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

机译:基于多源数据融合的分发网络电力故障激励分析

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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.
机译:停电导致更复杂的问题,因为准确,电源故障的预警需要使用多视角来的大数据分析来深入分析停电,尝试全景分析及其对分布网络功率因数的影响。为此,提出了一种简单易于分析了基于多源数据融合的分配网络的中断风险的简单方法。基于通过数据的营销和分发方法,构建了停电事件建设停电事件信息,然后返回的主成分分析和逻辑成熟的返回用于区分电源场景和相应的非遮光场景,并找到明显的标志在“分销网络故障中的停电”之前。本文提出的方法的可行性和正确性通过示例验证。

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