Temperature prediction method for photovoltaic assembly

Abstract

The invention relates to a temperature prediction method for a photovoltaic assembly. The method comprises: step one, data initialization is carried out and an input vector and a target vector are determined; step two, an assembly temperature prediction model based on a BP artificial neural network is constructed; step three, error counter-propagation algorithm training is executed to obtain outputting of all nodes of a hidden layer and an output layer; step four, a connection weight value is adjusted and all node outputs of the hidden layer and the output layer after adjustment are obtained; and step five, if a convergence condition is met, training is completed; and otherwise, the step three is executed again. On the basis of predication of a photovoltaic assembly temperature, the accuracy of photovoltaic power generation prediction is improved.

Description

technical field [0001] The invention relates to a new energy power prediction method, in particular to a photovoltaic module temperature prediction method. Background technique [0002] The power generated by photovoltaic power plants is closely related to photovoltaic modules. Photovoltaic modules and other semiconductor devices are very sensitive to temperature. As the temperature increases, the band gap of silicon material decreases, which affects the performance parameters of most characterization materials, and then affects the electrical performance parameters of the components, resulting in a decrease in the open circuit voltage of the component, a slight increase in the short circuit current, and a decrease in the overall power. Module temperature is an important factor affecting the conversion efficiency of photovoltaic modules. Accurate prediction of module temperature is helpful to improve the accuracy of photovoltaic power generation prediction. Therefore, phot...

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Problems solved by technology

As the temperature increases, the band gap of silicon material decreases, which affects the performance parameters of most characterization materials, and then affects the electrical performance parameters of the components, resulting in a decrease in the open circuit voltage of the component, a slight increase in the short circuit current, and a decrease in the overall power.

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