Wind power plant annual average wind speed prediction method and system based on cycle stacking extrapolation

A technology of average wind speed and forecasting method, which is used in forecasting, electrical digital data processing, special data processing applications, etc., and can solve the problems of not considering the impact of dynamic wind speed on project economic benefits.

Active Publication Date: 2018-04-06
GUODIAN UNITED POWER TECH
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AI Technical Summary

Benefits of technology

This patented technology allows us to predict how fast an offshore wind turbine operates compared with other types of generators by analyzing its cycles over time. By doing this we aimed at providing better understanding about future weather patterns that affect it.

Problems solved by technology

This patents discusses how wind turbines work differently from other sources due to their irregularly changing output levels over time or varying weather conditions that affects its performance. It suggests developing methods to accurately estimate this variation through measurements at different times along the entire lifecycle of each machine's component parts. These estimates help identify areas where there may be potential future shortages of use compared to previous periods when they were expected beforehand. Additionally, these techniques could also aid in optimizing operational planning and managing costs associated with wind generations.

Method used

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  • Wind power plant annual average wind speed prediction method and system based on cycle stacking extrapolation
  • Wind power plant annual average wind speed prediction method and system based on cycle stacking extrapolation
  • Wind power plant annual average wind speed prediction method and system based on cycle stacking extrapolation

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Embodiment Construction

[0039] The investment decision-making and operation management of existing wind farms are based on the power generation calculated in a fixed wind measurement year, without considering the impact of dynamic wind speed on the economic benefits of the project. The present invention provides a method for predicting the annual average wind speed of wind farms based on periodic superposition and extrapolation And the system can predict the annual average wind speed of the wind farm during the operation period in the next few decades, and can provide more scientific and effective information for the investment decision-making and operation management of the wind farm.

[0040] Please combine figure 1 As shown, the wind farm annual average wind speed prediction method based on periodic superposition and extrapolation of the present invention is mainly realized through the following steps:

[0041] Step 1: Extract data; extract the local long-term meteorological model data and the win...

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Abstract

The invention discloses a wind power plant annual average wind speed prediction method based on cycle stacking extrapolation. The method mainly comprises the steps of data extraction, climate correction, linear trend analysis, linear trend influence removal, wind speed main cycle extraction, cycle stacking extrapolation, cycle component and trend component combination and the like. According to the method, wavelet transformation calculation is performed on average wind speeds over the years of a wind power plant mainly through wavelet analysis, main cycles are extracted, then the main cycles are utilized for stacking extrapolation, and therefore a result with good correlativity and a low average deviation value is obtained. The invention furthermore discloses a wind power plant annual average wind speed prediction system based on cycle stacking extrapolation. The prediction method and system are more scientific and accurate, and the prediction result can provide a more scientific and effective basis for investment decision making and operation management of the wind power plant.

Description

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Claims

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Application Information

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Owner GUODIAN UNITED POWER TECH
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