臺灣博碩士論文加值系統

摘 要

臺灣是一個飼養豬隻高密度的國家，若能將豬隻廢棄物有效的回收再利用轉換成能源，不僅可以有效降低甲烷的溢散亦可獲得再生能源的使用。一般來說，大型集中式沼氣廠具有較高的沼氣產量及較高的利潤。台灣飼養豬隻方式以小規模居家飼養為主，生質能源的再利用產值偏低，所以需要利用良好的豬糞回收集運系統運至沼氣廠。由於不同的豬糞量將影響沼氣生成量的多寡，使得投資風險的提高，有鑒於此，本研究利用灰規劃幫助決策者處理模糊不清的訊息。
本研究利用混合整數規劃與灰規劃模型進行養豬業溫室氣體減量分析。本研究自行訂定養豬業的溫室氣體削減目標，其目標為10%、20%、30%、40%、45%，再針對13個研究區域經由多準則決策篩選出開發順序。研究結果顯示，當削減10%需要開發區域2;當削減20%需要開發區域2、11、1; 當削減30%需要開發區域2、11、1、6、13; 當削減40%需要開發區域2、11、1、6、13、9、2; 當削減45%需要開發區域2、11、1、6、13、9、2。

Taiwan has a high potential to develop renewable energy from pig’s waste because of its high density of pig farms. Taiwan also faces the pressure of reducing the emission of greenhouse gas. Converting pig manure into energy is a technology that not only reduces the emission of methane it also produces renewable energy at a low cost. But most of pig farms in Taiwan are too small to have profit by directly using biogas on site. Generally the large and centralized biogas plant has higher yield on biogas and better profit than that of small one. So Taiwan needs a good shipping system to gather manure distributed over small pig farms into the large biogas plant.
The ambiguous yield rate of biogas and the variable amount of swine manure will induce a risk of investment on this renewable energy system. This study proves that grey theory is able to help decision maker treat the ambiguous information. For the duty of GHG reduction to pig-farming industry, this paper fulfilled the optimization analysis of GHG reduction based on a mixed integer and grey programming model. The developing priority of 13 hauling zones in the Southwest Taiwan was figured out. Seven hauling zones were suggested to be developed for complying with the goal of 45% off of GHG.

Content
Acknowledgements----------------------------------------i
Chinese Abstract----------------------------------------iii
English Abstract----------------------------------------iv
Content-------------------------------------------------v
List of Tables------------------------------------------vii
List of figures-----------------------------------------xiii
Chapter 1 Introduction----------------------------------1
1.1Background and motivation----------------------------1
1.2Purpose----------------------------------------------2
1.3Flow Chart-------------------------------------------3

Chapter 2 Literature Survey-----------------------------4
2.1The characteristic of swine industry in Taiwan-------4
2.2The influence of swine breeding industry to the
greenhouse gases-------------------------------------11
2.3The present scenario and forecast of renewable energy-13
2.4Swine manure as an energy source----------------------21
2.5Gray System Theory------------------------------------26
Chapter 3 Methodology------------------------------------30
3.1Geographical information system-----------------------32
3.2LINGO 10.0 programming language-----------------------32
3.3System Construction-----------------------------------33
3.3.1System analysis-----------------------------------35
3.3.2Model modification--------------------------------37
3.4The Grey decision-------------------------------------46
3.5Multi-objective decision-making-----------------------47

Chapter 4 Conclusion and Discussion----------------------50
4.1The Multi-objectives decision-------------------------50
4.1.1The sensitivity analysis--------------------------53
4.2Decide the optimal developing sequence----------------55
4.3The optimized analysis of the hauling plan in every
scenario----------------------------------------------60
4.3.1Scenario A----------------------------------------60
4.3.2Scenario B----------------------------------------88
4.3.3Scenario C----------------------------------------117
4.3.4Scenario D----------------------------------------145
4.4The reduction of the greenhouse gas at the swine
industry----------------------------------------------178

Chapter 5Conclusion and Suggestions----------------------193
5.1Conclusion--------------------------------------------193
5.2Suggestions-------------------------------------------194
References ----------------------------------------------195

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