The electric vehicle industry expanded significantly over the past decade. These vehicles emerge as a possible strategy for decarbonization and green transportation due to social demand. However, to ensure and enable rapid market penetration of EVs, one major obstacle needs to be addressed – range anxiety.
In a paper published in Applied Energy, Cornell researchers showed that wireless charging roads equipped with energy storage systems are promising electric vehicle charging solutions by virtue of their strong advantages in time-saving and reduced pressure on the existing power infrastructure.
In their work, the researchers have developed a coupled transportation-power system framework for the incorporation of a wireless charging road system into the real-time electricity market. In addition, they propose a Lyapunov optimization-based control strategy to manage the energy storage system in a cost-efficient manner.
Their simulation study demonstrates that efficient control of the energy storage system not only reduces the energy costs of the entire wireless charging load system but also alleviates the pressure produced by the wireless charging load on the existing power grid. In two numeric examples, the energy costs are reduced by 2.61% and 15.34%, respectively.
“We designed a Lyapunov optimization-based control strategy to manage the energy flow between the wireless charging roads and the energy storage system in a cost-efficient way,” said H. Oliver Gao, the Howard Simpson Professor of Engineering and co-author of the paper. “The proposed framework is composed of three major modules: the hybrid traffic assignment, the extended DCOPF, and the controller.”
The hybrid traffic assignment calculates the traffic flow given specific trips across a road network composed of wireless charging lanes and normal traffic lanes. The extended direct current optimal power flow (DCOPF) determines the optimal electric energy flows between the generation resources, load centers, and wireless charging in the given power grid. The control approach seeks to minimize the energy costs of wireless charging roads by efficiently managing the output of the energy storage system.
“Our control strategy is computationally efficient and requires no forecasts of the system states, making it appealing to practical applications,” said Jie Shi, a former Cornell systems postdoctoral researcher.
