Risk Evaluation Model of Wind Energy Investment Projects Using Modified Fuzzy Group Decision-making and Monte Carlo Simulation

Abstract

The recent increasing trend of investments in wind energy projects to support sustainable development requires an appropriate risk evaluation model to ensure the success of these projects. Early studies focus on opinion and discussion from subject matter experts. However, the expertise level in the subject is varied, and evaluation without considering expert competency can cause biased results. On the other hand, most of the project cost estimation models do not consider uncertainty in all cash flow parameters. In response, this article proposes a model that evaluates risks in wind energy investment projects by considering the knowledge and background of experts. Then, an integrated model of risk evaluation and cost estimation is developed. The model consists of three main stages: risk identification based on a systematic literature review (SLR); risk analysis phase 1 based on a modified fuzzy group decision-making; and risk analysis phase 2 based on a Monte Carlo simulation method. The main advantages of the proposed model are: (a) providing a comprehensive risk identification in wind energy investment projects; (b) using a modified fuzzy model to improve the risk assessment process by considering the expert competency in wind energy projects; and (c) establishing an integrated model to evaluate the cash flow of the investment. A wind farm in the Middle East is selected as the case study to examine the usability and practicality of the proposed model. The results show that the most important risks are ‘change in regulation and policy’, ‘dependency on the international market for importing raw materials’ and ‘market competitiveness’. On the other hand, the financial assessment under uncertainty shows that the profitability of the investment can be varied, and it emphasises the importance of an appropriate risk management process to guarantee the success of the investment.