Machine learning-enhanced fuzzy framework for prioritizing financial risk management techniques in renewable energy projects

Abstract Appropriate actions should be taken to minimize the financial risks of renewable energy investment projects. Addressing this issue can mitigate many problems, such as financial losses, bankruptcy of the project, noncompliance with legal rules and a decrease in operational efficiency. Therefore, applying the right risk management techniques is vital to the success and sustainability of projects. This study tries to find the priority risk management techniques that should be applied to effectively manage financial risks in renewable energy projects. In this context, a new fuzzy decision-making model based on machine learning is developed in this study. The first stage of this model is related to the construction of the expert-weighted decision matrix by using machine learning methodology. Moreover, in the second stage, selected criteria are weighted via Fermatean fuzzy MEREC methodology. MEREC is a multicriteria decision-making technique used to determine the objective weights of criteria. Third, risk management tools are ranked by Fermatean fuzzy RATGOS. RATGOS is a multicriteria decision-making approach that allows alternatives to be ranked by evaluating their performance holistically. The most significant contribution of this manuscript is that a novel model is constructed to understand the most critical financial risk management actions for the effectiveness of renewable energy investment projects. The weights of the decision makers can be computed by using a machine learning approach. Integrating RATGOS and MEREC techniques with Fermatean fuzzy numbers is another element that increases the quality of the proposed model. These issues contribute significantly to increasing the effectiveness, validity, and consistency of the model. The cash flow rate of the project is found to be the most important factor in determining the risk management tool. On the other hand, the most sustainable tool for financial risk management in renewable energy is financial derivative instruments.