Real-time charging strategies, in the context of vehicle to grid technology, are needed to enable the use of electric vehicle fleets batteries to provide ancillary services. In this paper, we develop tools to manage charging and discharging in a fleet to track an automatic generation control signal when aggregated. We propose a real-time controller that considers bidirectional charging efficiency and extend it to study the effect of looking ahead when implementing model predictive control. Simulations show that the controller improves tracking error as compared with benchmark scheduling algorithms, as well as regulation capacity and battery cycling.
BT - IEEE Transactions on Smart Grid DA - 09/2018 DO - 10.1109/TSG.2017.2681961 IS - 5 LA - eng N2 -Real-time charging strategies, in the context of vehicle to grid technology, are needed to enable the use of electric vehicle fleets batteries to provide ancillary services. In this paper, we develop tools to manage charging and discharging in a fleet to track an automatic generation control signal when aggregated. We propose a real-time controller that considers bidirectional charging efficiency and extend it to study the effect of looking ahead when implementing model predictive control. Simulations show that the controller improves tracking error as compared with benchmark scheduling algorithms, as well as regulation capacity and battery cycling.
PY - 2018 SP - 5141 EP - 5151 ST - IEEE Trans. Smart Grid T2 - IEEE Transactions on Smart Grid TI - Real-Time Charging Strategies for an Electric Vehicle Aggregator to Provide Ancillary Services VL - 9 SN - 1949-3053 ER -