Abstract
Intuitionistic Fuzzy Set theory can be used in conjunction with environmentally extended input–output based life cycle assessment (EE-IO-LCA) models to help decision makers to address the inherent vagueness and uncertainties in certain sustainable energy planning problems. In this regard, the EE-IO-LCA model can be combined with an intuitionistic fuzzy set theory for a multi-criteria decision making (MCDM) application with a set of environmental and socio-economic indicators. To achieve this goal, this study proposes the use of the Technique for Order of Preference by Similarity to Ideal Solution method to select the best wind energy alternative for a double layer MCDM problem, which requires expert judgments to simultaneously apply appropriate weighting to each life cycle phase and sustainability indicator to be considered. The novelty of this research is to propose a generic 9-step fuzzy MCDM method to solve sustainable energy decision-making problems using a combination of three different techniques: (1) an intuitionistic fuzzy entropy method to identify the individual importance of phases and criteria; (2) an IFWGA operator to establish a sub-decision matrix with the weights applied to all relevant attributes; and (3) an IFWAA operator to build a super-decision matrix with the weights applied to all of the life-cycle phases considered. This proposed method is then applied as a case study for sustainable energy planning, specifically for the selection of V80 and V90 onshore and offshore wind turbines to be installed in the United States. It is strongly believed that this methodology will provide a vital guidance for LCA practitioners in the future for selecting the best possible energy alternative under an uncertain decision-making scenario.
6. Conclusions and future work
In this study, an intuitionistic fuzzy TOPSIS method was proposed for evaluating wind energy technologies in the US First, the results of an EE-IO-LCA analysis are used to quantify the overall environmental and socio-economic impacts of onshore and offshore wind turbines at each life cycle phase, after which the decision makers evaluated each energy alternative based on the TBL sustainability impacts of each LCA phase. Second, the evaluation results were obtained, taking into account the applicable weight of each specified criterion and each life cycle phase, also using IFWAA and IFWGA operators to account for the influence of individual decision makers on alternatives and the overall group influence on the selection of criteria and life cycle phases for further analysis. Finally, the proposed method was applied to a real case study in which the aim was to rank the performance of wind turbines installed in the US Based on expert evaluations, the manufacturing phase has the highest weight for ranking the sustainability performance of wind energy alternatives, followed by the construction and manufacturing phases, respectively, while the use phase has the lowest weight. Among the environmental impact categories, GHG emissions have the largest importance out of all of the indicators considered in this analysis. The V90 offshore wind turbine was ranked the highest out of the four wind turbine alternatives compared in this study. In addition, wind turbines with a higher power generation capacity (in this case, the V90 onshore and V90 offshore turbines) were found to be better alternatives than those with a lower capacity (the V80 onshore and offshore).
