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Lorenz perturbation wind speed prediction method based on principal component analysis

A technology of principal component analysis and wind speed prediction, which is applied in the fields of prediction, instrumentation, electrical digital data processing, etc., can solve problems such as unsatisfactory prediction results and neglect of the influence of atmospheric dynamic system disturbances, etc., so as to facilitate large-scale development and utilization , the effect of improving the level of prediction

Active Publication Date: 2017-11-17
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

[0004] Most of the above wind power prediction methods are based on the improvement of the algorithm model and the prediction system, but ignore the research on the disturbance effect on the atmospheric dynamic system, so the prediction effect is not very ideal

Method used

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  • Lorenz perturbation wind speed prediction method based on principal component analysis
  • Lorenz perturbation wind speed prediction method based on principal component analysis
  • Lorenz perturbation wind speed prediction method based on principal component analysis

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Experimental program
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Embodiment

[0097] Collect the raw data observed every 10 minutes in the wind farm, including wind speed, wind direction data, and data such as air temperature, air pressure, specific volume, specific humidity, and surface roughness obtained by cubic spline interpolation; perform related processing.

[0098] Figure 1(a) and (b) are the wind speed distribution of the wind farm every ten minutes and its wind direction rose diagram, it can be seen that the wind speed in figure (a) has typical random fluctuations; the wind speed in figure (b) The wind direction rose diagram has the highest wind speed in the interval (6,8), and the longest color band in the southeast direction, indicating that the wind direction has the highest frequency. Figure 2(a) and (b) are distributions of the Lorenz attractor shape when the Rayleigh number r=23 and r=27. It can be seen that for the same initial value, different Rayleigh numbers will result in different Lorenz attractor shapes . image 3 It is the Lorenz...

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Abstract

The invention discloses a Lorenz perturbation wind speed prediction method based on principal component analysis, and belongs to the technical field of power generation. According to the technical scheme, the principal component analysis is conducted according to original data, then a least square support vector machine (LS-SVM) model is utilized to conduct wind speed prediction on main components and wind speed data, and finally a Lorenz atmospheric perturbation sequence is utilized to correct a preliminary prediction value of the wind speed to improve the prediction level of the wind speed. As is shown by a simulation result, in the prediction process of the wind speed, the perturbation influence of an atmospheric system is fully considered, and the prediction precision of the wind speed is obviously improved. According to the Lorenz perturbation wind speed prediction method based on the principal component analysis, the ignorance of the effects of the atmospheric system in the field of the prediction of the wind speed is made up for, the stability of a wind powder connected grid is guaranteed, and the large-scale development and utilization of a wind resource are guaranteed.

Description

technical field [0001] The invention relates to a method capable of accurately predicting the wind speed of a wind farm, belonging to the technical field of power generation. Background technique [0002] In today's world, the tight supply of fossil fuels has brought about a series of problems such as the environment, ecology, and global climate change. All countries are consciously taking action to solve the dilemma, accelerate energy transformation, and develop renewable energy. As an environmentally friendly, renewable and clean energy, wind energy occupies a pivotal position in low-carbon energy technology and has received extensive attention from all over the world. At the same time, with the increasing share of wind power generation in electricity production, grid operators are facing challenges in terms of power balance, power quality, grid connection stability, and load dispatch planning. Therefore, reliable wind power forecasting methods must be considered in the g...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06K9/62G06Q10/04
CPCG06Q10/04G06F30/20G06F18/2411
Inventor 张亚刚王鹏卉王增平
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)