China’s electricity market is in the environment for a round of new electric power reform, energy planning and transformation and the carbon market construction. The current market players are in urgent need of implementing their own energy saving and emission reduction actions. Relatively extensive and systematic researches on the assessment of the energy saving and emission reduction effects for the power plants, power grid companies, and technical equipment have been carried out at home and abroad. However, there are still vacancies in the researches on those for electricity retailers emerged on the sales side. Based on the carding and analysis of related policies and guidance, in this paper, relevant indicators are considered to build the evaluation indicator system of the energy saving and emission reduction effects for electricity retailers. The combination weights are gained by means of analytic hierarchy process and entropy weight method. Then, after the combined empowerment of indicators, the multi-level fuzzy comprehensive evaluation of energy saving and emission reduction effects for electricity retailers is conducted. Finally, choosing 10 electricity retailers (numbered from A to J) as evaluation objects, this model is used for obtaining the evaluation results and ranking of energy saving and emission reduction effects of electricity retailers, which provides reasonable ideas for the construction of evaluation indicator system and effective comprehensive evaluation methods of energy saving and emission reduction effects for market players in the electricity sales side. The results of example analysis show that, from a single dimension, the best electricity retailers in market transactions, technical means, integrated energy services, management system, and social responsibilities are followed by B, J, D, G, C, or I. However, from a global perspective, the sorted evaluation results are D, J, I, A, H, G, E, B, F, and C, which reflects the overall energy saving and emission reduction effects of electricity retailers through the two-level fuzzy comprehensive evaluation.
Read full abstract