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Day-ahead charging operation of electric vehicles with on-site renewable energy resources in a mixed integer linear programming framework

机译：在混合整数线性规划框架中具有现场可再生能源的电动车辆的一天充电操作

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摘要

The large-scale penetration of electric vehicles (EVs) into the power system will provoke new challenges needed to be handled by distribution system operators (DSOs). Demand response (DR) strategies play a key role in facilitating the integration of each new asset into the power system. With the aid of the smart grid paradigm, a day-ahead charging operation of large-scale penetration of EVs in different regions that include different aggregators and various EV parking lots (EVPLs) is propounded in this study. Moreover, the uncertainty of the related EV owners, such as the initial state-of-energy and the arrival time to the related EVPL, is taken into account. The stochasticity of PV generation is also investigated by using a scenario-based approach related to daily solar irradiation data. Last but not least, the operational flexibility is also taken into consideration by implementing peak load limitation (PLL) based DR strategies from the DSO point of view. To reveal the effectiveness of the devised scheduling model, it is performed under various case studies that have different levels of PLL, and for the cases with and without PV generation.
机译：电动车辆（EVS）进入电力系统的大规模渗透将引发经销系统运营商（DSOS）处理所需的新挑战。需求响应（DR）策略在促进每个新资产的整合到电力系统方面发挥了关键作用。借助智能电网范式，在本研究中，在不同地区的不同地区大规模渗透的一天提前充电操作，包括不同的聚集器和各种EV停车场（EVPLS）。此外，考虑了相关EV业主的不确定性，例如初始能源状态和到达相关EVPL的到达时间。通过使用与日常太阳照射数据相关的基于场景的方法，还研究了PV生成的随机性。最后但并非最不重要的是，通过从DSO的角度来实现基于峰值负载限制（PLL）的DR策略，还考虑了操作灵活性。为了揭示设计的调度模型的有效性，它是在不同水平的PLL水平的案例研究中进行的，并且对于具有和没有PV生成的情况的情况下进行。

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