目前電力公司常以時間基準進行例行性維護，但因配電變壓器數量龐大及運轉狀況不一，難以確認維護效能，故本論文提出應用森林繁衍智能演算法於配電變壓器維護排程規劃，並將配電變壓器平均故障率及絕緣壽命減少百分比統整納入考量，因而可依各變壓器運轉狀況彈性調整維護週期。本文所提出之森林繁衍智能演算法，係以模擬森林樹木傳播種子之繁衍行為加以延伸建模，可適於求解最佳化問題。而為驗證本文所提方法之可行性，本文分別經由包含不同變壓器個數之系統進行模擬分析，同時與其他演算法進行比較。由測試結果可知，本文所提方法應用於維護排程規劃上，確具有高度可行性，並有助於規劃人員應用參考。

Electric power companies often perform the maintenance work at a fixed time interval, yet because of the large number of distribution transformers and various operating conditions, such a strategy may not be effective. This thesis, therefore, proposes to apply the forest optimization algorithm to form a maintenance schedule of distribution transformers, where both averaged failure rate and percentage loss of transformer insulation life are taken into consideration so as to reach a schedule of high flexibility. This forest optimization algorithm is developed based on the mimicking of seeding behaviors of forests, by which it is proved to be suitable for solving the optimization problem. To validate the feasibility of this approach, simulations have been made along with comparisons of other methods through systems of different number of distribution transformers. Test results demonstrate the feasibility of the proposed method for the maintenance scheduling applications, which can be served as useful references for power system planning engineers.

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