Bi-level framework for microgrid capacity planning under dynamic wireless charging of electric vehicles

Abstract

The battery energy storage system in the microgrid can regulate energy and maintain the stability and continuity of renewable energy generation. This paper presents a new microgrid structure with in-motion electric vehicles as a distributed energy storage system. This structure combines the technology of dynamic wireless charging, allowing in-motion electric vehicles to participate in the energy regulation of the microgrid. The proposed microgrid mainly consists of wind turbines, photovoltaic arrays, as well as dynamic wireless charging facility. Two different planning objectives, i.e., maximizing the microgrid utility and minimizing the total generalized social cost, are investigated respectively. Taking into account the response of EV users to the microgrid capacity plans, we propose a bi-level framework. Further, an algorithm based on the surrogate model is used to solve the bi-level programming, where the radial basis function interpolation model is utilized to approximate the objective function. Finally, in case studies, the influence of parameter variations on the results is explored. The feasibility and advantages of the proposed microgrid capacity planning are demonstrated. Further, through the studies of the uncertainties of wind speed, light intensity, base load, and movable load, it is illustrated that the objective value can maintain good stability under the optimal capacity plan.