dc.description.abstract | The circular economy has gradually become a universal trend, and waste incineration and energy conversion for power generation have become an important source of power generation for renewable energy. From recent years, there has been an obvious breakthrough in power generation technology for waste heat treatment in various countries. At present, 24 incineration plants in operation have assisted domestic disposal of more than 130 million tons of general waste (including household and general business waste) by the end of 108, and its total power generation has reached 56.1 billion kWh. It shows that incinerators not only effectively solve domestic waste disposal problems, but also provide safe, reliable and stable renewable energy. Therefore, this study mainly discusses and analyzes the possible factors that affect the power generation of incinerators.
This research method is divided into two empirical models. First, for the power generation effect model, the least average method is used to estimate the best average power generation of the empirical results, in order for the model (3) 538 degrees (the input variable is household garbage and general business Waste), followed by the model (5) 471 degrees (the input item is the actual average calorific value of the waste), and then the model (4) 469 degrees (the input item is the actual maximum processing capacity of a single furnace). Immediately using the fixed effect analysis model to estimate the empirical results, the best average power generation is in order: model (4) 464 degrees (input variable is the actual maximum processing capacity of a single furnace), followed by model (5) 463 degrees (input The item variable is the actual average calorific value of waste), and then comes the model (3) 453 degrees (the input item variable is household waste and general business waste). The other model variables of the two are consistent in the order of their power generation from high to low.
The second part is the policy effect analysis model. The research method will use the difference in difference (DID) method for inferential analysis. That is, it is assumed that the policy group is not affected by the policy and the experimental group is affected by the policy. . According to the empirical results, the virtual variables of the time before and after the implementation of the policy are not significant, and the virtual variables affected by the implementation of the policy change are also insignificant, but the multiplication of the time before and after the implementation of the policy and the virtual variables affected by the implementation of the policy change is very significant. Before the policy change, power generation increased by 2.234 million kWh, and the increase was about 10% of the plant’s total monthly power generation. Therefore, the policy effect analysis model of this study overall estimates that the impact on the increase in power generation after its implementation as listed above is very significant. Therefore, in this study, the policy of collecting and transporting garbage from 7 days a week to 5 days a week was analyzed. According to the results of the difference analysis, the implementation of the policy change is positive and significant for the power generation of the waste incineration plant. | en_US |