Electric Bus Demand Management through Unidirectional Smart Charging

The difficulty of controlling the charging of electric buses (EBs), managing the EBs missions requirements with the ingoing and outgoing timetables and its effects on network demand are discussed in this study. The solutions suggest a call for worldwide, complex infrastructures that manage EVs and EBs equally. Additionally, the Distribution Network (DN) must be prepared for an increased prevalence of reverse power flow caused by widespread distributed renewable generation. This thesis focuses exclusively on EBs since they have higher capacity and predictable charging patterns, which makes them more significant for the DN in the context of a transition to complete vehicle electrification and technologies that are mature enough to be hosted. The proposed algorithm employs the Day-Ahead Energy Market (DAEM) in the Smart Charging (SC) to forecast the network operating circumstances, or to design a charging station specifications according to the networks requirements. Additionally, the technique makes it possible for distributed photovoltaic (PV) generation, allowing network demand to be referenced depending on net demand. It also optimises individual charger current per vehicle and per-time-step with load-levelling or peak-shaving as its primary goal. The final real demand demonstrates that a coarse correction of the demand is possible. According to the analysis on a typical European DN synthesised with a 13-Node Feeder with a radial topology, by using the DN voltage profile and associated line losses as references, it was found that the ideal node position location of the CS is dependent on PV penetration. In addition, the study points out the possibility for future updates of the algorithm in order to host real-time control of the reverse power flow and reactive power control, without overturn the charging system Infrastructure.