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Wind farm site selection from the perspective of sustainability: A novel satisfaction degree‐based fuzzy axiomatic design approach
International Journal of Energy Research ( IF 4.6 ) Pub Date : 2020-12-03 , DOI: 10.1002/er.6256 Jianghong Feng 1
International Journal of Energy Research ( IF 4.6 ) Pub Date : 2020-12-03 , DOI: 10.1002/er.6256 Jianghong Feng 1
Affiliation
As a clean and renewable energy resource, wind energy is the most mature, environmentally friendly, and most commercially developed new energy resource in the world. Therefore, it is of great importance to determine the best location of wind farms to ensure the sustainable development of wind energy. However, since wind farm site selection often involves multiple criteria, which include qualitative and quantitative criteria, there may be conflicts between these criteria, so wind farm site selection is a complex multi‐criteria decision‐making (MCDM) problem. Therefore, the objective of this study is to propose a novel integrated MCDM approach using a fuzzy analytic hierarchy process and satisfaction degree‐based fuzzy axiomatic design (AD) to determine the optimal onshore wind farm site under a hybrid decision information environment. First, based on the literature review and experts' opinion, the evaluation index system for wind farm site selection is built from a sustainable perspective, which includes geographic, technical, economic, social, and environmental criteria. Second, fuzzy analytic hierarchy process is applied to determine criteria weights. Third, the satisfaction degree‐based fuzzy AD is employed to evaluate and rank alternatives under a hybrid decision information environment. Finally, a case study is used to illustrate the reliability and advantages of the method proposed in this paper. In addition, the information content of each alternative is calculated by aggregating the evaluation matrix of experts, and the results are IC1 = 0.058, IC2 = 0.096, IC3 = 0.16, IC4 = ∞, IC5 = ∞, and IC6 = 0.226. Then the satisfaction degree of each alternative is S1 = 0.629, S2 = 0.545, S3 = 0.501, S4 = 416, S5 = 389, and S6 = 0.463. Thus, the best wind farm site is A1. Moreover, the results show that the method proposed herein is flexible and can effectively deal with the wind farm site selection problem. Although this paper chooses China as a case study, the proposed method herein is also applicable to other countries or regions.
更新日期：2020-12-22
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