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Ensemble prediction method for short-term wind speed of wind power plant

A technology for ensemble forecasting and wind farms, applied to electrical components, circuit devices, AC network circuits, etc., can solve problems such as inapplicability, and achieve the effects of reduced relative root mean square error, high precision, and improved forecasting effect

Inactive Publication Date: 2018-11-13
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

However, when a single boundary layer parameterization scheme is used to forecast wind speed, even the best parameterization scheme combined with this region may not be applicable in other regions

Method used

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  • Ensemble prediction method for short-term wind speed of wind power plant
  • Ensemble prediction method for short-term wind speed of wind power plant
  • Ensemble prediction method for short-term wind speed of wind power plant

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Embodiment Construction

[0024] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0025] A kind of wind farm short-term wind speed ensemble forecasting method of this embodiment, its steps are as follows,

[0026] 1. Collect the measured wind speed data of the wind farm, and perform data preprocessing in combination with the surrounding wind field data and historical data. The preprocessing includes removing outliers and filling in missing data, etc., to obtain the wind speed data after denoising, and pass the completeness and rationality test.

[0027] 2. WRF mode scheme setting

[0028] The design of the WRF mode selected in this example is as follows: a triple nested grid is used, and the forecast area is as follows figure 1 shown. Integral grid design, the grid numbers are 50×60, 55×52, 67×64, the horizontal grid resolutions are 27km, 9km, 3km, and the grid center points are located at 29.788°N and 108.227°E. The g...

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Abstract

The invention discloses an ensemble prediction method for a short-term wind speed of a wind power plant. The ensemble prediction method is based on a WRF mode and a random forest algorithm. The methodcomprises the following steps: based on the WRF mode, choosing 6 different boundary layer parameterization schemes to predict meteorological factors of wind speeds, wind directions and the like at the 70m height; then utilizing varieties of boundary layers parameterization schemes to predict the wind speeds in an ensemble mode; applying the wind speeds predicted by all the single boundary layer parameterization schemes and wind speed data actually detected by an anemometer tower to the random forest algorithm to establish an ensemble prediction model; predicting the wind speed of the wind power plant. The ensemble prediction method disclosed by the invention is a scientific and effective method for predicting the short-term wind speed of the wind power plant, has the characteristics of strong generalization ability, good stability and high prediction accuracy, improves wind power prediction accuracy, is favorable for dispatch and operation of an electric power system and has certain practical value.

Description

technical field [0001] The invention relates to a short-term wind speed ensemble forecasting method of a wind farm, which belongs to the field of wind power forecasting. Background technique [0002] With the rapid development of the global economy and the depletion of fossil fuels, it is imminent to seek clean and renewable energy. As a clean and renewable energy, wind energy has a relatively mature technology and its cost is constantly falling. It can not only alleviate the problem of over-exploitation of energy, but also has outstanding advantages in environmental protection. In wind power generation, the intermittency of wind energy is the most fundamental reason restricting the development of wind power. Wind energy originates from the movement of the atmosphere, which has great randomness and indirectness, and the output of wind turbines is approximately proportional to the cube of the wind speed, so the output power of wind power has great volatility and randomness, ...

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Application Information

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IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20Y02A30/00
Inventor 叶小岭支兴亮李慧玲黄飞
Owner NANJING UNIV OF INFORMATION SCI & TECH
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