火力發電廠在台灣對整體電力系統扮演重要地位，但它也排放了大量的溫室氣體，其中二氧化碳為溫室氣體中導致全球氣候暖化及海平面上升的主因。本論文探討公營發電業二氧化碳限制下與發電規劃策略間的關係，提出一改良式粒子群演算法求解獨立發電業參與下之發電擴建規劃策略。當擴建一新的發電機組時，公營發電業需同時在獨立發電業與環境因素下做出抉擇，問題亦加入評估二氧化碳減少及可靠度議題，在滿足所有限制中符合負載端需求。改良式粒子群演算法有助於避免提早收斂情況的發生，測試結果顯示在發電規劃策略上改良式粒子群演算確實為一個有效的決策方法。
在競爭的市場中，發電擴建規劃為一重大的決策，所有的公營發電業及獨立發電業均欲求在符合負載需求及可靠度準則下尋求最大利益。為更好的經濟和效率，公營發電業將考慮在新擴建機組與向獨立發電業購電間做出抉擇。

Thermal power plants dominate electric power generation in Taiwan, which causes high Green House gases (GHG) emissions. CO2 is the most important greenhouse gas that cause global warming and sea-level to rise. This paper faces the relationship between CO2 limitation and power generation expansion planning (GEP) for the utility. Modify Particle Swarm Optimization (MPSO) is presented to determine the generation expansion planning strategy of the utility with independent power providers (IPPs). The utility has to take both the IPPs’ participation and environmental impact into account when a new generation unit is expanded. This problem also takes into account the CO2 reduction and reliability issues, while satisfying all electrical constraints simultaneously from the supply point of view. MPSO scheme was improved to avoid getting a premature answer. Testing results shows that MPSO can offer an efficient way in determining the generation expansion planning.
Generation expansion planning is an important decision-making activity in a competitive market, all utilities including IPPs need to maximize the profit while meeting the load demand with a pre-specified reliability criterion. In order to achieve the objective, utilities will perform the generation expansion planning to determine the minimal-cost capacity power addition. For better economy and efficiency, they will consider options of either constructing new generating units or purchasing electricity from other utilities or IPPs.

中文摘要 I
Abstract II
目錄 III
圖目錄 VI
表目錄 IX

第一章 緒論 1
1-1 研究背景與動機 1
1-2 文獻回顧 4
1-3 論文貢獻 5
1-4 論文章節概要 7

第二章 電力市場之解制 8
2-1 自由化電力市場架構 8
2-2 電力市場架構與運作關係 13
2-2-1綜合電業模式 13
2-2-2發電業開放模式 14
2-3 電力買賣交易 16

第三章 發電擴建規劃模型 19
3-1 負載曲線建立 19
3-2 可靠度分析 20
3-2-1備轉容量評估 22
3-2-2缺電機率與缺電量評估 23
3-3 發電機二氧化碳排放模型 29
3-4 問題描述與數學模型 33

第四章 最佳化演算法之探討與改良 37
4-1 典型基因演算法 37
4-2 粒子群演算法 41
4-2-1粒子群演算法 42
4-2-2求解整數規劃問題之粒子群演算法 45
4-3 加速度形式之粒子群演算法 47
4-4 混合基因觀念之粒子群演算法 49
4-5 混合基因觀念之加速度粒子群演算法 53
4-6 問題模擬流程 55

第五章 模擬測試與結果 59
5-1 演算法測試結果 59
5-2 短程發電擴建規劃 68
5-3 中程發電擴建規劃 76
5-4 長程發電擴建規劃 84

第六章 結論與未來的研究方向 92
6-1 測試結果討論與結論 92
6-2 未來研究的方向 93

參考文獻 94

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