Method and device for predicting output power of photovoltaic power generation system

Abstract

The embodiment of the invention discloses a method for predicting output power of a photovoltaic power generation system, variation mode decomposition is performed on historical output power data of the photovoltaic power generation system in a preset time period, an extreme learning machine prediction model is built according to a plurality of decomposition components obtained by decomposition and corresponding meteorological data, a prediction result of each decomposition component is calculated according to the extreme learning machine prediction model, and a sum of the prediction results is used as a prediction result of the output power of the photovoltaic power generation system. A variation mode decomposition algorithm has good noise robustness and non-recursiveness, and selection of reasonable parameters can effectively avoid a mode aliasing phenomenon, thereby obtaining a high-accuracy decomposition signal, and facilitating improvement of prediction accuracy; and the characteristics of good generalization performance and fast learning speed of an extreme learning machine can further improve prediction precision and prediction efficiency. In addition, the embodiment of the invention also provides a corresponding realization device, which further enables the method to have practicability, and the device has corresponding advantages.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of photovoltaic power generation, and in particular to a method and device for predicting output power of a photovoltaic power generation system. Background technique [0002] With the increasing consumption of conventional energy (such as petroleum, coal and other fossil energy), the environmental pollution caused by the consumption of conventional energy is becoming more and more severe, and the reserves of conventional energy are limited, which has prompted the development of new energy sources. (such as solar energy, wind energy, ocean energy, etc.) vigorous research and development. As an environmentally friendly, safe, extensive and sufficient renewable new energy, solar energy is the most promising green energy. [0003] Photovoltaic power generation is a technology that uses the photovoltaic effect at the semiconductor interface to directly convert light energy into electrical ...

AI Technical Summary

Problems solved by technology

Although the empirical mode decomposition method can realize the smooth processing of nonlinear and non-stationary signals, the empirical mode decomposition method lacks strict mathematical foundation, low algorithm efficiency, modal aliasing, poor noise immunity and end-point effects.

Due to these disadvantages of the empirical mode decomposition method, a series of components obtained by its decomposition still have a large prediction error after rebuilding the prediction model

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