Cuckoo search and BP neural network based fault diagnosis method of photovoltaic assembly
A BP neural network and photovoltaic module technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as dangerous maintenance work and high costs, and achieve high diagnostic accuracy, fast convergence speed, and complex calculations low degree of effect
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[0024] Such as figure 1 As shown, the present invention provides a photovoltaic module fault diagnosis method based on cuckoo algorithm and BP neural network, comprising the following steps:
[0025] Step 1, establish the equivalent circuit model of the photovoltaic module, such as figure 2 As shown in , collect all kinds of data output by the photovoltaic module model, filter out the fault data representing the fault type, and set some fault data as training samples;
[0026] Step 2, initialize the weight and threshold of BPNN, initialize the number of nests m, Pa and the maximum number of iterations of the cuckoo retrieval algorithm;
[0027] Step 3, randomly generate m nests, and set the initial position values to w i (0) =[x 1 (0) , x 2 (0) ,...x m (0) ] T , encode and optimize the weights and thresholds of BPNN for training, and use the mean square error as the objective function to record the current optimal bird’s nest position x b (0) ;
[0028] Step 4:...
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