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A Method for Establishing Spatial Wind Field Prediction Model Based on Correlation Coefficient

A technology of correlation coefficient and forecasting model, applied in forecasting, data processing applications, instruments, etc., can solve problems such as roughness and insufficient wind direction, and achieve high efficiency and accurate forecasting results

Active Publication Date: 2021-05-18
HARBIN INST OF TECH
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Problems solved by technology

The existing spatial wind field prediction models are mainly aimed at average information, and the consideration of terrain, roughness and wind direction is seriously insufficient

Method used

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  • A Method for Establishing Spatial Wind Field Prediction Model Based on Correlation Coefficient
  • A Method for Establishing Spatial Wind Field Prediction Model Based on Correlation Coefficient
  • A Method for Establishing Spatial Wind Field Prediction Model Based on Correlation Coefficient

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Embodiment 1

[0042] A method for establishing a spatial wind field prediction model based on correlation coefficients, the steps are as follows:

[0043] According to CFD Computational Fluid Dynamics (CFD Computational Fluid Dynamics) numerical simulation space wind field results, calculate the correlation coefficient between each space point position and observation point position:

[0044] Cor ij =corrcoef(ux i ,ux j ) (1)

[0045] where ux i is the fluctuating wind speed at observation point i, ux j Fluctuating wind speed at any point j in space, Cor ij is the correlation coefficient between any point in space and the observation point;

[0046] Calculate the wind speed at any point in space based on the information of two adjacent observation points. It needs to be discussed according to the situation: the selected parameter criterion is the difference between any point in space and the average wind direction angle of the observation point and the size of the correlation coeffic...

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Abstract

The invention proposes a correlation coefficient-based method for establishing a space wind field prediction model, and uses a small number of observation point data to predict the entire space wind field information. According to the results of CFD numerical simulation of the spatial wind field, the correlation coefficient between the position of each spatial point and the position of the observation point is calculated first; then, the wind speed at any point in space is calculated according to the information of two adjacent observation points. For the correlation coefficient, if the correlation coefficient between two adjacent observation points and any point in the space exceeds the critical value, it is considered that the two observation points are in the same vortex, and the correlation between the two is very large. At this time, the correlation coefficient with any point in the space is selected The larger observation point is used as the basis for predictive model analysis; if the correlation coefficient between the observation point and any point in the space is less than the critical value, the data of the two observation points are used to superimpose and solve the wind speed at any point in the space. According to the above method, the time history of wind speed at any point in space can be predicted, and the wind field data of the whole field can be obtained. The invention has the advantages of high prediction efficiency, accurate, real and comprehensive results.

Description

technical field [0001] The invention relates to a method for establishing a spatial wind field prediction model based on a correlation coefficient. Background technique [0002] As national infrastructure, long-span bridges and wind power plants inevitably need to consider the impact of wind in the initial stage of project evaluation and in the later stage of operation. Accurate spatial wind field can be used in the site selection of wind power plants and long-span bridges, so that they are located in the best wind resource and the least wind damage position respectively. On-site monitoring is the best way to obtain wind field in local space. However, due to the need to measure a large number of observation points at the same time, it is very difficult and expensive to implement. Considering the sparsity and inhomogeneity of spatial monitoring points, how to use a small amount of observation point information to obtain spatial wind field data is particularly important. Exi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/06315G06Q50/06
Inventor 陈文礼任贺贺李惠
Owner HARBIN INST OF TECH
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