為因應電力自由化的趨勢，台灣電力公司於2014年開始持續開發短期日前市場機組排程最佳化程式。本研究為使此機組排程程式之水火協調更加完善，便在其架構基礎上新建大甲溪串流式水力發電模型，而水力發電通常需要為期至少一週的規劃週期才能有效反映其水文及運轉需求，但在模型複雜度提高且規劃時間範圍需加長的情況下會衍生模擬時間過長的問題。本研究於是採用機組聚類的概念將模型改建為聚類機組排程模型，藉由減少機組發電組合使排程程式能夠以較短的模擬執行時間完成中期機組排程。經由模擬案例顯示，在正常無缺量的情況下，採用聚類機組模型所得出的排程結果與詳細模型的結果差異不大，但明顯加快了收斂速度，達到縮短執行時間的目的。

In response to the trend of electricity liberalization, Taiwan Power Company (Taipower) has been developing short-term unit commitment (UC) optimi-zation program for day-ahead market since 2014. To better cooperate hy-dro-thermal coordination with the present unit commitment program, a new mathematical model of Da-Chia river cascade hydropower system is intro-duced in this thesis. The planning horizon of hydropower system usually needs to be at least one week to reflect the hydrological condition and re-quirement. It inevitably prolongs simulation time due to the extended plan-ning horizon as well as model complexity. To solve this problem, unit clus-tering concept is realized to transform the original detail model into a clustered unit commitment model. By simplifying the models of generator portfolio, the execution time of mid-term unit commitment program can be significantly reduced. Case studies show that the UC result obtained from the clustered model only produces minor difference compared to that from the detail model under the no-slack condition. On the other hand, the clustered model facili-tates fast computational convergence that achieves the purpose of simulation time reduction.

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