Fault diagnosis method for photovoltaic modules based on internal equivalent parameters

Abstract

The invention discloses a photovoltaic assembly fault diagnosing method based on internal equivalent parameters. The method includes the steps of conducting feature extraction for internal equivalent parameters of a photovoltaic assembly under different faults, establishing four photovoltaic assembly fault diagnosing models based on external characteristic electrical parameters by employing the BP neural network, the RBF neural network, Elman neural network and the RVM algorithm to conduct preliminary fault diagnosis for the photovoltaic assembly, providing a photovoltaic assembly data fusion fault diagnosing model based on improved evidence similarity, and conducting fusion diagnosis output on a decision layer with the diagnosing result of the four models as function values of basic probability assignment (BPA) of the improved data fusion algorithm. The photovoltaic assembly fault diagnosing method effectively improves the credibility of the fault diagnosing result and reduces the misjudgement rate due to the fact that the fault diagnosing result is obtained through a single method.

Description

technical field [0001] The invention relates to a fault diagnosis method for a photovoltaic module, belonging to the field of new energy power generation. Background technique [0002] At present, the excessive exploitation and use of fossil energy has led to a sharp deterioration of the ecological environment, which seriously threatens the survival of human beings and the sustainable development of society. One of the effective ways to resolve the crisis of energy and ecological environment is to reduce the excessive dependence on fossil energy and actively develop the utilization of renewable energy. Among them, photovoltaic power generation has been widely developed and applied due to its unique power generation characteristics. However, due to the long-term operation of photovoltaic modules in a relatively harsh environment, various failures are unavoidable, which greatly reduces the actual service life. Once a photovoltaic module fails to operate, the direct harm is to...

AI Technical Summary

Problems solved by technology

However, due to the long-term operation of photovoltaic modules in a relatively harsh environment, various failures are unavoidable, which greatly reduces the actual service life

Once a photovoltaic module fails to operate, the direct harm is to damage the module itself and reduce the power generation efficiency; the indirect harm is to cause the entire photovoltaic power generation system to fail to operate normally or affect the power grid, thereby causing major economic losses

[0003] In fact, due to the complex and changeable external environment, photovoltaic modules present complex fault causes and diverse types of faults, and the existing fault diagnosis techniques and methods are difficult to meet the needs of fault diagnosis of photovoltaic modules. Therefore, research on effective photovoltaic module faults Diagnostic methods are imminent

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