Enhancing the utilization of renewable generation on the highway with mobile energy storage vehicles and electric vehicles

Abstract

The growth of electric vehicles (EVs) and renewable generation on the highway will magnify the imbalance between the energy supply and traffic electricity demand. Reshaping EV charging loads to address the above imbalance is challenging. Scheduling mobile energy storage vehicles (MESVs) to consume renewable energy is a promising way to balance supply and demand. Therefore, leveraging the spatiotemporal transferable characteristics of MESVs and EVs for energy, we propose a co-optimization method for the EV charging scheme and MESV scheduling on the highway, considering locational marginal price, renewable generation, and EV users’ benefit. Furthermore, by building a time–space–energy model for MESVs and EVs, we develop a bi-level optimization model to simulate the interaction between EV users and the highway operator (HO). In detail, the upper-level model optimizes EV charging pricing and MESV scheduling strategies to maximize HO profit, while the lower-level model considers EV users’ characteristics to minimize their charging-parking costs. The column-and-constraint generation algorithm is adopted due to the objective conflict between two levels. The study shows a 32.0% increase in renewable energy utilization and a reduction of 3190.1 kWh in electricity purchased from the main grid, promoting environmental and economic sustainability for the HO.