Electric Vehicles charging strategy based on multimarket platforms for photovoltaic-powered workplace charging station

Atmospheric pollution is extremely raised in recent years due to the growth of fuel-based vehicles number and the increase of energy generation coming from nonrenewable sources. To alleviate this issue, electric vehicles (EVs) and renewable sources are applied in many countries. This chapter presents an optimal model able to forecast photovoltaic (PV) power generation and optimize power flows between grid, PV system, and EVs at workplace charging station. Considering multimarket platforms, the optimal model aims to maximize the selling cost of the surplus energy discharged by EVs and the PV system while minimizing the EVs’ charging energy cost. The developed model consists of three components: back-propagation neural network model to predict PV power generation, the EV user’s behavior uncertainties by the probability distribution functions, and mixed-integer linear programming optimal framework that allocates power to maximize the selling cost of energy and to minimize purchasing energy cost. The results show that the developed approach can minimize the purchasing energy cost while maximizing the selling cost of energy.