Differential evolution random forecast classifier-based photovoltaic array fault diagnosis method

Abstract

The invention relates to a differential evolution random forecast classifier-based photovoltaic array fault diagnosis method. The method comprises the steps of firstly, collecting photovoltaic array voltages under various working conditions and currents of photovoltaic strings, and performing identification on various working conditions by different identifiers; secondly, determining a quantity range of decision trees in a random forest model by adopting an out-of-bag data-based classification misjudgment rate mean value; thirdly, performing global optimization on the quantity range of the decision trees by utilizing a differential evolution algorithm to obtain an optimal decision tree quantity value; fourthly, substituting the calculated optimal decision tree quantity value into a randomforecast classifier, and training samples to obtain a random forecast fault diagnosis training model; and finally, performing fault detection and classification on a photovoltaic array by utilizing the training model. According to the method, the model training speed can be greatly increased while the optimal model classification accuracy is ensured, so that the fault detection and classificationof the photovoltaic power generation array are realized more quickly and accurately.

Description

technical field [0001] The invention relates to a photovoltaic array fault detection and classification technology, in particular to a photovoltaic array fault diagnosis method based on a differential evolution random forest classifier. Background technique [0002] Large-scale photovoltaic power plants are an important way to utilize new energy. The core photovoltaic power generation arrays are affected by the external natural environment and self-aging problems during operation, and some failures will inevitably occur. The photovoltaic system is relatively large, and once a failure occurs, it will cause great damage to the entire photovoltaic power generation system. If these faults are not detected and eliminated in time, it will directly affect the normal operation of the photovoltaic power generation system, and even burn out the battery components and cause a fire in severe cases. Therefore, realizing the fault diagnosis of the photovoltaic system is of great signific...

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Problems solved by technology

[0005] At present, the photovoltaic array fault diagnosis method based on the differential evolution random forest classifier proposed by the present invention has not yet been seen in the published literature and patents

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