Medium-voltage distribution network user electricity consumption abnormity diagnosis method based on machine learning

A technology of machine learning and diagnostic methods, applied in the direction of integrated learning, instrumentation, measurement of electricity, etc., can solve problems such as difficult troubleshooting, high line loss, restricting the construction process of first-class distribution networks, etc., to avoid blind inspection of lines and lines. The effect of restoring the damage to normal and having a good application prospect

Pending Publication Date: 2021-12-31
STATE GRID JIANGSU ELECTRIC POWER CO ELECTRIC POWER RES INST +2
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Problems solved by technology

The abnormal cases of electricity users found out by manual investigation mainly rely on the on-site investigation of grassroots employees. Due to factors such as large number of users, complicated equipment, long time consumption, various abnormal electricity usage methods, and difficulty in investigation, it is difficult to be comprehensive and targeted. Evaluate the power consumption status of each user in a timely manner, which will lead to business pain points such as high line loss, high calculation error of medium voltage line loss rate, and low accuracy of reliability analysis, which seriously restricts the construction process of a first-class distribution network

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  • Medium-voltage distribution network user electricity consumption abnormity diagnosis method based on machine learning
  • Medium-voltage distribution network user electricity consumption abnormity diagnosis method based on machine learning
  • Medium-voltage distribution network user electricity consumption abnormity diagnosis method based on machine learning

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Embodiment Construction

[0049] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field of the invention. The terms used herein in the description of the present invention are for the purpose of describing specific embodiments only, and are not intended to limit the present invention. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0051] See figure 1 , an embodiment of the present invention provides a machine learning-based method for diagnosing abnormal power consumption of users in a medium-voltage d...

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Abstract

The invention discloses a medium-voltage distribution network user electricity consumption abnormity diagnosis method based on machine learning. The method comprises the steps of generating a potential electricity consumption abnormity user set based on acquired user name data; on the basis of the potential abnormal power utilization user set, acquiring forward active power, voltage and three-phase current data of the industry to which the potential abnormal power utilization user set belongs and near two cycles; carrying out missing value preprocessing on the obtained data; calculating and adding 5 eigenvalues into historical power consumption data anomaly four-level labels of all the users to form a sample set; dividing the sample set, training an artificial intelligence model, and testing a model effect and model tuning; carrying out model training and evaluation by adopting a random forest in a machine learning integration algorithm; and carrying out batch marking processing by using the trained model. The method is simple in calculation, and can help an operator to find and adjust an abnormal line loss line in time.

Description

technical field [0001] The invention belongs to the field of diagnosing abnormal power consumption of medium-voltage distribution network users, and in particular relates to a method for diagnosing abnormal power consumption of medium-voltage distribution network users based on machine learning. Background technique [0002] The abnormal power consumption of the medium-voltage distribution network refers to abnormal phenomena such as component failure, abnormal data collection, and abnormal power consumption by criminals. The abnormal cases of electricity users traced out manually mainly rely on the on-site investigation of grassroots employees. Due to factors such as large number of users, complicated equipment, long time-consuming, various abnormal electricity usage methods, and difficulty in investigation, it is difficult to be comprehensive and targeted. Evaluating the power consumption status of each user in a timely manner will lead to business pain points such as high...

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Application Information

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IPC IPC(8): G01R31/08G06N20/20G06Q50/06
CPCG01R31/086G01R31/088G06N20/20G06Q50/06
Inventor 陈烨陈锦铭叶迪卓然郭雅娟刘伟袁栋蔡云峰程力涵焦昊李岩
Owner STATE GRID JIANGSU ELECTRIC POWER CO ELECTRIC POWER RES INST
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