Voltage Control and Network Losses Reduction with Intelligent Charge and Discharge Management of Electric Vehicle Batteries Based on Vehicle-To-Grid Technology

Article Type:
Research/Original Article (دارای رتبه معتبر)
The use of electric vehicles (EVs), to reduce greenhouse gases and air pollution caused by the fossil fuel consumption, seems to be an inevitable solution. The increased penetration of EVs imposes a large variable load to the grid. However, the battery of EVs in an aggregator provides a large source of energy storage. Therefore, EVs depending on the charging or discharging modes can act as flexible loads or as flexible energy sources. Then, the proper coordination and control charging and discharging of EVs, using vehicle-to-grid (V2G) technology, not only can minimize the undesirable effects resulting from the increased penetration of EVs, but also can improve the voltage profile. In this paper, a new algorithm with variable-objective function is proposed to control variable quantities of generation and consump tion. In the proposed method, the control of the point of common connection (PCC) voltage in a specific value of a determined permissible range, which depends on different operating conditions, can be considered as a variable-objective function. Moreover, there are constraints to state of charge (SOC) of electric vehicles (EVs) batteries and charging/discharging time. Other advantages of using the proposed method are the reduction of network losses in peak load hours and the establishment of an appropriate coordination between charging and discharging EVs. The simulations of the IEEE 14-Bus distribution system with V2G capabilities based on the proposed variable-objective function (VOF) algorithm are implemented for both charging and discharging modes using MATLAB/PSAT software and tested for the various scenarios. Finally, the results of the proposed method are compared with the traditional method and the merit of that is proved.
Journal of Intelligent Procedures in Electrical Technology, Volume:16 Issue: 61, 2024
157 to 176
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