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Clustering Time Series over Electrical Networks

机译:电网上的时间序列聚类

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摘要

The growing number of renewable energy sources in electrical networks introduces new uncertainties in the electrical network nodes. Reducing the size of electrical networks helps to understand their structure better as well as to plan capacity updates more effectively. The ways of reducing representation of an electrical networks is not a trivial task. In this paper, we consider different methods of clustering of nodal time series data renewable power networks. We propose a clustering method for spatial and temporal data size reduction with local renewable energy as a main driver. The proposed methods are applied to an illustrative 9-bus, 118-bus case studies, and the RE-Europe dataset network.
机译:电网中可再生能源的数量不断增加,给电网节点带来了新的不确定性。减小电气网络的规模有助于更好地了解其结构以及更有效地规划容量更新。减少电网表示的方法并不是一件容易的事。在本文中,我们考虑节点时间序列数据可再生电网的不同聚类方法。我们提出了一种以本地可再生能源为主要驱动力的,用于时空数据缩减的聚类方法。所提出的方法适用于说明性的9总线,118总线案例研究和RE-Europe数据集网络。

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