Wind-speed time series forecasting method for wind power station

Abstract

The invention relates to a wind-speed time series forecasting method for a wind power station. The wind-speed time series forecasting method is characterized by comprising the following steps that: a wind-speed collecting instrument is used for data of wind speed of same area once per hour, and the collected original wind speed data is organized to form a wind-speed time series for analyzing and forecasting; a rapid independent component analysis algorithm is utilized for carrying out multiple-scale decomposition on the wind-speed time series, so as to obtain a plurality of independent components; the delay time and the embedding dimension of the independent components are calculated, and a phase-space reconfiguration theory is adopted for carrying out phase space reconfiguration on the independent components; a least squares support vector machine regression model is utilized for carrying out modeling forecasting on the independent components after phase space reconfiguration; and the forecasting results are superposed to obtain the final forecasting result of the wind-speed time series. The method is scientific, reasonable, accurate and reliable in wind-speed time series forecasting, and has strong adaptivity.

Description

technical field [0001] The invention relates to a wind speed time series prediction method of a wind farm, in particular to a short-term wind speed prediction method based on local mean value decomposition and multi-core least squares support vector machine. Background technique [0002] Energy and the environment are urgent problems to be solved for the survival and development of human beings today. Conventional energy is mainly coal, oil, and natural gas, which not only have limited resources, but also cause serious air pollution. Therefore, the utilization of renewable energy, especially the development and utilization of wind energy, has been highly valued by various countries. With the accelerated development of wind energy utilization, more and more large-scale wind farms will be included in the unified regulation of the grid, and the proportion of wind power in the grid is increasing. However, because the maximum load of the system is limited by the penetration powe...

AI Technical Summary

Problems solved by technology

Most of the above prediction methods are aimed at the original wind speed sequence, and the wind speed prediction accuracy is low, and the average relative prediction error usually reaches 20%.

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