伏特
光伏系统
电压
地铁列车时刻表
调度(生产过程)
电池(电)
电
荷电状态
交流电源
涓流充电
计算机科学
工程类
电气工程
控制理论(社会学)
功率(物理)
控制(管理)
汽车工程
运营管理
物理
量子力学
人工智能
操作系统
作者
Arunima Dutta,Sanjib Ganguly,Chandan Kumar
标识
DOI:10.1016/j.segan.2022.100761
摘要
This paper proposes a three-stage model predictive control (MPC)-based centralized coordinated approach to schedule charging of electric vehicles (EV) and volt/var (VV) devices. The approach aims at maintaining bus voltage magnitudes and state-of-charge (SOC) of EV battery within desired limits with minimal usage of control resources and cost of electricity consumption. The first stage determines the optimal operating points of traditional discrete control devices on an hourly basis. The second stage dispatches the optimal set-points of power electronics interfaced fast devices [photovoltaic (PV) and EV inverters] every one minute. The third stage schedules charging/discharging of EV half-hourly with respect to the real-time electricity price. Furthermore, several rules are formulated to adjust the local volt/var curve of PV and EV inverters according to the voltage magnitudes. The combined central and local control approach ensures that EVs attain the desired SOC at the time of their departure from the charging station without violating the voltage limits. The proposed control approach is tested in a 33-bus distribution network and 38-bus distribution network with different operating conditions. Simulation results depict that the performance of the proposed control approach is better than uncoordinated charging in terms of reduced voltage deviations, energy loss, and control resources utilization.
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