Site selection for solar power plants using GIS and fuzzy analytic hierarchy process: Case study of the western mediterranean region of Turkiye

IF 9 1区 工程技术 Q1 ENERGY & FUELS Renewable Energy Pub Date : 2024-11-02 DOI:10.1016/j.renene.2024.121799
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Abstract

As global warming becomes increasingly evident, the need to use renewable energy sources cannot be overstated. The consumption of fossil fuels in energy production not only exacerbates the effects of global warming but also negatively affects air quality and puts human health at serious risk. The objective of this research is to determine the most suitable locations for solar power plants (SPPs) in the Turkish provinces of Antalya, Burdur, and Isparta, which are situated in the Western Mediterranean Region (WMR). The study employs the Fuzzy Analytic Hierarchy Process (FAHP), a Multi-Criteria Decision Making (MCDM) method, in conjunction with Geographic Information Systems (GIS) for the extraction of spatial information. In evaluating SPP site selection, 11 criteria were considered, including climate, economy, topography, and environmental factors. To produce more objective results during the decision-making phase, a thorough analysis of the relationship between solar irradiance and climatic factors such as air temperature, cloud frequency, and water vapor density which are crucial for the power plant's efficiency in SPP projects was conducted using machine learning techniques. The criteria weights were calculated by the FAHP method, considering expert opinions, literature observations, and machine learning results. The results show that approximately 20 % of the region is suitable for SPP.

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利用地理信息系统和模糊层次分析法为太阳能发电厂选址:土耳其西地中海地区案例研究
随着全球变暖日益明显,使用可再生能源的必要性怎么强调都不为过。在能源生产中消耗化石燃料不仅会加剧全球变暖的影响,还会对空气质量造成负面影响,严重危害人类健康。本研究的目的是确定土耳其安塔利亚省、布尔杜尔省和伊斯帕尔塔省最适合建设太阳能发电厂(SPP)的地点,这些省份位于西地中海地区(WMR)。该研究采用了模糊分析层次过程 (FAHP)、多标准决策 (MCDM) 方法以及地理信息系统 (GIS) 来提取空间信息。在评估 SPP 选址时,考虑了 11 项标准,包括气候、经济、地形和环境因素。为了在决策阶段得出更客观的结果,利用机器学习技术对太阳辐照度与气候因素(如气温、云层频率和水蒸气密度)之间的关系进行了深入分析,这些因素对 SPP 项目中发电厂的效率至关重要。考虑到专家意见、文献观察和机器学习结果,采用 FAHP 方法计算了标准权重。结果表明,约有 20% 的区域适合建设 SPP。
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来源期刊
Renewable Energy
Renewable Energy 工程技术-能源与燃料
CiteScore
18.40
自引率
9.20%
发文量
1955
审稿时长
6.6 months
期刊介绍: Renewable Energy journal is dedicated to advancing knowledge and disseminating insights on various topics and technologies within renewable energy systems and components. Our mission is to support researchers, engineers, economists, manufacturers, NGOs, associations, and societies in staying updated on new developments in their respective fields and applying alternative energy solutions to current practices. As an international, multidisciplinary journal in renewable energy engineering and research, we strive to be a premier peer-reviewed platform and a trusted source of original research and reviews in the field of renewable energy. Join us in our endeavor to drive innovation and progress in sustainable energy solutions.
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