隨著全球人口的增加與經濟的成長，可用之能源不斷的減少，能源匱乏的危機越來越受到重視，而電價持續上漲，各季節與各時段之電費差異也逐漸變大，若能透過有效的負載管理，即可改善用戶的負載型態，縮短尖峰與離峰負載之差距，提高能源使用效率，同時也可以降低電費的支出，進而節省成本。
本研究擬發展一套電能管理系統，其主要目的系針對時間電價用戶，以粒子群演算法求解最小電費支出為觀點，考慮台電公司現行之規定，避免超約用電受罰或契約容量訂得太高而增加了基本電費的支出，根據用戶之用電習性，協助用戶進行最佳化負載排程，並決定較佳的契約容量，另外也將儲能系統併入考慮，利用離峰時段充電，尖峰時段放電，能更有效地達到負載轉移之目的，如此便能節省更多的電費支出。儲能系統亦考量其安置容量與成本以確保其安裝的效益。本研究最後進行案例模擬，以驗證本程式執行之可行性。

With the growth in the global population and economy, available energy sources are gradually diminishing and the awareness of energy shortage crisis has increased. In addition, the price of electricity continues to rise, causing gradual increases in the seasonal and periodic price differences for electricity. In this context, effective load management not only improves user load patterns, reduces the peak and off-peak load margins, and enhances energy efficiency, but also reduces the electricity expenditure and facilitates cost savings.
In this study, an energy management system focused on time-of-use (TOU) rate users was developed. The particle swarm optimization (PSO) method was adopted to calculate the minimal energy expenditure. In addition, the current Taiwan Power Company regulations were referenced to prevent unnecessary electricity expenditure because of over-usage or impractical contract capacity. Based on user energy consumption habits, this system enables users to optimize their load schedule, formulating improved contract capacities. In addition, this system considers energy storage equipment, and employs an off-peak recharge/peak discharge approach to effectively achieve load shifting and electricity cost savings. Furthermore, the placement capacity and cost for the energy-storage system were also considered to ensure the installation effectiveness. To verify the execution feasibility of the proposed program, the energy consumption data were used for case simulation in this study.

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