High Power level Direct Current Fast Charger (DCFC) Electric vehicles chargers are a key factor to the widespread of Plugged Electric Vehicle (PEV) penetration to the grid. This thesis proposes modelling the aggregation of Bidirectional EV chargers to perform as STATCOM. This high-power level bidirectional Electric Vehicle (EV) Chargers are modelled to continuously provide reactive power services through their front-end AC-DC converter. The work decouples the reactive power capability of the chargers from the Real power. Three phase, 2-level voltage source converter is used for modeling the bidirectional charger. The front-end converter is controlled to continuously provide reactive power and the boost/buck rectifier is controlled to charge the battery whenever EV is connected to the charger. The control is in Direct-Quadrature-Zero (dqo) synchronous rotating reference frame, and the reactive power is controlled by the quadrature current. The aggregation of these high-power level DCFC generates enough reactive power that make an impact to the grid. The dispatch of the bidirectional DCFC is considered a unit commitment problem and proposes that neural network be employed. In this work, the high-power level DCFC is modelled like the ASEA Brown Boveri (ABB) high-power Charger - ABB Terra HP 350 DC Fast charging station. The model is tested with IEEE 13 Node Test Feeder.