Network security-aware charging of electric vehicles


Recent technology advancement has given birth to electric vehicles. Favored with the growing concern of environment pollution, global warming and need to protect the environment, electric vehicles have gained popularity globally. Generally, they are less environmental pollutants as compared to fuel-driven automobiles. Unfortunately, efficient coordination in the large-scale integration of electric vehicles is still a huge challenge worldwide. Most scholars have however prophesied this a potential risk that will lead to negative impacts on the power systems if not properly managed. To this note, there is an urgent need for effective electric vehicles charging strategies and coordination to prevent the negative effects of the grid.

In the recently published literature, most studies about the electric vehicle charging systems have majored mostly on the distribution networks. However, problems associated with charging from the transmission network have been given little consideration. Even though most of the developed methods have the potential of reducing the power losses, enhancing the voltage profiles and improving on the charging costs among other benefits, they do not take into consideration the N-1 security constraints.

In a recent paper published in Electrical Power and Energy System, Dr. Aina Tian and Dr. Weixing Li at Harbin Institute of Technology in collaboration with Dr. Zuyi Li at Illinois Institute of Technology and Yong Sun at State Grid Jilin Electric Power Supply Company developed an efficient network security-aware charging system for electric vehicles. The authors took into account the N-1 security constraints to develop the multi-objective schedule for electric vehicles charging. Their main objective was to develop a charging model for reducing the network power loss, improving voltages profile and user satisfaction. Also, they purposed to enhance the security of the whole system through N-1 constraints. Lagrangian Relaxation and Benders Decomposition techniques were used to solve the time coupled constraints and optimal contingencies respectively. Furthermore, the optimal charging schedule was determined on a tri-level hierarchy based on an aggregator representing controllable electric vehicles.

The authors observed that the proposed charging strategy had a huge potential for solving the security problems associated with charging of the electric vehicles. Furthermore, through optimization, the system was capable of selecting a preferred schedule to enhance the system voltage profile, improve on the user satisfaction and also reduce the power loss. This represents a significant improvement as compared to the initially proposed models.

The study does not contradict the presently used electric vehicles charging systems but instead proposes an alternative method that takes into consideration the rapid growth of electric vehicles and potential problems and impact on the power systems that will rise into the future. Therefore, it provides a foundation for future works that will advance, for example, the optimization strategies for electric vehicles aggregators that will improve the functionality of the control center.


Tian, A., Li, W., Li, Z., & Sun, Y. (2018). Network security-aware charging of electric vehicles. International Journal of Electrical Power & Energy Systems, 100, 42-49.

Go To International Journal of Electrical Power & Energy Systems

Check Also

Distributed rotating consensus of second-order multi-agent systems with nonuniform delays