Infrastructure projects for harnessing renewable energy (e.g., wind farm projects) have recently gained popularity because of their low adverse impact on the environment. However, it is challenging to perform risk assessments for these projects because data are either scarce or of low quality. Therefore, risk assessments for renewable energy infrastructure projects must rely on expert knowledge and can be treated as multi-criteria group decision-making (MCGDM) problems. In group decision-making problems, consensus must be built between individual decision makers who each supply their own preference indices for decision alternatives. This paper introduces a novel technique for consensus building in MCGDM problems using the principle of justifiable granularity, thereby producing an interval-valued fuzzy set that represents the aggregated value of the preference indices assigned to decision alternatives by decision makers. The preference indices obtained from each expert are realized through the analytic hierarchy process (AHP). In this paper, the introduced MCGDM technique is used to assess risk for wind farm projects. First, a context-specific work breakdown structure for wind farm projects is developed. Second, construction work packages are ranked based on how much they contribute to the overall risk or uncertainty involved in achieving the project objectives of time, cost, quality, and safety.
|Publication status||Published - Jun 2019|
|Event||2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019 - New Orleans, United States|
Duration: 23 Jun 2019 → 26 Jun 2019
|Conference||2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019|
|Period||23/06/19 → 26/06/19|