Risk assessment of renewable energy projects using a novel hybrid fuzzy approach

Abstract

ABSTRACT The majority of countries attempting to switch from conventional energy sources to renewable energy sources have decided to make significant investments in these projects. This study aims to identify critical risks for renewable energy (RE) investment projects using a novel hybrid approach based on interval type 2 hesitant fuzzy sets (IT2HFS) and alpha level sets. The hybrid model integrates interval type 2 hesitant fuzzy (IT2HF) DEMATEL-based analytic network processing (DANP) with qualitatively flexible multiple criteria (QUALIFLEX). In the first stage, the dimensions and criteria for RE investment risks are defined. In the second stage, the importance levels of these attributes are assessed. Finally, the risk awareness levels of strong, average, and weak investors are graded using the IT2HF-QUALIFLEX. The results indicate that the cost of the investment and technological maturity are the substantial criteria for RE investment projects. Also, the sensitivity analysis is conducted, and the stability of the results for the proposed approach is verified. Eventually, five different scenarios are designed, and the results are interpreted accordingly. The findings of this study will be valuable to investors, enterprises, and authorities involved in evaluating their investment in RE projects.