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Photovoltaic power station short-term power prediction method based on improved Bi-LSTM

A photovoltaic power station and power forecasting technology, applied in forecasting, neural learning methods, biological neural network models, etc., can solve problems such as not considering historical meteorological data, forecasting effect effects, and ignoring internal influence relationships.

Active Publication Date: 2021-01-22
FUZHOU UNIV
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Problems solved by technology

Many current models only consider the current meteorological data and directly output the predicted value, without considering the historical meteorological data to the current meteorological data, ignoring the internal influence relationship between different time points, which also has a great influence on the final prediction effect

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  • Photovoltaic power station short-term power prediction method based on improved Bi-LSTM
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  • Photovoltaic power station short-term power prediction method based on improved Bi-LSTM

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Embodiment Construction

[0066] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0067] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0068] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinatio...

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Abstract

The invention relates to a photovoltaic power station short-term power prediction method based on improved Bi-LSTM. The method comprises the following steps: extracting original meteorological parameters as input of a photovoltaic power station prediction model; preprocessing the data set; carrying out characteristic parameter selection on the fitting degree of the output power prediction curve ofthe photovoltaic power station by adopting Pearson correlation coefficient analysis; sorting the selected characteristic parameters by adopting a principal component analysis method, and determiningan improved model input data set; taking to-be-predicted day data of three consecutive days obtained by the numerical weather forecast center as a test set; judging the weather type of the to-be-predicted day according to a numerical statistics method, calculating the Euclidean distance between the characteristic parameters of the historical training set and the characteristic parameters of the to-be-predicted day, and selecting a parameter with an error less than 0.5 as the input of an improved model; and building a prediction model, optimizing, setting related parameters of the improved prediction model, and selecting an optimal photovoltaic power station output power prediction effect. According to the invention, the accuracy of photovoltaic power generation output power prediction canbe improved.

Description

technical field [0001] The invention relates to the technical field of output power forecasting of photovoltaic power plants, in particular to a short-term power forecasting method for photovoltaic power plants based on an improved Bi-LSTM. Background technique [0002] Since the current photovoltaic power generation is easily affected by various meteorological and environmental factors, the output power of photovoltaic power plants is intermittent, volatile and unstable. In recent years, photovoltaic power generation has become one of the most important renewable energy sources, and renewable energy has become an important guarantee for the development of the world economy. At present, a large number of photovoltaic power stations have been established around the world to use solar energy for power supply. However, with the expansion of photovoltaic arrays in photovoltaic power plants year by year, especially the fluctuation and randomness of power generation have brought g...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/04G06N3/08G06K9/62G06Q50/06
CPCG06Q10/04G06N3/08G06Q50/06G06N3/044G06N3/045G06F18/2135G06F18/214Y04S10/50
Inventor 陈志聪张财贵吴丽君林培杰程树英
Owner FUZHOU UNIV
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