Calculation of the optimal charging scheduling of electric vehicles

Climate change, shortage of oil and natural resources and technological improvement on batteries are convincing reasons to invest in electric vehicles. When the number of electric vehicles increases it becomes important to manage their charging scheduling, in order to avoid overloading of lines and transformers of the distribution network. This thesis studies the calculation of optimal charging scheduling of a fleet of plug-in electric vehicles (PEVs) that are supplied by a distribution network. The optimization problem is formulated as a mixed-integer linear program, with the objective of minimizing the cost of purchasing electricity from the network, while satisfying the local and network constraints. Considering the scenario “charging only”, the optimal charging scheduling of the PEVs is calculated through a centralized approach. When the vehicle to grid functionality of the PEVs is enabled and the number of PEVs increases, then the problem becomes difficult to solve and the centralized approach becomes impractical. In order to cope with this problem, the objective function of the centralized model is modified in a way to give the priority to the PEVs with higher battery capacity to perform the vehicle to grid functionality which results in reducing the complexity of the calculations. Then a distributed approach is applied to solve the optimal charging scheduling through an iterative distributed algorithm. The distributed approach is applied for both scenarios “charging only” and “charging and vehicle to grid”, in which the centralized approach is impractical to solve. Objective functions of the two approaches are compared. Results show that for each fleet of PEVs, the value of objective function of the centralized model is similar to the value of objective function of the distributed model