Semi-Stochastic Load Model for Heavy Goods Electric Vehicles Depot Charging Considering the Potential for Demand Side Management
Semi-Stochastic Load Model for Heavy Goods Electric Vehicles Depot Charging Considering the Potential for Demand Side Management
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DOI：
10.1109/ciees55704.2022.9990821
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
O. Shariati;P. Coker;S. T. Smith;B. Potter
中科院分区：
文献类型：
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作者：
O. Shariati;P. Coker;S. T. Smith;B. Potter
道路车辆电动化的研发一直以轻型乘用车和货车为主。然而，电动汽车(EV)技术的最新发展引起了人们对重型汽车电气化的关注，并引发了对车队充电概况和对电网的相关影响的问题。建立了重型电动汽车车辆段充电需求分布的半随机模型。通过建立有管理和无管理的日负荷分布模型，研究了典型负荷分布的特点和需求侧管理对价格信号的响应潜力。从电网的角度，研究了充电约束和车辆段最优充电的问题，以了解如何满足车队的需求。这项工作的结果为研究重型汽车电气化对电网的影响以及基于所采取的充电策略的电网所需的最大功率铺平了道路。这项研究可以为围绕车队充电地点采用灵活性计划或网络加固计划提供参考-帮助缓解电网因未来需求增加而可能面临的总体压力。
Research and development on the electrification of road vehicles have been dominated by light-duty passenger vehicles and vans. Recent developments in Electric Vehicle (EV) technology, however, are bringing attention to the electrification of heavy-duty vehicles and raising questions about fleet charging profiles and related implications for power networks. In this paper, a semi-stochastic model is developed for the simulation of Heavy Goods Electric Vehicle (HGEV) depots' charging demand profiles. The modelling of daily fleet charging profiles, managed and unmanaged, are addressed in this paper to investigate the characteristics of the typical load profile and the potential of demand side management in response to price signals. Issues of charging constraint and optimal depot charging, from a power network perspective, have been applied to understanding how the fleet demand is met. The findings of this work paves the way to study the impacts of heavy-duty vehicle electrification on the network and the maximum power demanded from the grid based on the charging strategies taken. Adoption of flexibility programs or network reinforcement plans around sites of fleet charging can be informed by this study - helping to mitigate the overall stress that the grid could face due to increasing future demands.