A decision framework of low-speed wind farm projects in hilly areas based on DEMATEL-entropy-TODIM method from the sustainability perspective: A case in China. (15th December 2020) - Wu, Yunna; Liao, Mingjuan; Hu, Mengyao; Lin, Jiawei; Zhou, Jianli; Zhang, Buyuan; Xu, Chuanbo
Abstract: The development of low-speed wind farms (LSWFs) has been recognized as the most promising option for onshore wind power project in the future. However, existing research on hilly LSWFs is still insufficient, and site selection is a vital in the construction of LSWF projects. This paper proposes a decision framework to provide investors with guidance for LSWF site selection in hilly areas. First, an indicator system that complies with the peculiarities of hilly LSWF projects has been established from the sustainability perspective. Second, the indicator data are collected by adopting hesitant fuzzy linguistic term sets (HFLTSs) to ensure the completeness of the data. Third, considering the impact of subjective preferences and objective fairness on the indicator weights, a method combining the extended triangular intuitionistic fuzzy number-decision making trial and evaluation laboratory (TIFN-DEMATEL) method and the entropy weight method for multiple data types is used to determine the indicator weights. Fourth, an acronym in Portuguese for interactive multi-criteria decision-making (TODIM), which takes the psychological characteristics of decision makers (DMs) into account, is applied to rank alternative sites. Finally, a case study in the eastern China is illustrated to demonstrate the rationality of the decision framework. Highlights: A framework is established for location decision of low-speed wind farm projects in hilly areas based on fuzzy theories. A novel indicator system concerning the evaluation analysis is established from the sustainability perspective. The combination weights and the improved ranking method are applied to select the optimal alternative site. The fuzzy theories are utilized to ameliorate the collection and description of data information. An empirical study is provided to verify the practicability of the framework.