Wind speed interval prediction method and system based on Lorenz system

Abstract

The invention discloses a wind speed interval prediction method and system based on a Lorenz system. The prediction method comprises: obtaining an original wind speed sequence; carrying out variational mode decomposition (VMD) on the wind speed sequence, and obtaining a denoising sequence and a noise remainder; establishing a long-short-term neural network prediction model (LSTM), and carrying outpreliminary prediction on the denoised sequence to obtain a preliminary prediction result; correcting the preliminary prediction result by defining a wind speed climbing event (WSR) and a wind speedclimbing rate to obtain a corrected wind speed prediction result; describing the influence of the atmospheric power system on the wind speed through a Lorenz equation, and obtaining a Lorenz disturbance sequence (LDS); fitting the LDS through a B spline interpolation method, fixing a confidence interval for a fitting result, and obtaining an upper limit and a lower limit of a wind speed disturbance interval; and summing the corrected wind speed prediction result and the wind speed disturbance interval to obtain an interval prediction result of the wind speed. According to the wind speed interval prediction method or system, the precision and reliability of the prediction model are remarkably improved, and a high-precision prediction result can be obtained.

Description

technical field [0001] The invention relates to the field of wind speed prediction, in particular to a method and system for wind speed interval prediction based on the Lorenz system. Background technique [0002] In recent years, the global energy situation has become increasingly severe, and energy demand has continued to increase. As a clean and renewable energy source, wind energy has attracted much attention in new energy applications around the world, and wind power grid-connected technology has become an international research hotspot. The International Energy Agency (IEA) reported that wind power generation is expected to increase by 325 gigawatts in 2019. However, wind fluctuations often lead to instability of the power system after wind power integration. Therefore, effective wind speed prediction can promote the intelligent development of the wind power industry, and accurate wind speed prediction is an important prerequisite for the large-scale development and ...

AI Technical Summary

Problems solved by technology

However, wind fluctuations often lead to instability of the power system after wind power integration

Images