Non-invasive type household load intelligent detection method and system

Abstract

The invention relates to a non-invasive type household load intelligent detection method, which comprises: collecting the voltage signal and the current signal at each collection point within a preset cycle threshold at a general entry of at least one household load in a steady operating state; making analysis of the voltage signal and the current signal; obtaining the voltage signal and the sub-current signal corresponding to each load of the at least one load respectively; according to the voltage signal and the sub-current signal corresponding to each load of the at least one load, determining the voltage-current trajectory diagram corresponding to each load; according to the voltage-current trajectory diagram corresponding to each load, extracting the load characteristics information corresponding to the each load; and according to the load characteristics information corresponding to the each load identifying the type of the electrical appliance corresponding to the each load through the support vector machine (SVM). According to the invention, through the analysis of the voltage-current trajectory diagrams of the loads, it is possible to identify the types of the electrical appliances of the loads effectively.

Description

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AI Technical Summary

Benefits of technology

This technology helps manage power usage by various types of devices more effectively without requiring physical inspections or expensive equipment that may be needed for each device being managed. It also identifies specific types of electronic devices based on their energy use patterns during operation.

Problems solved by technology

This patents discusses various techniques used during developing intelligent grids that aim towards reducing economic losses caused by overloading certain parts of houses while improving efficiency. These improvements involve identifying specific devices (electric machines) from among multiple ones based upon factors like how much they consume more electricity than what others). Additionally, these systems require less expensive equipment compared to installing them beforehand due to its higher accuracy.

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