Method for wind speed prediction based on experience Copula function

Abstract

The invention discloses a method for wind speed prediction based on an experience Copula function. According to the method, no limits exist on marginal distribution and joint distribution, the difficulty of direct construction of a multi-element random variable joint distribution function is avoided, and the statistical situations at various wind speeds can be obtained flexibly according to the constructed experience Copula function, so that the wind speed with the maximum probability value is obtained and used as the predicted wind speed of the next moment. Due to interval division, the wind speeds within a certain range have the same characteristics, and finally wind speed sample data are divided into data sets with different characteristics. Under the conditions that the probability corresponding to the wind speed of the previous moment and different probabilities of the wind speed of the next moment are known, finally, the wind speed corresponding to the probability of the wind speed, with the maximum probability value, of the next moment is selected as the predicted wind speed, and a confidence interval with the confidence coefficient being 1-alpha can be obtained. According to the method for wind speed prediction based on the experience Copula function, it is of great significance in improving the level of power grid running, ensuring safety and stability of an electric power system, improving economy of the electric power system, and reducing greenhouse gas emission.

Description

technical field [0001] The invention belongs to the technical field of new energy, and more specifically relates to a method for wind speed prediction based on an empirical Copula function. Background technique [0002] In recent years, affected by the global energy crisis and the severe pollution brought by traditional energy sources, renewable clean energy represented by wind power has been vigorously developed. According to incomplete statistics, as of the end of December 2013, China's cumulative installed capacity of wind power reached 91.7446 million kilowatts, ranking first in the world. However, wind power output is affected by natural factors and has the characteristics of large randomness and strong volatility. Although scholars have done a lot of related research work on wind power prediction, it is still difficult to obtain accurate prediction results. Certainty will remain for a long time. Generally speaking, the shorter the forecast period, the more moderate t...

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Problems solved by technology

[0004] Aiming at the defects of the prior art, the purpose of the present invention is to provide a method for wind speed prediction based on the empirical Copula function, aiming to solve the technical problems of low wind speed prediction accuracy and difficult determination of the confidence interval in the prior art

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