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Green neighbourhoods in low voltage networks: measuring impact of electric vehicles and photovoltaics on load profiles

机译:低压网络中的绿色社区:测量电动汽车和光伏发电对负荷分布的影响

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摘要

In the near future various types of low-carbon technologies (LCTs) are expected to be widely employed throughout the United Kingdom. However, the effect that these technologies will have at a household level on the existing low voltage (LV) network is still an area of extensive research. We propose an agent based model that estimates the growth of LCTs within local neighbourhoods, where social influence is imposed. Real-life data from a LV network is used that comprises of many socially diverse neighbourhoods. Both electric vehicle uptake and the combined scenario of electric vehicle and photovoltaic adoption are investigated with this data. A probabilistic approach is outlined, which determines lower and upper bounds for the model response at every neighbourhood. This technique is used to assess the implications of modifying model assumptions and introducing new model features. Moreover, we discuss how the calculation of these bounds can inform future network planning decisions.ud
机译:在不久的将来,各种低碳技术(LCT)有望在整个英国广泛使用。但是,这些技术将在家庭层面上对现有的低压(LV)网络产生的影响仍然是广泛研究的领域。我们提出了一种基于主体的模型,该模型可估计LCT在受到社会影响的地方社区内的增长。使用来自LV网络的真实数据,该数据包含许多社会不同的社区。借助此数据,研究了电动汽车的使用以及电动汽车和光伏发电的综合使用情况。概述了一种概率方法,该方法确定每个街区模型响应的上下限。该技术用于评估修改模型假设和引入新模型功能的含义。此外,我们讨论了这些界限的计算如何为将来的网络规划决策提供信息。 ud

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