Intelligent Controller for Grid Connected by Charging Station towards Achieving Sustainable Development

Anbarasu L, G. S, Jaikavin K, S. D.
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Abstract

This study suggests power management techniques for a PV storage system that is connected to the grid in an electric vehicle charging station (EVCS). The CS's power control system is where the strategy is intended to be used. To lower energy consumption costs calculated using the electrical grid in stand-alone mode and to minimize stress on existing power, the control relies upon relating to the use of renewable energy sources using an optimization process. The outcomes of a 15kW PV-Grid system's simulation coupled with a load flow of five EVs and a 40 kWh lithium-ion battery are used in this paper to describe the approach in detail. However, this study describes a powerful predictive model that is founded on real-time power monitoring supply and demand. When an effective data connection is made between the CS and the plugged EV. The method to determine the best charging mode also takes into account several other factors, such as the PV array's instantaneous power, the amount of energy in the buffer for battery storage, and the restricted power available from the grid. The source converters for voltage the MPPT algorithm, additionally, the ongoing control loop serves as the foundation for the power forecasting model that has been chosen. The outcomes of the simulation of various scenarios for charging effectively describe the efficiency of the suggested CS, which is used to test the validity of this model.
面向可持续发展的充电站并网智能控制器
本研究提出了在电动汽车充电站(EVCS)中连接到电网的光伏存储系统的电源管理技术。CS的动力控制系统是打算使用该策略的地方。为了降低在独立模式下使用电网计算的能耗成本,并最大限度地减少对现有电力的压力,该控制依赖于使用优化过程的可再生能源的使用。本文使用15kW光伏电网系统的模拟结果,以及五辆电动汽车和40 kWh锂离子电池的负载流来详细描述该方法。然而,本研究描述了一个建立在实时电力监测供需基础上的强大预测模型。当在CS和插入的EV之间建立有效的数据连接时。确定最佳充电模式的方法还考虑了其他几个因素,例如光伏阵列的瞬时功率,电池存储缓冲区中的能量量以及电网可用的受限功率。电压源变换器采用MPPT算法,另外,正在进行的控制回路作为所选择的功率预测模型的基础。不同收费情景的仿真结果有效地描述了所建议的CS的效率,并用于检验该模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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