Photovoltaic power generation power prediction method

A photovoltaic power generation and prediction method technology, applied in the direction of prediction, instrumentation, data processing applications, etc., can solve the problems of power grid reliability and stability impact, large weather influence, photovoltaic power station can not be easily controlled, etc., to achieve the reduction characteristics Extraction workload, improved prediction accuracy, and the effect of simple output power

Inactive Publication Date: 2018-10-23
GUANGDONG UNIV OF TECH
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Problems solved by technology

Renewable energy power generation equipment such as photovoltaic power generation panels must generate energy according to the current weather conditions, which is greatly affected by the weather, and the power generation has strong randomness and volatility, which means that photovoltaic power stations cannot are as easily controlled as conventional p

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  • Photovoltaic power generation power prediction method
  • Photovoltaic power generation power prediction method
  • Photovoltaic power generation power prediction method

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Embodiment 1

[0038] A method for predicting photovoltaic power generation, this embodiment chooses to use python language and Keras deep learning framework, such as figure 1 As shown, the method includes the following steps:

[0039] S1: Obtain data, read all historical data of photovoltaic power generation and corresponding meteorological data from the system database; each piece of historical meteorological data in step S1 includes light intensity, ambient temperature, humidity, wind speed, wind direction and corresponding photovoltaic power generation Power, the time interval between each piece of data is at the minute level, for example, the interval is 10 minutes.

[0040] S2: Data preprocessing. The data imported from the database cannot be used directly and needs to be processed. Each data variable in the data set is normalized to (-1,1), and the data of different representations is reduced to within the same scale to eliminate the dimensional influence between the data; the data d...

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Abstract

The invention discloses a photovoltaic power generation power prediction method, which comprises the following steps that: S1: obtaining data, and reading the historical data of all photovoltaic powergeneration power and corresponding meteorological data from a system database; S2: carrying out data preprocessing, and carrying out normalization on each data variable in a dataset to (-1,1); S3: establishing a prediction network model; S4: training the model, and according to the preprocessed sample data, adopting an error counterpropagation training method to train the model; S5: testing and assessing the model; S6: storing the model, and storing the model which passes the test and is assessed to be qualified in S5 into a computer ROM (Read Only Memory) unit; and S7: predicting the photovoltaic power generation power, calling a photovoltaic power generation power prediction model stored in S6 from the computer ROM unit, and carrying out calculation to obtain the prediction value of thephotovoltaic power generation power.

Description

technical field [0001] The present invention relates to the field of photovoltaic power generation forecasting, and more specifically, to a method for forecasting photovoltaic power generation power. Background technique [0002] As more and more renewable energy sources are connected to the grid, the research field of predictive analysis of renewable energy generation power has been receiving much attention in the past decade. Renewable energy power generation equipment such as photovoltaic power generation panels must generate energy according to the current weather conditions, which is greatly affected by the weather, and the power generation has strong randomness and volatility, which means that photovoltaic power stations cannot It is as easy to control as a conventional power station. Due to the continuous increase of photovoltaic power generation connected to the grid, this will have a great impact on the reliability and stability of the power grid operation. How to ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y04S10/50
Inventor 胡俊灵武小梅汤伟成
Owner GUANGDONG UNIV OF TECH
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