Investigating risks in renewable energy in oil-producing countries through multi-criteria decision-making methods based on interval type-2 fuzzy sets: A case study of Iran

Abstract

Despite the importance of relying on renewable energy sources, oil-producing countries, especially Iran, encounter numerous risks associated with the generation of such energy sources. The present study investigated the risks in renewable energy in Iran. As the first investigation addressing this problem in Iran, the study methodologically improved the probability-impact matrix by employing multi-criteria decision-making (MDCM) methods and using interval type-2 fuzzy sets. The results showed that most important macro-level risks facing Iran's renewable energy generation were “inflation and price fluctuations”, “corruption”, “complex licensing procedures”, “research and development and the capacity of domestic technology”, “sanctions”, “exchange rate fluctuations”, and “property rights and contractual risks.” Following these macro-level risks, there were important specific risks both in the general field of energy and renewable energy including “geographical risks”, “non-renewable energy prices”, “electricity prices”, “a lack of a coherent renewable energy policy”, “the impact of climate change on revenue rates”, and “financial risks.” Finally, based on the outcome of the probability-impact matrix combined with the hierarchy of risks, the two highest-priority risks are “complex licensing procedures” and “non-renewable energy prices.” To respond to such risks, it would be necessary to formulate coherent and integrated policies.