隨著全球暖化和空氣污染問題加劇，以及人們對環保意識的提高，各國政府對於環境保護議題更加重視，紛紛制定公約和規範，並推動環保政策致力於2050年實現淨零碳排目標。在此背景下，推廣電動車和增加綠色能源的使用成為實現該目標的關鍵皆在幫助減少溫室氣體排放和推進低碳的可持續方展。然而，隨著電動車數量的逐年增加，對充電的需求亦隨之提升，其充電需求的不穩定性和隨機性，將對電力系統造成了額外的負擔。因此，本文提出的充電策略最佳化結合儲能系統的整合，提供了一種緩解電動車充電壓力的解決方案。
本研究提出的解決方案即為將充電控制模型和儲能系統的日前排程與動態控制策略整合，形成一種新的整合優化策略。充電控制模型採用的策略除了非受控充電和均流模式充電外，以及基於粒子群演算法和線性規劃的動態多目標充電排程策略，考慮電動車用戶的充電資料、充電站設備資料及時間電價，根據不同情境制定最佳的充電排程策略，以提升系統的靈活性和高效性。儲能系統方面，透過歷史負載資料做為日前排程的輸入，並考量了儲能電池的設備資料與時間電價，以制定預期的充放電規劃。此外，還加入了儲能動態控制策略以應對實時變化的電力負載和時間電價。最後，本文將不同的充電策略與儲能系統結合，通過建立的數學模型和整合的優化算法，不僅能改善電網負載平衡，還能滿足用戶的充電需求並實現電費最小化。

As global warming and air pollution worsen, and environmental awareness rises, governments worldwide are prioritizing environmental protection by enacting policies to achieve net-zero carbon emissions by 2050. Promoting electric vehicles (EVs) and increasing green energy use are crucial for reducing greenhouse gas emissions and advancing sustainable development. However, the growing number of EVs increases charging demand, adding stress to the power grid due to its instability and randomness. To address this, this study proposes an optimized charging strategy integrated with energy storage systems.
The proposed solution combines a charging control model with day-ahead scheduling and dynamic control strategies of energy storage systems, forming a novel optimization strategy. The charging control model incorporates uncontrolled charging, equalized charging, and dynamic multi-objective charging scheduling based on particle swarm optimization and linear programming, considering EV users' charging data, station equipment data, and time-based electricity pricing to optimize charging schedules for various scenarios. The energy storage system uses historical load data for day-ahead scheduling, factoring in storage battery data and electricity pricing to develop expected charging and discharging plans. Additionally, dynamic control strategies are implemented to address real-time changes in power load and pricing. This integrated approach not only improves grid load balance but also meets user charging needs and minimizes electricity costs.

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