An ultra-short-term wind speed dynamic prediction method based on cascaded wind turbines

A wind speed and fan technology, applied in the field of ultra-short-term wind speed dynamic prediction based on cascaded fans, can solve problems such as insufficient wind energy absorption

Inactive Publication Date: 2015-10-28
SHANGHAI UNIVERSITY OF ELECTRIC POWER
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Problems solved by technology

From the wind energy formula (1), it can be seen that the change of wind speed is in a cubic relationship with the change of wind energy. Therefore, during the lag time, the absorption of wind energy is not sufficient.

Method used

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  • An ultra-short-term wind speed dynamic prediction method based on cascaded wind turbines
  • An ultra-short-term wind speed dynamic prediction method based on cascaded wind turbines
  • An ultra-short-term wind speed dynamic prediction method based on cascaded wind turbines

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Embodiment Construction

[0020] When the wind speed is greater than the cut-out wind speed, the fan will stop, and the cut-out wind speed is generally around 25m / s. For an actual wind farm, the distance between two wind turbines is usually several hundred meters, and among several power plants actually investigated, the minimum distance is 500m. There is a certain time difference in the transmission of wind energy from one wind turbine to another, and in this time period, the signal processing equipment can fully process the data as a feed-forward signal and transmit it to the next wind turbine as the Reference data for fans after time period. Since the fan needs to absorb wind energy, the friction of the ground will also cause certain obstacles to the propagation of wind speed. Therefore, in the process of propagation, the attenuation of wind energy must be considered.

[0021] figure 1 It is a schematic diagram of a wind farm model with two wind turbines, which are respectively recorded as No.1 a...

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Abstract

The invention relates to an ultrashort-term dynamic wind speed prediction method based on cascading fans. The method comprises the steps of establishing a wind farm with the cascading fans, measuring the distance between two adjacent fans, acquiring instantaneous wind speeds and instantaneous wind direction angles of the front and rear fans, calculating the spread time from the front fans to the rear fans, establishing a prediction system according to a wind speed attenuation rate formula and a wind direction attenuation rate formula, and obtaining wind speed and wind direction attenuation rates. The wind speed and wind direction of the rear fans are converted through the established wind speed and wind direction attenuation rate data system, a cascading fan system is established by fully using the energy transfer relation between the fans, and the ultrashort-term dynamic wind speed prediction is achieved. The method provides technical base for universal application of wind energy.

Description

technical field [0001] The invention relates to a wind speed prediction technology, in particular to an ultra-short-term wind speed dynamic prediction method based on cascaded fans. Background technique [0002] With the emergence of the global energy crisis, all countries in the world have aroused strong interest in renewable resources. Wind energy has been widely used due to its advantages of cleanness, low cost, and great development potential, and its proportion is also increasing rapidly year by year. However, wind power also has disadvantages. The uncertainty of wind makes the prediction of wind speed and wind power more complicated, with large prediction error and low accuracy. At present, most of the studies at home and abroad focus on the short-term forecasting of wind speed, and there are few studies on ultra-short-term forecasting or even dynamic forecasting. [0003] The ultra-short-term forecast of wind speed usually refers to the forecast within 30 minutes. A...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00F03D7/00
CPCY02E10/723Y02A30/00Y02E10/72Y02P70/50
Inventor 徐耀良杨亚兰钟绍山蒋晓波王博
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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