Electric Bus Demand Management through Unidirectional Smart Charging

Nicolae Darii, R. Turri, K. Sunderland
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Abstract

This paper addresses the challenge of the charging control of Electric Busses (EBs) and implications on network demand. Present literature has already confirmed the possibility to do this type of service and its benefits, but the solutions proposed require a complex communication infrastructure. Moreover, the Distribution Network (DN) must be ready to an increased prevalence for reverse power flow manifest by mainstreaming of EVs. In this context, the paper proposes a transitional solution to host the EBs until the required communication infrastructure is mature enough. The Smart Charging (SC) method proposed here relies instead on the Day-Ahead Energy Market to forecast the network working conditions. The method also facilitates distributed photovoltaic (PV) production so that network demand reference is based on net demand. The algorithm focuses on load-levelling or peak-shaving as the primary objective, in the optimisation of individual charger current per vehicle and per time step to realise an overall charging strategy for the charging station. The strategy seeks to control fleet charging by managing how individual vehicle charging is interchangeable based on an 80% vehicle state-of-charge objective. The algorithm achieves a scheduling capability for the EBs that transit through the Charging Station (CS) through optimum load-levelling/peak-shaving based on the size of the fleet.
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基于单向智能充电的电动客车需求管理
本文讨论了电动公交车充电控制的挑战及其对网络需求的影响。目前的文献已经证实了这种服务的可能性及其好处,但是所提出的解决方案需要一个复杂的通信基础设施。此外,配电网(DN)必须准备好应对电动汽车主流化所带来的反向潮流的日益流行。在这种情况下,本文提出了一种过渡性解决方案来托管EBs,直到所需的通信基础设施足够成熟。本文提出的智能充电(SC)方法依赖于日前能源市场来预测电网的工作状态。该方法还促进了分布式光伏发电,使电网需求参考基于净需求。该算法以负载均衡或削峰为主要目标,优化每辆车和每个时间步长的单个充电器电流,以实现充电站的整体充电策略。该策略旨在通过管理基于80%车辆充电状态目标的单个车辆充电的可互换性来控制车队充电。该算法通过基于车队规模的最佳负载均衡/削峰来实现通过充电站(CS)的EBs的调度能力。
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