臺灣博碩士論文加值系統

本研究源於某汽電廠中一部汽輪機低壓段葉片受損，造成發電效率大幅降低，由於即將面臨夏季高電價時段，該廠經理人面臨該機組是否應立即停機檢修或以低效率繼續運轉，直到夏季高電價時段結束之困擾。
本文提出蒸汽渦輪機在異常情形下，利用基因演算法分別找出各狀況下最佳的排程及機組調度，並考慮在不同季節的時間電價、契約容量費率、及當機組發生臨時性故障時，其所對應的超約罰款、售電利益損失、檢修後重新啟動成本為何，並以該汽電廠近幾年機組異常次數及故障時間，找出其機組故障發生概率，再以此概率評估各機組損失期望值，作為該機組應立即停機檢修或以低效率繼續運轉之決策依據，此方法可供日後國內眾多汽電廠若遭遇相同狀況，將能迅速了解如何因應，並作為是否立即維修之判斷依據。

Broken blades of the steam turbine generating unit lead to low efficiency. Fears abound that cogeneration plants with broken blades are going to face high electricity rates of summer peak periods. During high-rate period, the problem which managers have to consider is how to decide between immediate shutdown for repair and low-efficient operation. As the first step in this study, the optimal schedule and economic dispatch, according to abnormal condition of the steam turbine generating unit, need to be examined in detail with the gene algorithm. The problem being to consider next are the amount penalty and benefit loss, which caused by the different time rates of various seasons and the expense of the contract capacity, and the amount cost of restarting the unit when a temporary incident occurring.
Broken units should be continuously operated or rapidly shutdown to repair on the grounds that the probability of the incident is evaluated by the incident number in past years. This study is very informative for managers have to consider is how to decide between immediate shutdown for repair and low-efficient operation of cogeneration plants with broken blades.

誌謝 I
Abstract II
摘要 III
目錄 IV
圖目錄 VII
表目錄 IX
第一章 緒論 1
1.1研究背景與動機 1
1.2研究系統介紹 3
1.3相關研究及本研究分析方法 4
第二章 非等熵效應與發電量分析 8
2.1簡介 8
2.2蒸汽動力系統 9
2.2.1熱力學基本觀念 9
2.2.2 熱力學第一定律 11
2.2.3 熱力學第二定律 12
2.2.4 郎肯循環 13
2.2.5 實際循環過程 16
2.2.6汽電共生系統實際循環 17
2.3抽汽背壓式蒸汽渦輪發電機 23
2.4抽汽冷凝式蒸汽渦輪發電機 27
2.5三號汽渦輪機於異常情形之效率及發電量 30
第三章 基因遺傳演算法 34
3.1 簡介 34
3.2基因遺傳演算法基本原理 34
3.3實數修正基因遺傳演算法 39
3.4應用基因遺傳演算法於機組排程調度 40
第四章 系統分析與數學模型 52
4.1 簡介 52
4.2 機組排程調度數學模型 52
4.2.1目標函數與限制式 52
4.2.2機組啟動成本 62
4.3 經濟調度數學模型 64
4.3.1目標函數與限制式 64
4.4 I/O Curve分析 72
4.4.1 汽輪機I/O Curve分析 72
4.4.2 鍋爐I/O Curve分析 80
4.5汽電廠機組排程調度 82
第五章 案例模擬與分析 85
5.1簡介 85
5.2備用電力費率計算 95
5.3案例一(夏季電價時段) 96
5.4案例二(非夏季電價時段) 111
5.5 以期望值準則為維修決策 125
5.5.1案例一、TG3是否立即維修之決策分析 130
5.5.2案例二、考慮TG3葉片製作完成時間之決策分析 133
5.6綜合討論 137
第六章 結論與建議 139
參考文獻 142
附錄A夏季時段實際運轉記錄 A1
附錄B非夏季時段實際運轉記錄 A5
附錄C TG3於夏季立即更換葉片 A9
附錄D TG3於非夏季立即更換葉片 A12
附錄E TG3於夏季異常運轉 A15
附錄F TG3於非夏季異常運轉 A19
附錄G TG3於夏季正常運轉 A23
附錄H TG3於非夏季正常運轉 A27

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