近年來，非再生能源汙染與破壞環境的議題受到高度的關注。如何有效的制定相關政策刺激再生能源的運用，將是一項值得探討的議題。為了因應這個議題，政府應當制定相關非再生能源使用之稅金懲罰，並推動再生能源使用補助等方案，希望藉此提高再生能源使用率；但此稅金與補助的制定除了影響政府如何運作之外，亦牽涉到被徵收以及受費率補貼之業者。因此，本研究利用兩階層數學規劃模型解析台灣地區再生能源利用最佳化的問題，其中高階決策者為政府，而低階決策者則為台灣電力公司。政府的目標為平衡基金預算，而低階台灣電力公司業者則期望獲得利潤極大化。由於雙方的目標不一致但決策又彼此互相影響，故本研究即利用此一互動關係建立兩階層之模型。本模型為兩階層非線性規劃問題，為簡化求解過程，首先以KKT最佳化條件轉換以及變數替換，將此模型轉換為一 0-1非線性規劃問題，再以Lingo一般化數學規劃軟體求解。透過此模型除了可反映出其目標衝突的本質，並可利用數值案例所得的結果進行分析。此外，本研究更進一步探討台灣電力公司體與政府在利益產生衝突時應如何找到最佳的合作策略，使得兩者可以進行合作，以達到兩者目標最佳化之結果。

The consumptions of non-renewable energy are inevitably accompanied by human activities that not only pollute and damage the environment, but also exhaust the natural resources and the environment issue is arouse. How to use the policy to promote the usage of renewable energy, it must be systematically studied and established a reasonable fee rate. In this thesis, we attempt to optimize the operations of the government through the decision of a subsidy for renewable energy industry. The hierarchical and interactive nature between the two parties is modeled by bi-level programming (BLP), where the government plays the higher level decision maker while Taipower is the lower level counterpart. Since the objectives of both levels are usually conflict, the BLP model can simulate the actual decision-making process and obtain an optimal solution under an interactive behavior. Furthermore, this study presents a detailed discussion about how to find an efficient compromise solution so that the decision makers can cooperate and achieve satisfactory results. In order to solve the problem by optimization software, the BLP problem is transformed into a single level problem via Karush-Kuhn-Tucker (KKT) optimality conditions and further transformed into a 0-1 mixed integer programming problem by variable substitution. The problem is then solved with real-world data, and the obtained solutions are analyzed. The results suggest that the proposed approach can improve the operations of both the government and the Taipower.

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