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Statistical consumer modelling based on smart meter measurement data

机译:基于智能电表测量数据的统计消费者建模

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This paper presents an approach for modelling residential load profiles based on measurement data of 291 smart meters over the period of one year. It is shown that the generalised extreme value distribution describes the distribution of the occurring loads for every point in time very well. The parameters of the distribution function depend on the mean power value of all smart meters in each point in time. For modelling realistic load profiles the consumers are assigned to different states, which describe the load within one point in time in relation to the others. By introducing transition matrices for the individual consumers with subdivided time ranges, temporal state changes can be simulated. Finally the synthetic load profiles are generated using Markov chains, based on the transition matrices and the distribution functions.
机译:本文提出了一种基于一年内291个智能电表的测量数据的住宅负荷分布模型的方法。结果表明,广义极值分布很好地描述了每个时间点上出现的负载的分布。分布函数的参数取决于每个时间点上所有智能电表的平均功率值。为了对实际的负载曲线进行建模,将消费者分配给不同的状态,这些状态描述了一个时间点内相对于其他时间点的负载。通过为细分时间范围内的各个消费者引入过渡矩阵,可以模拟时间状态变化。最后,基于过渡矩阵和分布函数,使用马尔可夫链生成综合负荷曲线。

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