The blind expansion and increasing carbon emissions of the coal-fired power generation industry in China have attracted wide attention at home and abroad. To detect the technical ineffectiveness in the coal-fired power generation industry and the effects of carbon emission reductions, this study developed energy congestion models using data envelopment analysis (DEA). Energy congestion is classified into undesirable energy congestion (UEC) and desirable energy congestion (DEC) under natural disposability and managerial disposability. The UEC and DEC models were used to identify energy congestion, measure the amounts of UEC and DEC, and analyze the sources of inefficiency for regional coal-fired generation industry in China from 2004 to 2013. Our empirical analysis revealed: i) The UEC of coal-fired generation industry has occurred in many regions, most of which are less-developed areas. This indicates that energy is wasted in coal-fired generation industry due to congestion inefficiency. ii) DEC has occurred in a few regions and did not occur in 2013. These provinces where DEC occurred may have a high potential for eco-technology innovation. The method of energy congestion measurement proposed in this study and the research conclusion have reference effect on regional energy conservation and eco-technology innovation.