An Interactive Preference Disaggregation Method for Renewable Energy Project Sorting With Multiple Experts

Abstract

To mitigate power supply and demand imbalances and achieve carbon reduction goals, provinces in China have recently been promoting the development of renewable energy (RE) projects. Multiple criteria analysis is commonly employed for RE project assessment as energy considerations from multiple perspectives are required. To support governments’ reserve work on RE projects and facilitate their smooth development, this study introduces an interactive preference disaggregation approach for RE project sorting. The sorting model accounts for the influence of different experts. To resolve contradictory preferences among experts, mathematical programming models that can ensure the reliability of the decision-making results are constructed for conflicting analysis and adjustment strategy recommendations. The proposed approach achieves a certain form of “cognitive convergence” through iterative processes and finally derives sorting results aligning with the perceptions of all experts. In addition, to promote the high-quality development of RE projects, an optimization model is given to generate improvement strategies for inferior projects based on the sorting results. An illustrative example of solar photovoltaic project sorting is provided to validate the applicability of the proposed approach.