Thanks to the demand response (DR), the system operators have a substantial opportunity to manipulate the demand side of the power system. Moreover, the system operators can easily incorporate trending technologies such as electric vehicles (EV) due to the idea of introducing improved level of controllable loads. In this study, a real-time optimization-based energy management model for an EV parking lot (EVPL) is propounded by using linear programming. The proposed algorithm offers a peak load limitation oriented DR program providing operational flexibility from the load-serving entity point of view together with the objective of maximizing the load factor of the EVPL in daily operation. Because of the mobility of the EVs, uncertain arrival/departure times along with the state-of-energy levels upon their arrival are generated by considering historical data to ensure a more realistic approach. In order to prove the validness of the suggested optimization model, a bunch of case studies is performed. Besides, credible results and useful findings are found out by activating the propounded model.

中文翻译：

---

提供基于PLL类型需求响应程序的基于实时算法的智能EV停车场收费管理策略

由于需求响应（DR），系统操作员有很大的机会来操纵电力系统的需求方。此外，由于引入了改进水平的可控负载的想法，系统操作员可以轻松地整合趋势技术，例如电动汽车（EV）。在这项研究中，通过使用线性规划提出了基于实时优化的EV停车场（EVPL）能源管理模型。所提出的算法提供了一种面向峰值负载限制的DR程序，从负载服务实体的角度出发提供了操作灵活性，并且目标是在日常操作中最大化EVPL的负载因子。由于电动汽车的机动性，通过考虑历史数据以确保更现实的方法，可以生成不确定的到达/离开时间以及到达时的能量状态水平。为了证明所建议的优化模型的有效性，进行了大量案例研究。此外，通过激活提出的模型，可以找到可信的结果和有用的发现。