An intelligent photovoltaic array fault diagnosis method based on optimal rotating forest

Abstract

The invention relates to an intelligent photovoltaic array fault diagnosis method based on an optimal rotating forest. Firstly, the data of photovoltaic electrical characteristics under various operating conditions are collected and mapped to obtain the overall fault characteristics. Secondly, the ReliefF feature selection algorithm is used to rank the importance weights of the fault features, andthe most important fault features are obtained. Then, the input variables of the base classifier are obtained by using the improved rotating forest algorithm. Furthermore, the limit learning machinereplaces the decision tree in the original rotating forest algorithm to overcome the over-fitting problem and obtain the optimal model parameters by traversal method. Furthermore, the optimal trainingmodel of rotating forest fault diagnosis is obtained by combining the improved rotating forest algorithm with the limit learning algorithm to train each sample in the training set. Finally, the training model is used to detect and classify the fault of PV arrays. The method of the invention has high classification accuracy and is an effective alternative scheme for photovoltaic fault diagnosis.

Description

technical field [0001] The invention relates to photovoltaic power generation array fault detection and classification technology, in particular to an intelligent photovoltaic array fault diagnosis method based on optimal rotating forest. Background technique [0002] As an alternative energy source, solar energy has received extensive attention in recent years. According to the latest announcement of the International Renewable Energy Agency (IRENA), by the end of 2017, the installed capacity of global photovoltaic power plants had reached 390GW. However, photovoltaic power plants are subject to multiple failures due to external harsh operating conditions, which may result in a large amount of energy loss as well as potential safety risks. 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, fau...

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Problems solved by technology

[0005] At present, the intelligent photovoltaic array fault diagnosis method based on the optimal rotation forest proposed by the present invention has not yet been seen in the published literature and patents.

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