Fuzzy cognitive maps based decision support system for renewable energy investments

Abstract

Today, renewable energy sources such as hydropower, biomass, geothermal, solar and wind play a major role in meeting the energy requirements in terms of economics and politics aspects for any country. The selection of the optimum renewable energy source provides guidelines to practitioners for sustainable planning of local, national, regional and global energy systems. The selection process is a multi-criteria decision making problem and requires taking into account social, technological, economic, environmental, and political aspects. In this study, a decision support system consisting of combined Fuzzy Cognitive Mapping (FCM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodology is proposed for the planning of national renewable energy investments of the developing countries. FCM draws cognitive maps which intend to model the different aspects of the behavior of complex systems. Therefore, FCM method is applied to explore and prioritize the critical factors which are likely to influence renewable energy investment decisions. Also, several maps obtained from the experts who have diverse backgrounds in the public and private sectors are integrated into a map. Then, TOPSIS method is applied to rank renewable energy alternatives and select best one. In order to demonstrate the usefulness of the proposed methodology, an illustrated example of Turkey is performed.