Short-period wind power non-parametric probability predication method

Abstract

The embodiment of the invention discloses a short-period wind power nonparametric probability predication method which comprises: constructing an SVM (Support Vector Machine) predication model and an SBC (Sparse Bayesian Classification) predication model of each prospective time period; inputting data needed for wind power predication into the SVM predication model, so as to obtain a wind power predicated value of each prospective time period; inputting data needed for error distribution predication into the SBC predication model, so as to obtain a predication error conditional probability of each prospective time period; integrating the predication error conditional probabilities by use of the D-S evidence theory, designing distribution range constraints of wind power, so as to obtain predication error overall probability distribution of each prospective time period; and superposing the wind power predicated value and the predication error probability distribution, so as to obtain wind power probability distribution of each prospective time period. The short-period wind power non-parametric probability predication method is constructed on the basis of a sparse Bayesian framework, has high sparsity, ensures the generalization ability and calculation speeds of the models, and systematically designs boundary constraints of output power of a wind power field, so that the predication result is better in conformity with reality.

Description

technical field [0001] The invention relates to the technical field of wind power prediction in the process of new energy power generation, in particular to a short-term non-parametric probability prediction method of wind power. Background technique [0002] Wind energy is a renewable and clean energy. The development of wind energy has been highly valued by various countries. Wind power has become one of the fastest growing and most mature technologies in renewable energy. However, the volatility and uncontrollability of wind energy And other characteristics, resulting in the fluctuation and intermittency of the output power of the wind farm. In turn, the access of wind power has brought impacts to the power grid, increasing the uncertainty of the power grid and increasing the difficulty of power dispatching. Therefore, accurate forecasting of wind power is conducive to reducing the impact of wind farms on the grid, reducing adverse effects, and improving the ability of w...

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Problems solved by technology

[0005] The embodiment of the present invention provides a short-term wind power non-parametric probability prediction method to solve the problem of large differences between the prediction results of the wind power probability prediction method in the prior art and the actual situation

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