Eco-econo-efficiency Based Quota Allocation towards Coal De-capacity Reform Implementation: Case Study from China

Business School, Sichuan University, Chengdu 610065, People’s Republic of China

^* e-mail: cwlyu@scu.edu.cn

Abstract

Reducing coal capacity is an essential part of China’s energy transition, with the formulation of a coal de-capacity quota allocation plan the key to achieving its coal overcapacity reductions. This paper presents a coal decapacity quota allocation mechanism based on a comprehensive consideration of the ecological, economic, and efficiency concerns at the enterprise level to deal with China’s coal overcapacity problems. A multi-objective optimization quota allocation model based on equilibrium strategy is established for the decision makers, in which the ecological concerns are measured by three waste emissions, the economic concern assessed based on the coal de-capacity costs, and the efficiency measured using a DEA method. By introducing a membership function method, the model is transformed into its equivalent single form and solved using LINGO software. To prove the practicality of the model, a case analysis was conducted. The results indicate that due to the different ecological and economic level in each coal mine, the allocation ratio of each coal mine for coal de-capacity is quite different. Compared with the government plan to reduce overcapacity in the mining area, the ecological benefits of the enterprise’s strategy increases by 4.69 million tonnes, and the economic costs has reduced 42.79 million CNY. A sensitivity analysis under different parameters for the decision maker preferences implemented, and the production efficiency changes in the mining areas analyzed and compared. It was found that although coal capacity reduction quota allocations can be affected by the decision makers preferences, the comprehensive ecological, economic, and efficiency objectives at small scale, low-efficiency coal mines should take on additional coal capacity reduction tasks. After the optimal allocations, the efficiencies in all mining areas reached an optimal value.