradiance and direct normal irradiance) with the effects of the land constraints (land slope, land use and land accessibility to the transportation infrastructure) and weather conditions (airborne dust properties, wind speed, relative humidity, air temperature). Remote sensing, weather forecast models and geospatial information system (GIS) offer excellent tools for estimating and monitoring the aforementioned data at high temporal and spatial resolutions. Indeed, these data have acceptable accuracy to provide a good understanding of the degree of exposure to these data over each location. Our results highlight the potential for using the considered tools to estimate the UAE land capability map, dust/relative-humidity/air-temperature risk map and finally the land relative suitability index for both PV and CSP power plants setting. The obtained results confirm that PV power plants are more appropriate for the UAE context than CSP power plants. In fact, the most suitable areas for PV power plants are located in the eastern side of the country, an area which represents 9.7% of the UAE’s total land area. As for the CSP power plants, their most suitable areas are located on the coast nearby Abu-Dhabi and the extreme south of the UAE, with an area that represents 1%.

Suggested Citation

  • Gherboudj, Imen & Ghedira, Hosni, 2016. "Assessment of solar energy potential over the United Arab Emirates using remote sensing and weather forecast data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 1210-1224.
    • Handle: RePEc:eee:rensus:v:55:y:2016:i:c:p:1210-1224
    DOI: 10.1016/j.rser.2015.03.099
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    2. Hachicha, Ahmed Amine & Al-Sawafta, Israa & Said, Zafar, 2019. "Impact of dust on the performance of solar photovoltaic (PV) systems under United Arab Emirates weather conditions," Renewable Energy, Elsevier, vol. 141(C), pages 287-297.
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    8. Al Garni, Hassan Z. & Awasthi, Anjali, 2017. "Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia," Applied Energy, Elsevier, vol. 206(C), pages 1225-1240.
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    13. Wang, Yongli & Tao, Siyi & Chen, Xin & Huang, Feifei & Xu, Xiaomin & Liu, Xiaoli & Liu, Yang & Liu, Lin, 2022. "Method multi-criteria decision-making method for site selection analysis and evaluation of urban integrated energy stations based on geographic information system," Renewable Energy, Elsevier, vol. 194(C), pages 273-292.
    14. Chia-Nan Wang & Yu-Chi Chung & Fajar Dwi Wibowo & Thanh-Tuan Dang & Ngoc-Ai-Thy Nguyen, 2023. "Site Selection of Solar Power Plants Using Hybrid MCDM Models: A Case Study in Indonesia," Energies, MDPI, vol. 16(10), pages 1-24, May.
    15. Griffiths, Steven, 2017. "A review and assessment of energy policy in the Middle East and North Africa region," Energy Policy, Elsevier, vol. 102(C), pages 249-269.
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