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Photovoltaic power station ultra-short-term power prediction method based on meteorological data similarity analysis and LSTM neural network

A technology of similarity analysis and meteorological data, applied in the field of ultra-short-term power forecasting of photovoltaic power plants, it can solve the problems of long historical time and real-time limitations of training historical data, and achieves a strong environmental applicability, improved accuracy, and strong innovation. Effect

Inactive Publication Date: 2019-08-20
FUZHOU UNIV
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Problems solved by technology

However, most of them require a large amount of training history data and a long history time, and the improvement of real-time performance is also greatly limited.

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  • Photovoltaic power station ultra-short-term power prediction method based on meteorological data similarity analysis and LSTM neural network
  • Photovoltaic power station ultra-short-term power prediction method based on meteorological data similarity analysis and LSTM neural network
  • Photovoltaic power station ultra-short-term power prediction method based on meteorological data similarity analysis and LSTM neural network

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[0040] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0041] It should be pointed out that the following detailed description is exemplary and is 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.

[0042] 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 combina...

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Abstract

The invention relates to a photovoltaic power station ultra-short-term power prediction method based on meteorological data similarity analysis and an LSTM neural network. The method comprises steps of selecting power generation power and corresponding meteorological data in the same time period of each day of one month before a day the predicted time period belongs to; carrying out Pearson correlation degree analysis on each meteorological data and the power output; selecting meteorological data with the highest correlation degree, and selecting an initial value, an average value and a tail value of the data in the time period to form a three-dimensional coordinate point; carrying out similarity analysis on meteorological data of unit time before the prediction time and a corresponding meteorological data set of a selected time period by utilizing Euclidean metric; and obtaining meteorological data and power data in a similar time period in which the Euclidean value is smaller than aspecified value, and finally predicting the generated power by adopting the trained LSTM model. According to the method, the generated power of the ultra-short-term photovoltaic power station can be predicted quickly and accurately.

Description

technical field [0001] The invention relates to the field of ultra-short-term power forecasting of photovoltaic power plants, in particular to a method for realizing ultra-short-term power forecasting of photovoltaic power plants based on meteorological data similarity analysis and LSTM neural network. Background technique [0002] Due to its stable, sustainable and environmentally friendly characteristics, renewable energy has become the most reliable way to obtain energy to replace various traditional energy sources in the future. Under the complex situation of the world's energy structure, the development of renewable energy is a bargaining chip for my country's external energy supply. , it is of great strategic significance to solve the problems of fossil energy depletion and environmental pollution. In recent years, my country's determination to develop new energy has been reflected in the rapid development of various new energy power generation fields. Among the many ren...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/06G06Q10/04G06K9/62G06N3/04
CPCG06Q50/06G06Q10/04G06N3/04G06F18/214
Inventor 林培杰陈标炜赖云锋程树英陈志聪吴丽君郑茜颖
Owner FUZHOU UNIV
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