Research On Scale Wind Power Forecasting And Grid-connected Capacity Optimization Method

The output of wind power is random,fluctuating,and intermittent.Its large-scale grid connection is likely to cause grid power flow disorder and seriously affect grid capacity planning.The prediction of wind power and the optimization of grid-connected capacity based on power prediction can predict and analyze future wind power,grid power flow and grid capacity planning in advance,laying an important foundation for the advance planning and control of grid dispatching,thus effectively promoting wind power Development and safe and stable operation of the power grid.First,for the low accuracy of a single wind power prediction method,a wind power combination prediction method based on PSR-Elman-GWO is proposed.This method uses the Elman neural network for predictive modeling,and uses the gray wolf optimization algorithm to quickly optimize its parameters for rolling initialization,which reduces the model errors caused by fixed parameters.On this basis,the data reconstruction method of phase space reconstruction is used to multi-dimensionally expand the input data of the prediction model,which increases the feature input of the data and reduces the input error of the data.The simulation results verify that the proposed method can simultaneously reduce the data error and the model error,and effectively improve the prediction accuracy of the gentle section of wind speed.Secondly,in view of the low prediction accuracy of the above method in the climbing section,a wind power climbing section prediction method based on VMD-Elman-IGWO is proposed.This method uses the extreme value extraction algorithm to search the extreme points of the sequence.Through the redefinition of the climbing section,it achieves the effects of climbing section identification and wind power sequence segmentation;The segment prediction model uses the VMD algorithm to decompose the input of the climbing section and reduce the information complexity of the input of the model.Then improve GWO and use IGWO with faster convergence speed.The simulation results verify thatthe proposed method can greatly improve the prediction accuracy of the wind power climbing section,and provide a reliable data guarantee for the calculation of grid-connected capacity with wind power.Finally,a wind power grid-connected capacity optimization method based on power prediction is proposed.This method first analyzes the wind power stability grid-connected constraints;then based on the wind power forecast data,establishes the objective function of the maximum planned grid-connected capacity of the wind power under the 10 KV ?35KV grid;and finally solves the objective function.The analysis results of the calculation examples show that the safe and stable operation margin of the power grid can be met,and the maximum operation rate of the wind farm and the maximum absorption rate of the wind power can be achieved.