Incentive Analysis of Power Failure in Distribution Network Based on Multi-source Data Fusion

L. Zhong
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引用次数: 0

Abstract

Blackout causes more complex problems, for the accurate, early warning of power failure needs to use big data analysis from multi perspective to in-depth analysis of blackouts, try panoramic analysis and its impact on the distribution network power factor. For this reason, a simple and easy method for analyzing the outage risk of distribution network based on multi-source data fusion is proposed in the paper. Based on the method of marketing and distribution through the data, the blackout Scene Building blackout event information is built, and then principal component analysis and logical mature returned is used to distinguish power scenes and the corresponding non-blackout scene, and find the obvious signs before the power outage of distribution network fault warning. The feasibility and correctness of the method proposed in this paper are verified by an example.
基于多源数据融合的配电网停电激励分析
停电造成的问题更为复杂,为了准确、早期预警停电,需要利用大数据分析从多个角度对停电进行深入分析,尝试全景式分析及其对配电网功率因数的影响。为此,本文提出了一种基于多源数据融合的配电网停电风险分析方法。通过数据营销和分配的方法,构建停电场景构建停电事件信息,然后利用主成分分析和逻辑成熟回归来区分电力场景和相应的非停电场景,并在停电前发现明显的迹象,对配电网进行故障预警。通过算例验证了本文方法的可行性和正确性。
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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