This paper elaborates on the concept of using electric vehicles (EVs) to provide energy sustainability in a smart energy cyber-physical system. This system constitutes of smart homes (SHs) and EVs, where the latter is used to provide the load demand stability to the former. In this smart energy system, software defined networking (SDN) paradigm is used as an underlying network to provide the communication services for facilitating the energy trade between SHs and EVs. Before taking the energy trading decisions, the proposed scheme initially forecasts the energy demand in the SHs using a regression tree model. Once this demand value is predicted, the deficit (or surplus) energy in the SHs, after catering to the load demand using renewable energy sources (RES), is traded from (or with) the EVs. For this trading, the EVs calculate their utility before traveling to the SHs for actually trading the energy. The EVs would go to the SH which would increase their utility after trading the energy. The simulation results prove that the demand forecasting model accurately predicts the energy demand of SHs. Moreover, results also show how the energy profile of the EVs changes with respect to their energy trading decisions taken.
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