Regional Scale wind farm and solar farm suitability assessment using GIS-assisted multi-criteria evaluation

被引:239
|
作者
Watson, Joss J. W. [1 ]
Hudson, Malcolm D. [1 ]
机构
[1] Univ Southampton, Fac Engn & Environm, Ctr Environm Sci, Southampton SO17 1BJ, Hants, England
关键词
Renewable energy; Suitability study; Multi-criteria decision making (MCDM); Analytical hierarchy process (AHP); United Kingdom (UK); RENEWABLE ENERGY-SYSTEMS; DECISION-MAKING; ENVIRONMENTAL IMPACTS; PHOTOVOLTAIC SYSTEMS; PROTECTED AREAS; SELECTION; DESIGN;
D O I
10.1016/j.landurbplan.2015.02.001
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
As global growth in renewable energy projects accelerates, site identification will come to the forefront, where a key consideration is to minimise the environmental impact of the development. A large area of southern England (17,094 km(2)) was assessed for suitability for wind and solar farm developments in three stages using geographic information systems. A multi-criteria decision making framework incorporating an analytical hierarchy process involving expert stakeholders was applied, which is a novel approach for this type of study. A binary constraint layer was created identifying entirely unsuitable locations. A factor layer was developed to indicate suitability in relation to a range of variables. Suitability layers for wind farm and solar farm development were then created covering the region. The environmental constraints used in the model accounted for over 60% of the study area for both wind and solar developments. Suitability for wind energy was generally low, with only 0.5 km(2) accounting for the 'most suitable' category. Solar suitability was higher overall; and a greater area (294 km(2)) within the 'most suitable' category, suggesting the region is better suited for solar farm developments. Stakeholder input resulted in higher weightings for economic considerations for the solar model, prompting the most suitable areas to coincide with locations of the national grid connections. A sensitivity analysis indicated that model was generally reliable. This method can be used to assist appropriate site selection for onshore renewable energy projects across large geographical areas, helping to minimise their environmental impacts. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:20 / 31
页数:12
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