Modeling predictive suitability to determine potential areas for establishing wind power plants in Sri Lanka

被引:10
作者
Amarasinghe, A. G. [1 ]
Perera, E. N. C. [2 ]
机构
[1] Univ Kelaniya, Fac Social Sci, Dept Geog, Kelaniya, Sri Lanka
[2] Dept Reg Sci & Planning, SANASA Campus, Kegalle, Sri Lanka
关键词
Renewable energy; Site selection; Spatial multi-criteria analysis; AHP; Wind power; SITE SELECTION; GENERATION;
D O I
10.1007/s40808-020-00868-w
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Many of renewable energy sources significantly contributing for fulfill increasing energy demand while reducing greenhouse gas emissions in all around the world. Among various source of renewable energy source, wind energy has been identified as one of the main potential, economically viable and environment friendly energy sources particular in Sri Lanka. Due to the geographical position of Sri Lanka, it has a good condition for wind energy exploitation. However, the optimal sites for install wind power plants are specific, because wind potential is dependent on the several geographical factors. This study introduced geospatial approaches to determine potential areas for wind power plants. For that, five decision factors; Elevation, Wind density, Land use, restricted area, Proximity to road network were extracted from the existing Geodatabases were used and their relative weights were estimated by applying Spatial Multi-Criteria Analysis methods in GIS environment. Results mainly concluded that, Sri Lanka has sufficient wind power potential in 13,130 km(2)(20%) of the land extent to maximize the renewable energy contribution in the national power supply. In addition, most of the potential areas were found in the sparsely populated coastal belt of the country. The proposed model has precious wind power predictive capacity. Hence, developed model could be used to estimate the wind power capacity in predicted areas. It is recommended to install wind power plants in possible areas to achieve more than half of the renewable energy target for 2030 by through wing power plants to generate electricity.
引用
收藏
页码:443 / 454
页数:12
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