有意孤岛电网与数据深度

2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) Pub Date : 2017-12-01 DOI:10.1109/CAMSAP.2017.8313149

A. K. Dey, Y. Gel, H. Poor

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引用次数: 3

摘要

提出了一种基于数据驱动的数据深度固有几何概念的电网有意孤岛化新方法。通过在意大利电网中的应用，说明了新型基于深度的孤岛的实用性。研究发现，基于数据深度的光谱聚类在k-way展开方面优于基于k-means的光谱聚类。概述了如何将k深度扩展到张量表示中的多层网格的方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Intentional islanding of power grids with data depth

A new method for intentional islanding of power grids is proposed, based on a data-driven and inherently geometric concept of data depth. The utility of the new depth-based islanding is illustrated in application to the Italian power grid. It is found that spectral clustering with data depths outperforms spectral clustering with k-means in terms of k-way expansion. Directions on how the k-depths can be extended to multilayer grids in a tensor representation are outlined.

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2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

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