A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts
A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts
复制标题
DOI：
10.1016/j.apenergy.2015.01.144
复制
发表时间：
2015-11
期刊：
影响因子：
11.2
通讯作者：
M. Neaimeh;R. Wardle;Andrew M. Jenkins;Jialiang Yi;G. Hill;Padraig F. Lyons;Y. Huebner;Phil T. Blythe-P
中科院分区：
文献类型：
--
作者：
M. Neaimeh;R. Wardle;Andrew M. Jenkins;Jialiang Yi;G. Hill;Padraig F. Lyons;Y. Huebner;Phil T. Blythe-P
这项工作使用概率方法结合现实世界电动汽车充电配置文件和住宅智能电表负载需求的两个独特数据集。这些数据用于研究电动汽车（EV）的使用对配电网络的影响。使用了代表城市和农村地区的两个真实网络和代表英国重载配电网络的通用网络。研究结果表明，配电网络不是一个同质群体，其容纳电动汽车的能力各不相同，而且比之前的研究表明的能力更大。事实证明，考虑电动汽车充电需求的空间和时间多样性可以减少对配电网络的估计影响。建议配电网络运营商与新的市场参与者（例如充电基础设施运营商）合作，支持广泛的充电基础设施的推出，从而使网络更加强大；为需求侧管理创造更多机会；减少与电动汽车充电需求的随机性相关的规划不确定性。
This work uses a probabilistic method to combine two unique datasets of real world electric vehicle charging profiles and residential smart meter load demand. The data was used to study the impact of the uptake of Electric Vehicles (EVs) on electricity distribution networks. Two real networks representing an urban and rural area, and a generic network representative of a heavily loaded UK distribution network were used. The findings show that distribution networks are not a homogeneous group with a variation of capabilities to accommodate EVs and there is a greater capability than previous studies have suggested. Consideration of the spatial and temporal diversity of EV charging demand has been demonstrated to reduce the estimated impacts on the distribution networks. It is suggested that distribution network operators could collaborate with new market players, such as charging infrastructure operators, to support the roll out of an extensive charging infrastructure in a way that makes the network more robust; create more opportunities for demand side management; and reduce planning uncertainties associated with the stochastic nature of EV charging demand.