Multi-Timescale Operational Optimization for Mobile Charging Solutions Considering Voltage Regulation Support for ADN: A Two-Stage Coordination Approach

To alleviate the pressure of traditional fixed charging methods, mobile charging solutions have emerged in recent years. This article presents a two-stage coordination approach for mobile charging robots (MCRs) and active distribution networks (ADN). In the first stage, we maximize the total revenue for the MCRs from providing charging services for electric vehicles (EVs) and interacting with the ADN within a frame-based time scale, where the duration of each frame is determined by the charging decisions of MCRs. Furthermore, we consider the long-term objectives of meeting the battery energy deficit constraint for each MCR, thereby improving their battery life. Lyapunov optimization is utilized to transform frame-based scheduling into an optimization problem within a specified time slot, simplifying the process of solving the optimization problem. To avoid affecting charging efficiency when MCRs interact with the power grid, we use the reactive power of free MCRs to provide voltage regulation support for the ADN, improving power quality and minimizing total network loss simultaneously. Decoupling active and reactive power in two stages ensures both the profitability of the MCRs cluster and the voltage security of the ADN, resulting in a win-win situation. The simulation results, based on the 18-bus and 51-bus distribution networks, confirm the effectiveness and superiority of the proposed approach.