隨著全球淨零碳排與環保意識的興起，大量再生能源與電動車加入電力系統，世界各國大力推動相關措施，以應對電力系統面臨的挑戰。發展微電網與能源管理系統透過有效的調控再生能源與分散式資源參與輔助服務市場，除了可以降低系統操作成本，同時也扮演著提升電力系統穩定度及安全性的重要角色。
本文以微電網營運商的角度設計一套電能管理系統，讓用戶以需量反應的形式參與輔助服務市場，其中，考慮再生能源的不確定性及輔助服務執行之機率，除了可以達到尖峰移轉與降低系統操作成本外，亦能提升分散式能源投資之經濟性。所提之電能管理系統含三階段調度策略，第一階段為日前最佳化排程，旨在最大化整體系統營運效益，排程各分散式資源並決定輔助服務市場投標策略。第二階段為即時滾動調控柴油發電機及可控負載，以修正因日前預測誤差之結果，最小化當前操作成本。第三階段，使用模型預測控制方法調控儲能系統輸出，以提高即時備轉執行率同時兼顧契約容量管理。
本文以實際資料驗證提出之控制方法具可行性，其運算時間相較於傳統最佳化方法大為縮短，可使調度上更具彈性、降低因通訊所產生之控制誤差，能更佳響應系統即時狀態。此外，藉由靈敏度分析驗證所提電能管理系統有效提高整體微電網效益。最後基於採用不同的控制方法參與輔助服務市場，顯示本文在固定年利率條件下，具最短的儲能系統投資回收年限，讓整體系統營運的更具經濟實用性。

With the rise of global net-zero carbon emissions and environmental awareness, a large number of renewable energy sources (RES) and electric vehicles (EV) have been added to the power system. Countries around the world are vigorously promoting relevant energy policies to cope with the changes that the power system will face.
This paper designs a power management system from the perspective of a microgrid operator, the proposed energy management system (EMS) follows a three-stage scheduling strategy. The first stage is day-ahead optimization scheduling, which aims to maximize the overall system's revenue, schedule various distributed resources, and determine the bidding strategy for the ancillary service (AS) market. The second stage is real-time rolling optimization control, which regulates diesel generators and controllable loads to minimize operating costs by correcting day-ahead forecast errors. In the third stage, the model predictive control (MPC) method is used to manage the output of the energy storage system (ESS), improving the AS executing rate and considering contract capacity management.
The actual data is used to verify the feasibility of the control method proposed in this research. Compared with traditional optimization methods, the method proposed in this thesis has a significantly shorter computation time. Scheduling can be made more flexible while reducing control errors caused by communication. Therefore, it can better respond to real-time system status. In addition, sensitivity analysis is used to verify that the power management system effectively improves the efficiency of the overall microgrid. Finally, based on different ancillary service market participation and control methods, this thesis demonstrates the shortest investment period for the ESS under a fixed annual interest rate, making the overall system operation more economical.

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