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A short-term wind speed prediction method and system based on phased global optimization

A technology for wind speed forecasting and overall optimization, applied in forecasting, data processing applications, instruments, etc., to solve problems such as inability to obtain forecast model parameters, grid scheduling, reaction of unit combination operations, and reduced wind speed forecasting accuracy.

Active Publication Date: 2018-05-29
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

The parameter selection of each stage method is mostly based on experience or trial and error, and the optimal prediction model parameters cannot be obtained by optimizing each stage independently, and the parameters of the combined methods affect each other, which reduces the accuracy of wind speed prediction , on the contrary, it has a negative effect on the power grid dispatching and unit combination operation, and ultimately affects the stable operation of the power grid

Method used

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  • A short-term wind speed prediction method and system based on phased global optimization
  • A short-term wind speed prediction method and system based on phased global optimization
  • A short-term wind speed prediction method and system based on phased global optimization

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Embodiment

[0163] The method of the present invention is described in detail below as the implementation object of the present invention with the wind speed data of Dabancheng Wind Field:

[0164] Step 1: Preparation and initialization. Collect the wind speed time series data of the Dabancheng wind field. The total length of the time series data Wind is 1008, and the 10-length sequence X is selected as the forecast input, and the forecast output is the wind speed Y at the next moment, namely:

[0165] X(i)=wind(i,i+1,...,i+9), Y(i)=wind(i+10), i=1,...,998, construct 998 pairs of wind speed prediction Input-output data pairs, the first 499 pairs of data are used as model training (train), and the last 499 pairs of data are used as model testing (test); the model training (train) data is used for parameter optimization of the wind speed mixed prediction model, according to image 3 The method shown optimizes the parameters of the wind speed mixing prediction model as a whole, and the step...

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Abstract

The invention provides a short-term wind speed prediction method based on phased global optimization. A wind speed mixed prediction model characterized in that variational mode decomposition is employed for a time series data composition model, Gram-Schmidt orthogonal is employed for a feature extraction model and an extreme learning machine is employed for a basic learning model; a gravitationalsearch algorithm is employed for global optimization of the parameters of the wind speed mixed prediction model; the optimal prediction model parameters suitable for short-term wind speed prediction can be selected preferentially to achieve accurate prediction of the wind speed. The invention also provides a short-term wind speed prediction system based on phased global optimization.

Description

technical field [0001] The invention belongs to the field of wind speed prediction, and more specifically relates to a short-term wind speed prediction method and system based on staged overall optimization. Background technique [0002] With the rapid growth of new energy, wind power as a green energy has developed rapidly in the past century. With the continuous growth of wind power access, the impact of intermittent and random fluctuations of wind power generation on the power grid is becoming more and more obvious. The nonlinear and unstable characteristics of wind speed increase the difficulty of accurate modeling and prediction of wind speed. Accurate wind speed prediction can estimate the power of wind power generation, thus providing the necessary basis for power grid dispatching, unit combination operation, wind farm operation and maintenance, etc. [0003] Numerical weather prediction (NWP) refers to solving the fluid dynamics and thermodynamic equations describi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/00
CPCG06N3/006G06Q10/04G06Q50/06
Inventor 李超顺汪赞斌甘振豪侯进皎王若恒
Owner HUAZHONG UNIV OF SCI & TECH
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