在本論文中，我們提出免疫演算法(Immune Algorithm)，來求解機組的維修排程問題。免疫演算法是應用抗體及抗原在免疫系統運作模式來求解最佳化問題，其中，抗體及抗原相當於最佳化問題中求解空間的一解和目標函數。利用抗體族群相似程度之關係，避免陷入局部最優解的可能性，使得在求解空間的搜尋過程中，能夠快速收斂且找到全域最佳解，結果顯示，免疫演算法對於機組的維修排程問題而言，應不失為一個很好的分析工具。 Recently, the reason that economics in Taiwan grow quickly makes load demands increase rapidly. In addition, the energy is hard up and the rise of environmental protection makes the difficulties of generating unit system, the spinning reserve is scant obviously. Therefore, the maintenance scheduling plays an important role within the planning of power system operation.
In this thesis, we plan the maintenance scheduling and levelize the spinning reserve rate to be the objective function. We also consider realistic constraints, such as maintenance alternate interval, crew constraints, power balance requirement, etc. Although departed methods such as dynamic programming, integer programming, and branch bound method can solve small scale problems, the rise in execution time of these methods is exponential with the number of generating units.
In this thesis, we render Immune Algorithm to solve the maintenance scheduling problem. Immune Algorithm is used to solve the optimal problem via the operation of the antibody and the antigen in immune system. The antibody is taken as the solution of the optimal problem and the antigen is taken as the objective function of the optimal problem. To prevent the local optimal solution, we can find out the global optimal solution rapidly during searching for solution space by the diversity of antibody populations. The result obtained from analysis proves that Immune Algorithm is a good method for maintenance scheduling problem.
