Hot spot fault detection method for photovoltaic cell panel

Abstract

The invention discloses a hot spot fault detection method for a photovoltaic cell panel, and belongs to the field of fault detection of a photovoltaic power generation system. The method comprises the steps: collecting infrared images in different hot spot fault states; carrying out the preprocessing and segmenting of the infrared images, and extracting a hot spot fault characteristic vector; training an SVM multi-fault detection model, and optimizing the parameters in the SVM through employing PSOM; and finally building a hot spot fault detection model for the photovoltaic cell panel. The method achieves the hot spot fault detection of the photovoltaic cell panel, gives a hot spot damage level, provides precise hot spot fault information, and prompts the safe and effective operation of the photovoltaic power generation system.

Description

technical field [0001] The invention relates to the field of fault detection of a photovoltaic power generation system, in particular to a method for detecting a fault of a hot spot of a photovoltaic battery board. Background technique [0002] As a renewable and non-polluting new energy source, solar energy has attracted more and more attention, and the installed capacity of photovoltaic power plants has grown rapidly every year. With the rapid development of the photovoltaic industry, the automatic monitoring and fault diagnosis of the working status of photovoltaic power stations has become the primary task of maintaining the normal operation of the power station. The operation of photovoltaic power plants is closely related to the working status of each photovoltaic array. When partial shading or component aging occurs in photovoltaic modules, the hot spot effect will affect the photovoltaic conversion. If the situation is not detected in time, it will cause permanent d...

AI Technical Summary

Problems solved by technology

[0004] At present, in order to directly and quickly detect the hot spot effect of photovoltaic panels, the infrared image-based method mostly uses the segmentation and feature extraction of the original image, and then uses the fuzzy reasoning method to identify the working status of the photovoltaic module, and the fuzzy reasoning lacks self-learning ability , poor generalization ability

Chinese patent application 201510331763.9 discloses a photovoltaic module fault prompt method and system based on image recognition. This method only uses threshold value comparison method to identify faults, and the reliability is not high.

However, these methods need to consider different environmental information, manual data collection in the early stage is cumbersome, and the workload is heavy

However, there are still few researches on methods for hot spot fault diagnosis of photovoltaic panels based on infrared images in relevant literature and patents.

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