Optimal Electric Bus Charging and Battery Swapping With Renewable Energy and Frequency Control Ancillary Service Through Aggregator

A methodology is designed for an aggregator to optimize the charging process of multiarea and multifunctional bus charging stations. This methodology highlights the potential collaboration among key participants through a unified modeling language (UML) sequence diagram. The diagram covers two algorithms for operational planning and charging optimization. The operational planning algorithm applies to normal charging, fast charging, and battery swapping. The operational planning algorithm computes and shares the initial state of energy (SoE) of electric buses to the charging optimization model. The charging optimization model employs the interior-point algorithm and stands out for three remarkable features. First, it is designed for an aggregator dealing with multiarea and multifunctional charging. Second, the model enhances the use of renewable energy during charging through a power purchase agreement (PPA), thereby reducing the carbon footprint. Furthermore, this model supports grid operation by providing ancillary services for frequency control while considering power network constraints. To validate the applicability of the methodology, it is tested using electric bus route data from Berlin and also involving the medium voltage (MV) benchmark network of the International Council on Large Electric Systems (CIGRE). The results confirm the effectiveness of the optimal charging strategies in minimizing the operating costs for an aggregator of multiarea and multifunctional stations.