A two-stage evaluation and optimization method for renewable energy development based on data envelopment analysis

Different kinds of renewable energy resources have developed rapidly. For renewable energy planning, it is meaningful to assess the comprehensive performances of different schemes and then to determine the optimal design of the energy structure. This paper presents a two-stage method for the comprehensive evaluation and structure optimization of renewable energy plans. First, in the evaluation stage, multiple indexes from different aspects are taken into consideration, of which each qualitative index will be converted quantitatively, using the intuitionistic fuzzy number to describe the fuzziness and ambiguity in a qualitative index. Then, the super-efficiency data envelopment analysis model is used to determine the comprehensive performances of different plans based on the concept of relative efficiency. Next, in the optimization stage, an optimal model combining multiple renewable energy resources is established based on the relative efficiency results of the evaluation process. This model aims at the maximum efficiency as a whole and can be used to optimize the proportions of different renewable energy resources. Finally, a real case of renewable energy development from a province in China is given to demonstrate the feasibility and effectiveness of the proposed method in this paper. The results show that it can overcome the shortcomings of the traditional basic model, obtain more objective evaluation results and provide beneficial references for the strategy making of renewable energy development.