Output power prediction method, device and apparatus of photovoltaic power generation system and medium

Abstract

The embodiment of the invention discloses an output power prediction method, device and apparatus of a photovoltaic power generation system and a computer-readable storage medium. The method comprisesthe following steps: decomposing the historical output power data of a photovoltaic power generation system in a preset time period by an integrated set empirical mode decomposition, inputting the decomposed sub-sequences and corresponding meteorological data into a pre-constructed kernel limit learning machine prediction model, and determining the output power prediction value of the photovoltaic power generation system according to the prediction results of each sub-sequence output by the kernel limit learning machine prediction model. The historical photovoltaic power data is decomposed byusing a complete set of empirical modes, the nonstationarity of the photovoltaic sequence is suppressed and the prediction accuracy of the output power is improved. Through the good generalization performance and fast learning speed of the kernel limit learning machine, the prediction accuracy and efficiency can be further improved. The improved bat algorithm is used to optimize the kernel parameters and penalty coefficients of the kernel limit learning machine, which greatly improves the accuracy of power prediction.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of photovoltaic power generation, and in particular, to a method, device, equipment, and computer-readable storage medium 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...

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Problems solved by technology

[0004] At present, photovoltaic output power prediction methods mainly focus on a single artificial intelligence prediction method, including artificial neural network, support vector machine, etc. A single prediction model is usually limited by its own characteristics, which will not only produce large errors in the prediction results, but also slower learning rate

For example, the BP neural network has disadvantages such as slow learning speed and easy to fall into local extremum; the learning parameters of support vector machine have a great influence on the performance of the prediction model; The final convergence result is easily affected by the size of the algorithm parameters and the initial population

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