| 摘要: | 循環經濟逐漸成為普世的潮流，廢棄物焚化處理並發電之能源轉換已成為再生能源重要產電來源。從近年廢棄物熱處理在發電技術上各國有了明顯的突破，即可窺其全貌。目前營運中24座焚化廠，截至108年底已協助國內處理約1億3仟多萬噸的一般廢棄物（含家戶及一般事業廢棄物），其總發電量亦高達561億度。顯示焚化廠不僅有效解決國內廢棄物處理問題，更提供安全、可靠、穩定的再生能源。因此，本研究主要探討及分析影響焚化廠發電量之可能因素。
本研究方法分兩個實證模型，首先為發電量效果模型以最小平方法推估實證結果其最佳平均發電量,依序為模型(3)538度(投入項變數為家戶垃圾及一般事業廢棄物)，其次為模型(5)471度(投入項是廢棄物實際平均熱值)，再來就是模型(4)469度(投入項為單爐實際最大處理量)。緊接以固定效果分析模型推估實證結果其最佳平均發電量，依序為模型(4)464度(投入項變數是單爐實際最大處理量)，其次是模型(5)463度(投入項變數是廢棄物實際平均熱值)，再來就是模型(3)453度(投入項變數為家戶垃圾及一般事業廢棄物)。兩者其他模型變數投入其發電量由高到低排列是一致的。
第二部為政策效果分析模型，研究方法會運用差異中之差異法(difference in difference,DID)作推估分析，即假設未受政策影響設為控制組，有受政策影響的設為實驗組。經實證結果政策實施前後時間之虛擬變數不顯著，受政策變動實施影響的虛擬變數亦不顯著，但政策實施前後時間與受政策變動實施影響虛擬變數之交乘相很顯著，即政策變動後較政策變動前發電量增加223.4萬度，增加之度數約為該廠每月總發電量之10％。所以本研究之政策效果分析模型整體推估如前述所列其實施後對發電量增加影響是非常顯著。所以本研究收運垃圾由每週七日調整為每週五日之政策，經差異分析結果，政策變動實施對垃圾焚化廠發電量是正向且很顯著。;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. |
