二氧化碳為造成全球暖化與海平面上升的溫室氣體中最重要的成分,據研究發現賴於發電的火力機組為最大的二氧化碳排放源,其將使得大氣層中的熱量無法逸散至外太空,進而造成全球溫度逐漸上升。 機組排程是一個在排程的時間內以最經濟方式來排定機組狀態與決定機組發電量的問題,其目的在於使總發電成本最小並同時滿足負載需求、備轉容量需求與一些個別限制條件;求解機組排程必須迅速而有效,才能做為發電策略的參考依據,因此如何選擇一個有效且穩定的求解方法來求解機組排程問題已成為一種重要的課題。 本論文研究重點在於機組排程與 配額交易市場進行研究,並導入配額交易市場機制。本論文採用一種較新穎的量子蟻拓演算法,此演算法是融合量子演算法和蟻拓演算法所實現的一種新的演算法,此演算法採用量子機率向量的編碼方式,同時使用量子位元、量子疊加狀態的思想,而量子疊加狀態的特性能使排列更多元化,而特性是將解的狀態以特定的機率方式表達出來,藉此有效提高最佳解搜索的能力。本論文同時採用量子蟻拓演算法為基礎來建立一個求解碳交易市場機制;最後以本論文所提出的量子蟻拓演算法對二個案例做分析與討論,分別以IEEE 30-Bus、IEEE 57-Bus的電力系統做24小時負載的線路損失最佳化機組排程,並和動態規劃法,蟻拓演算法做比較,模擬結果驗證量子蟻拓演算法可以達到在符合碳排放限制條件下達到較低發電成本及最短運算時間,因而適合將此方法使用在求解包含碳交易之短期最佳火力機組排程。
Carbon dioxide (CO2) is the most important component of Greenhouse Gas (GHG) that causes global warming and sea-level rising. Thermal power plants dominate electric power generation in the world, and has been reported to be the major contributor of emission. The purpose of unit commitment for a specified power system is to determine the generator status, electrical total power outputs to satisfy load demands, spinning reserves and constraints in the most economic way. To be a good reference for a power generation policy, the process of unit commitments must be fast and effective. How to find out an effective and stable solution method for unit commitment is a major course for modern power system. This thesis proposed a research focused on the relationship between the carbon trading scheme and unit commitment problem. This thesis combines Quantum Algorithm and Ant Colony System to present a new algorithm, called Quantum Ant Colony System . The QACS(Quantum Ant Colony System) uses the coding method of quantum probability vector, and also uses the quantum bit and quantum superposition at the same time. The characteristic of quantum superposition can make code express more flexible. The probability expression characteristic can expresse the solution state by certain probability. It can raise the ability of findy the optimal solution. In this thesis, QACS is also carried out to solve the carbon trading market problems. Two cases including IEEE 30-bus and IEEE 57-bus have been studied and analyzed for a short-term unit commitments. These results have been comparied with other methods i.e. Dynamic Programming and Ant Colony System. It shows that QACS proposed in this thesis is useful and efficient method in short-term unit commitments.