Non-intrusive electric bicycle monitoring method and system based on model self-learning

Abstract

The invention discloses a non-intrusive electric bicycle monitoring method based on model self-learning. The method comprises the following steps of carrying out preprocessing such as filtering and frequency reduction on the total power of a user; performing density clustering on the difference of the active power to obtain a mean value of a maximum density class and a corresponding reactive power mean value in time so as to reconstruct a signal, and screening out a time period containing a charging gentle slope by adopting bilateral filtering, state conversion removal and piecewise linear representation; finding out all suspected charging load events according to a non-intrusive load event detection algorithm, determining all load events caused by charging of the electric bicycle by adopting a sliding window, and completing model self-learning; a non-intrusive load event detection algorithm detecting a charging behavior in real time and performs early warning; on the basis of the charging model, the real-time sensing of the charge state and the calculation of the charging quantity being realized. Whether an electric bicycle charging behavior exists or not can be judged according to the total power of a user, model self-learning is completed, and charging behavior real-time early warning, charge state real-time sensing and charging electric quantity calculation are achieved.

Description

technical field [0001] The invention relates to the field of smart grid electric bicycle charging monitoring, in particular to a non-invasive electric bicycle monitoring method based on model self-learning Background technique [0002] From the current point of view, my country's electric bicycle industry has developed rapidly in recent years, and the demand for electric bicycles is constantly increasing. By the end of 2019, the number of electric bicycles in my country has increased to nearly 300 million. It can be seen that my country's current electric bicycles market demand is very high. However, due to the rapid development, my country's current electric bicycle industry is not very standardized. In order to strengthen management, my country has adopted a production permit system for the production of electric bicycles, requiring enterprises that produce electric bicycles to obtain corresponding permits, although the access requirements are very strict. , but the managem...

AI Technical Summary

Problems solved by technology

[0005]Considering the shortcomings of the existing technology, in order to further promote the popularization and application of electric bicycle charging detection in residential users, and realize the perception and early warning of illegal charging, the present invention combines wireless Supervised non-intrusive load monitoring technology, a non-intrusive electric bicycle monitoring method based on model self-learning is proposed, aiming to solve the problem of difficult investigation of illegal charging of electric bicycles for residential users

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