A wind turbine generator output power prediction method

A technology of output power and prediction method, applied in neural learning methods, computer components, biological neural network models, etc., can solve problems such as inaccurate wind power output power prediction, and achieve the effect of improving accuracy and calculation speed

Pending Publication Date: 2019-06-18
GUANGDONG UNIV OF TECH
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Problems solved by technology

[0005] The present invention provides a method for predicting the output power of wind turbines in order to overcome the inaccurate defect of wind power output power prediction described in the above-mentioned prior art

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  • A wind turbine generator output power prediction method
  • A wind turbine generator output power prediction method
  • A wind turbine generator output power prediction method

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Embodiment Construction

[0043] The accompanying drawings are for illustrative purposes only and cannot be construed as limiting the patent;

[0044] In order to better illustrate this embodiment, some parts in the drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0045] For those skilled in the art, it is understandable that some well-known structures and descriptions thereof may be omitted in the drawings.

[0046] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0047] This embodiment provides a wind turbine output power prediction method, such as figure 1 As shown, the method includes the following steps:

[0048] S1: Obtain meteorological data and historical output data of wind turbines, and construct meteorological matrix and wind turbine output matrix;

[0049] S2: Calculate the fuzzy membership degree of each attribute by fuzzy C-means clusteri...

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Abstract

The invention relates to a wind turbine generator output power prediction method which comprises the following steps: S1, acquiring meteorological data and fan historical output data, and constructinga meteorological matrix and a fan output matrix; S2, calculating the fuzzy membership degree of each attribute by using fuzzy C-means clustering; S3, performing attribute reduction on the meteorological matrix by using a fuzzy rough set method; S4, removing redundant samples from the reduced meteorological matrix by using a neighbor aggregation method; S5, creating a three-layer BP neural network, and training the neural network by using the data of the meteorological matrix from which the redundant samples are removed in the step S4 to obtain a prediction model of the fan output; S6, verifying the effectiveness of the wind power prediction model by using test data; According to the method, the number of samples of meteorological physical values is removed, the prediction precision of theoutput power of the wind turbine generator is improved, meanwhile, the calculation speed of a wind turbine generator output power prediction model is increased, and a necessary theoretical basis canbe provided for power supply management and economic dispatching of a power system.

Description

technical field [0001] The present invention relates to the field of renewable energy output forecasting, and more specifically, to a method for forecasting output power of wind turbines. Background technique [0002] With the rapid development of the world economy, the corresponding energy demand has also increased significantly, and the traditional fossil energy is facing the threat of depletion; at the same time, due to the large-scale consumption of traditional fossil energy, the problem of environmental pollution is also becoming more and more serious. Both social economy and human health pose a serious threat; as a green renewable energy, wind power has been widely used and developed in countries all over the world; but wind energy is also facing prominent problems in the process of rapid development, due to the instability of wind power Wind power generation is volatile and intermittent, which will cause great difficulties to the dispatching of the power grid; at pres...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/08G06Q50/06
CPCY04S10/50Y02E40/70
Inventor 任德江吴杰康毛骁
Owner GUANGDONG UNIV OF TECH
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