Short-term wind power prediction method based on probability prediction model

Abstract

The invention provides a short-term wind power prediction method based on a probability prediction model, and the method comprises the steps: 1) decomposing wind power historical data into a plurality of components through variational mode decomposition, building a leakage integral type echo state network model for each dimension of component for training prediction, reconstructing each prediction result, and obtaining a wind power point prediction value; 2) modeling the residual error of the point prediction by using an echo state quantile regression network to obtain residual error prediction values under different quantile conditions; and 3) integrating the point prediction value and the residual prediction value, and further improving the prediction precision by residual prediction on the basis of point prediction to obtain a probability prediction value of the wind power. According to the method, the wind power has the characteristics of randomness and volatility, the point prediction model and the residual prediction model are combined, the probability prediction model is obtained, the wind power is accurately predicted, and the method has great significance in ensuring safe, economical and stable operation of a power system.

Description

technical field [0001] The invention relates to a short-term wind power prediction method, in particular to a short-term wind power prediction method based on a probability prediction model. The invention belongs to the technical field of wind power prediction in the new energy generation process. Background technique [0002] Since the beginning of the world energy crisis in the 1970s, many countries have paid more attention to the research, development and utilization of renewable energy. my country has also been committed to optimizing the power structure. The proportion of renewable energy power generation including water energy, wind energy and solar energy is increasing. Among them, wind energy has the advantages of huge reserves, wide distribution, and mature utilization technology. Internationally recognized as one of the renewable energy sources with the most potential for large-scale development, the development and utilization of wind energy has become an importan...

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Problems solved by technology

[0003]However, wind power has randomness and volatility, and it may bring many problems such as difficulty in regulating the large power grid when it is connected to the grid, which will not only increase the dispatching and operation costs of the system Greatly increased, it may also cause hidden harm to the system, destroying the security and stability of the system

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