Priority-based vehicle-to-grid scheduling for minimization of power grid load variance

Electric vehicles are considered as additional loads to the power grid and may pose possible threats to the power grid reliability by overloading the grid equipment, disturbing the grid voltage stability and injecting harmonics into the power grid. Nonetheless, electric vehicles can also provide supports to the power grid through Vehicleto-Grid application by discharging battery energy into the power grid. This paper presents an optimal priority-based Vehicle-to-Grid scheduling with the objective to minimize the grid load variance. An optimal strategy was developed to optimize the amount of charging/discharging power based on the electric vehicle battery's state-of-charge. This study desires to find a central point which can benefit power utility and electric vehicle users. The algorithm can operate in three modes, which are valley filling, peak load shaving and priority charging. The charging of the electric vehicle can be performed in all three modes, as long as the charging of electric vehicle is required. Meanwhile, discharging of the electric vehicle only occurs during peak load shaving mode. To ensure the practicability of this study, numerous constraints were considered and the study was conducted in a commercial-residential area with electric vehicle mobility of 1300. The results indicated that the algorithm was able to minimize the grid load variance while prioritizing the electric vehicle with a low percentage of state-of-charge. The original maximum variation between peak loading and off-peak loading measured at 5 MW was effectively reduced to 1.5 MW following the deployment of the proposed algorithm.

Automated summary

This study presents a new method to minimize grid load variance by optimizing the scheduling of electric vehicles to the power grid, which can operate in three different modes to enhance power system reliability.