本文將針對大量風力與太陽能併入獨立電網系統後，考量火力機組彈性調度之升降載率於短時間內所需應付的負載變動進行最佳化機組派。其中，發電機所需參數將以電力公司提供的實際機組進行分析；本文將以改良優先順序法搭配過濾隱枚舉法、慣性權重粒子群演算法、模擬退火法、廣義乘子結合隨機可行方向法，用於求解電力系統中具有大規模的非線性混合整數規劃的機組調派問題，以避免在搜尋時陷入區域解或是不可行解區間，並比較這些演算法求解的速度、精確度的優劣，演算法部份將以Matlab進行編譯。
本文選定20台火力發電機組為排程機組，並在30分鐘與10分鐘內補足因再生能源不穩定所造成之缺口，最後發現以廣義乘子結合隨機可行方向法求得的解皆較其他演算法精準與快速。未來可藉由本文提出之機組排程，來穩定因再生能源驟降而造成之電力缺口。

This thesis focuses on optimizing the unit commitment by considering the load change in a short time, short-term rate of change for units and flexible scheduling of thermoelectric units after a large generation of wind and solar energy is connected into the independent power system. The parameters required for the generators will be analyzed by the actual unit parameters provided by the utility. The improved priority method with filtering the hidden enumeration method, the inertia weight particle swarm algorithm, the simulated annealing method, the generalized multiplier combination stochastic feasible direction method are used for solving the optimization unit commitment problem of large-scale nonlinear mixed integer programming in power system in order to avoid falling into a regional solution or an infeasible interval during a search. The solving speeds of these algorithms and advantages and disadvantages of accuracy are compared. All of algorithms are compiled in Matlab.
20 sets of thermal power units are selected for the unit commitment in this thesis. The instability caused by renewable energy is cancelled within 30 minutes or 10 minutes. Finally, the solution obtained by the generalized multiplier combined with the stochastic feasible method is accurate and fast compared with other algorithms. In the event of a shortage of electricity due to a sudden drop in renewable energy, the unit commitment proposed by this thesis can be used to stabilize the system.

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