Wind power combined prediction method considering spatial correlation and corrected numerical weather forecast

A technology of numerical weather prediction and spatial correlation, which is applied in the direction of forecasting, calculation, data processing, etc., and can solve the problems of not considering the timing of wind power prediction and the inaccuracy of spatial numerical weather prediction, etc.

Active Publication Date: 2021-01-29
SICHUAN UNIV
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Problems solved by technology

At the same time, none of the existing studies have taken into account factors such as the tempor

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  • Wind power combined prediction method considering spatial correlation and corrected numerical weather forecast
  • Wind power combined prediction method considering spatial correlation and corrected numerical weather forecast
  • Wind power combined prediction method considering spatial correlation and corrected numerical weather forecast

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Embodiment

[0067] Such as figure 1 As shown in Figure 4, the wind power combination prediction method that takes into account spatial correlation and revised numerical weather prediction includes the following steps:

[0068] S100, reading the historical data of the wind farm a and the data of various meteorological factors in the numerical weather forecast, the meteorological factors at least include wind speed, wind direction, temperature, air pressure, and relative humidity;

[0069] S200. Screen out the meteorological factors with strong correlation with wind power among the various meteorological factors through the automatic correlation determination algorithm, use their data as input variables, establish a prediction model based on Gaussian process, and obtain the wind power prediction value P 1 ;

[0070] S300. Establish a wind speed correction model through the corresponding known wind speed data, and use the wind speed data corrected by the wind speed correction model as the i...

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Abstract

The invention discloses a wind power combined prediction method considering spatial correlation and corrected numerical weather forecast, aiming at the defects of the traditional GP based on a singlekernel function, combining a plurality of kernel functions to obtain an optimal kernel function scheme, and establishing a prediction model on the basis of the GP based on the combined kernel function. In consideration of high data complexity of multi-dimensional meteorological factors, key factors are screened through an automatic correlation judgment algorithm, and an NWP wind speed deviation correction model is established. And meanwhile, wind speed time sequences of the target wind power plant and the adjacent wind power plant are analyzed by utilizing a spatial correlation method, a timedifference corresponding to the strongest correlation is solved by utilizing a Pearson correlation coefficient method, and a spatial correlation model is established. And based on a combined weightedprediction model of the above model, a combined model weight coefficient is obtained through a Lagrange method. Therefore, the numerical weather forecast deviation correction method and the spatial correlation method are effectively combined through the combined weighted prediction model, and the prediction precision of the wind power is improved.

Description

technical field [0001] The invention relates to the technical field of wind power forecasting, in particular to a wind power combination forecasting method that takes into account spatial correlation and corrected numerical weather forecast. Background technique [0002] The depletion of fossil energy and the environmental pollution it brings are becoming more and more serious, and the task of developing renewable energy is imminent. Wind energy, as a green and non-polluting renewable energy, has seen a continuous increase in the penetration rate in the power grid in recent years. According to the data provided by the Global Wind Energy Council, by 2018, the global installed capacity of wind power has reached 591GW, of which China has 184GW, ranking first in the world in terms of wind power installed capacity. However, the randomness and intermittency of wind power output have caused great difficulties in its accurate prediction, and brought certain challenges to the safe a...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y02A30/00
Inventor 向月胡帅刘俊勇
Owner SICHUAN UNIV
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