電動車與太陽能整合協調調度策略研究

Research on Coordination Scheduling Strategy of Electric Vehicles Integrated with Solar Energy

近年來，環境污染和能源短缺等問題日益嚴峻，電力和電動車在全球迅速普及，並且發展迅速。隨著電動車的普及，儘管電動車有不會排放廢氣、低噪音且環保等優點，但大量電動車所帶來的用電量增加，也會導致微電網系統在尖峰時段的負載大幅上升。
本研究提出了一種為微電網中的電動車制定協調充電調度策略的方法，該方法基於電動車充電的緊迫程度選擇不同的充電模式。同時，將太陽能發電納入充電調度模型，以最小化電動車在尖峰時段充電總負載的波峰波谷差異。考慮到每位駕駛的充電習慣以及電動車慢速、快速充電對微電網運行的各種限制，本研究利用蒙特卡羅模擬(Monte Carlo)模擬電動車充電時間的隨機性。所提出的協調充電調度方法為微電網實施的電力負載削峰填谷提供了方向，同時模擬模型也可為維持微電網穩定性提供參考，以適應未來電動車加速發展趨勢。

In recent years, issues such as environmental pollution and energy shortages have become increasingly severe. Electric power and electric vehicles (EVs) have rapidly gained popularity worldwide and developed swiftly. While electric vehicles offer benefits such as zero emissions, low noise, and environmental friendliness, their increasing popularity may strain microgrid system during peak periods due to the heightened demand for electricity.
This study proposes a method for developing coordinated charging scheduling strategies for EVs within microgrids. The method selects different charging modes based on the urgency of EV charging. Additionally,it incorporates solar power generation into the charging scheduling model to minimize the peak-to-valley differences in EV charging loads during peak periods.
The model considers individual driver’s charging habits and various constraints on slow and fast charging that affect microgrid operations.
Monte Carlo simulation is employed to account for the randomness in EV charging times. The proposed coordinated charging scheduling method provides guidance for peak shaving and valley filling in microgrid implementation. The simulation model also serves as a reference for maintaining microgrid stability in response to the accelerating trend of EV adoption.