ISSA-BP wind power prediction by interval based on dynamic division of wind speed fluctuation range
In order to solve the problem of low accuracy of traditional wind power prediction,a wind power combination prediction method based on dynamic interval division of wind speed fluctuation amplitude was proposed.Firstly,Kalman filtering was applied to the cleaned wind speed data to obtain the noise-reduced wind speed curve,The difference vector of adjacent elements in the curve was calculated and normalized to complete the visual analysis of the wind speed fluctuations.Secondly,the improvement sparrow search algorithm(ISSA)was obtained by initializing the sparrow population location using the Tent chaotic mapping algorithm,and the connection weights and thresholds of back propagation(BP)algorithm were optimized.The ISSA-BP wind power combination forecasting model was established.Finally,MATLAB simulation software was used for simulation verification.The simulation results show that the proposed dynamic interval division ISSA-BP wind power prediction method significantly improves the prediction accuracy,and has certain theoretical and practical significance for improving the economic operation level of power system and promoting the consumption of wind power.
improved sparrow search algorithmback propagationKalman filteringwind power forecast
NETL
NSTL
万方数据
