隨著永續發展及節能減碳意識高漲，電動車行業亦隨之蓬勃發展。然而大規模的電動車負載併入電網後，其大量與不確定性用電將會對電力系統造成嚴峻的挑戰。未來大型停車場廣設電動車充電設施後，需仰賴電能管理系統施以最佳化充/放電排程策略，俾兼顧營運利益與電網安全。
本文中提出一應用於電動車充電站中電動車G2V/V2G與儲能電池之最佳化充/放電排程策略，並藉由分散式運算架構簡化最佳化問題之複雜度。所提方法可配合電價費率及參與需量反應市場最大化各台電動車與儲能電池之充/放電營運利潤。此外，駕駛人用車需求隨機性、充電樁隨輕重載條件之轉換效率差異及電池反覆充/放電操作所產生之劣化成本均被納入最佳化問題中以提升整體營運效益。本文藉模擬一座含100具充電樁之充電站以驗證所提方法之可行性，相關演算法未來可用於智慧電網內電動車充電站營運商、用戶群代表或分散式電力資源整合服務商。

As the consciousness of carbon reduction and sustainable development rise rapidly worldwide, the industry of electric vehicle (EV) started to flourish. However, the large-scale of EVs connected to power grids with large load demand and uncertainty may result in significant challenges on the power system. With large amounts of EV charger installed, an energy management system will be needed for optimal charging and discharging scheduling strategies to maintain both operational benefits and power supply security.
This thesis proposes an optimal charging and discharging scheduling strategies for G2V/V2G and battery energy storage system (BESS) adopted in the EV charging station. Besides, a distributed computation architecture is employed to streamline the complexity of the optimization problem. In addition, the proposed method can maximize the operational profits of each EV and BESS based on the related electricity tariff and demand response programs. Moreover, the behavior model of the drivers, conversion efficiency of the converters for different load conditions, and BESS degradation cost caused by charging and discharging cycles are taken into account to improve the overall operational benefits. An EV charging station with 100 charging piles is simulated as a demonstration example to verify the feasibility of the proposed method. The related algorithms can be used for EV charging stations, load aggregator, and distributed energy resource integrated service companies in the smart grid.

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