This paper proposes a novel software defined wireless sensor network (SDWSN) based grid to vehicle (G2V) load management scheme to initiate off peak hour valley filling of the daily power supply curve. In particular, this paper focuses on domestic Plug-in Electric Vehicles (PEVs) charging that adopts smart energy allocation technique to maximize the number of charging vehicles and uses a Software Defined Network (SDN) to enable adaptive energy supply. A novel energy scheduling algorithm is proposed based on a linear prediction algorithm that suits the network model built upon a SDN paradigm. To demonstrate the proof of concept, an SDN based Smart Grid Neighborhood Area network (SGNAN) operating onto Wireless Sensor Network (WSN) is developed using Castalia. Simulation results show that the proposed SDWSN network architecture can efficiently support the G2V load management scheme and enables smart valley filling of the daily load curve for maximum utilization of power generation capacity.