Short-term wind power generation output power prediction method

Abstract

The invention relates to a method for predicting short-term wind power generation output power, which is technically characterized by comprising the following steps of: acquiring input data and outputdata of wind power generation, and normalizing the data; of an improved optimal foraging algorithm and a support vector machine model; running the improved optimal foraging algorithm to obtain an optimal penalty factor in the support vector machine model and an optimal parameter of a kernel function in the support vector machine model; substituting the optimized optimal parameters into a supportvector machine model, and training the support vector machine model optimized by the improved optimal foraging algorithm; and inputting the prediction data into a support vector machine model optimized by an improved optimal foraging algorithm to obtain a prediction result, and performing reverse normalization on the prediction result. According to the method, the reliable and high-precision prediction function on the short-term wind power generation output power is realized, the hidden danger existing in the operation of the wind power generation access power grid is effectively handled, andthe defect of low prediction precision of the existing short-term wind power generation output power prediction method is also overcome.

Description

technical field [0001] The invention belongs to the technical field of wind power generation, in particular to a method for predicting the output power of short-term wind power generation. Background technique [0002] In order to achieve the grand goal of sustainable energy development, the development and utilization of new energy is becoming more and more important in today's energy industry. As one of the most attractive renewable energy sources, wind energy has the characteristics of green environmental protection, no need for transportation, low cost and "inexhaustible and inexhaustible". Therefore, wind power technology is considered as one of the important solutions to meet today's energy demands. [0003] In recent decades, the wind power industry has developed rapidly around the world. A large number of wind farms have been built successively around the world, and the proportion of the number of wind farms in the power grid is also increasing. Although wind power...

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Problems solved by technology

[0007] The purpose of the present invention is to overcome the deficiencies in the prior art, propose a kind of prediction method of short-term wind power output power, it adopts combined artificial intelligence method, constructs the support vector machine model that improves optimal foraging algorithm optimization to short-term wind power output power Prediction solves the impact on grid operation when wind power is connected to the grid and the huge hidden dangers in the safe and reliable operation of the grid

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