因應全球電力需求增長與環境環保議題等因素，再生能源之使用已日趨普及，而太陽光伏系統更是重要的發展之一。然而太陽光伏系統滲透率過高會對原有之配電系統電壓帶來一定程度之衝擊，進而限制太陽光伏系統的發展。因此需要適切的電壓控制方法以有效抑制過電壓問題產生，進而增加太陽光伏系統併網容量。
本文利用儲能系統以解決過電壓問題，並且提出雙迴圈最佳化演算法決定儲能系統最佳化裝置容量。儲能系統的導入能夠減少太陽光伏系統饋入削減量，且降低系統電壓衝擊使其符合法定規範，增加太陽光伏系統的使用率及併網容量。本文主要透過變壓器有載切換開關與太陽光伏系統及儲能系統變流器之實、虛功控制，達成電壓控制的目的。其中，採用電子飄移演算法於內迴圈決定一天前每個小時在固定一儲能系統裝置容量下，各裝置的實、虛功發電量最佳化運轉排程；基於內迴圈所得結果，於外迴圈再以電子飄移演算法決定儲能系統的最佳裝置容量。
本文為驗證最佳化方法之可行性，利用實際之太陽光伏發電量與負載資料分析其成本效益，並與其他現有文獻之方法進行比較。同時為能了解時間電價費率結構對於本文提出之最佳化方法的影響，本文分析三種不同之時間電價費率整體收益。由數值模擬結果顯示，所提出之方法除可決定儲能系統最佳裝置容量外，較現有文獻方法能獲得更顯著之經濟效益。

The challenges of increasing power demand and environmental problems have directed extensive attention to the usage of renewable energy, especially photovoltaic (PV) systems. However, high penetration of PV generation drastically affects the voltage of distribution systems, which may limit the growth and the development of PV systems. Consequently, an effective voltage control method is necessary to mitigate overvoltage problems and to increase the hosting capacity of PV systems.
This thesis utilizes an energy storage system (ESS) to eliminate voltage rise problems and proposes a dual-loop optimization method to determine the optimal capacities and inverter sizes of ESSs. ESSs can thus reduce feed-in active power curtailment of PV systems. In the inner loop of the optimization, for a specified ESS capacity the daily active and reactive power scheduling, including on-load tap changer, PV, and ESS, are optimized by an electron drifting algorithm (EDA). The outer loop uses an EDA to optimize the ESS capacities and the inverter sizes.
To verify the feasibility of the proposed optimization method, real PV power generation data and load profiles are used to analyze the economic benefits of the proposed method. Moreover, three different kinds of electricity tariff structures are used to analyze the economic benefits. With the optimal capacity of energy storage system determined, simulation results also show that the optimized policy produces more economic benefits than other policies produce.

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