A comparative study of real-time coordinate charging schemes for residential electric vehicles

This paper proposes and compares two real-time charging scheduling schemes for residential electric vehicles (EVs), by incorporating user charging demands and individual response to charging management. They are a mathematical optimization-based approach and an aggregated target-based approach. The former involves formulating optimal charging scheduling as a mathematical programming problem for each arriving EVs. The latter approach offers a fast-solvable solution by approximating the objective function. Comprehensive simulations with varying EV penetration and participation rates have been conducted to examine the performance of the two schemes based on real EV and distribution substation data from a residential area in Beijing. A reduction of 23.2 % and of 39.0% in load variance can be achieved for the local grid with the current 670 EVs. The findings also indicate that a larger number of participating EVs and a higher range of charging power rates can further contribute to load flattening and shifting effect. Moreover, the comparative analysis reveals a trade-off between the computational efficiency and the coordination effects, allowing the two schemes to be recommended for different real-world scenarios.