Method utilizing independent component analysis and S transformation to detect photovoltaic system fault arcs under system process coupling conditions

Abstract

The invention discloses a method utilizing independent component analysis and S transformation to detect photovoltaic system fault arcs under system process coupling conditions. According to the method, based on a photovoltaic system output current signal, a current independent main source signal is acquired through independent component analysis, after Fourier transformation of the signal, variance processing on the frequency information is carried out to acquire a first characteristic quantity, the current is processed through S transformation, and a second characteristic quantity is acquired through time and high frequency component integration of an acquired time frequency matrix. After comparing the characteristic quantity value with a corresponding set threshold, a weight coefficient is utilized to realize weighing of output determination results of the two characteristic quantity values on a decision layer, and real-time detection on the photovoltaic system fault arcs is accomplished. The method is advantaged in that through dynamic threshold comparison and weight coefficient weighing of the two decision results, essential difference of the photovoltaic system fault arcs generated in a system process can be obviously mined, the photovoltaic system fault arcs under the system process coupling conditions can be rapidly and accurately cut off, and safe and stable operation capability of the photovoltaic system is improved.

Description

technical field [0001] The invention belongs to the technical field of photovoltaic electrical fault detection, and specifically relates to a method of applying independent component analysis and S transformation to obtain two characteristic values, comparing the characteristic values ​​with corresponding dynamic setting thresholds to obtain two decision results, and using dynamically set The weight coefficient weights the decision results of the two characteristic values ​​to detect the fault arc of the photovoltaic system in real time, and obviously excavates the essential difference of the fault arc of the photovoltaic system that occurs in the system process, and improves the rapidity and reliability of the fault arc detection of the photovoltaic system in the case of coupling In order to ensure that the photovoltaic system can operate stably, safely and economically at any time. Background technique [0002] The global energy crisis and climate warming are becoming more...

AI Technical Summary

Problems solved by technology

If the existing detection algorithm correctly determines the normal output current of the photovoltaic system, the fault arc of the photovoltaic system cannot be detected in time, and the fault arc detection device on the DC side of the corresponding photovoltaic system will refuse to operate, and the fault arc of the photovoltaic system that cannot be eliminated will cause Photovoltaic system fire accidents, resulting in loss of life and p

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