Cornell team develops framework for incorporating wireless charging road system into real-time electricity market
Researchers at Cornell have developed a coupled transportation–power system framework for incorporating a wireless charging road system into the real-time electricity market. In addition, they propose an optimization-based control strategy to manage the energy storage system in a cost-efficient manner. Their paper is published in the journal Applied Energy.
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. Integration of wireless charging roads into the existing electricity market and efficient management of the corresponding energy storage system are crucial for successful implementation of the wireless charging road systems.—Shi and Gao (2022)
The simulation study demonstrates that efficient control of the energy storage system not only reduces the energy costs of the entire wireless charging road system but also alleviates the pressure produced by the wireless charging load on the existing power grid. In two numerical examples, the energy costs are reduced by 2.61% and 15.34%, respectively.
Time average of maximum and time average of standard deviation of locational marginal prices are reduced by 10.65% and 69.33% for the first numerical example and 5.11% and 34.73% for the second numerical example.
The proposed framework consists 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 roads 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.—Jie Shi, lead author
Jie Shi, H. Oliver Gao (2022) “Efficient energy management of wireless charging roads with energy storage for coupled transportation–power systems,” Applied Energy, Volume 323 doi: 10.1016/j.apenergy.2022.119619