北华大学学报（自然科学版）2024，Vol.25Issue(5)：688-693,6.DOI:10.11713/j.issn.1009-4822.2024.05.022
基于数据重采样与GRU神经网络的风电功率多步提前预测
Multi-step Advance Forecast of Wind Power Based on Data Resampling and GRU
摘要
Abstract
Accurately predicting wind power at different times and scales is crucial for the reliable operation of energy management systems.Aiming at the problem that current prediction methods can not maintain high prediction accuracy with the increase of steps,a multi-step advance forecast of wind power method based on data resampling and GRU is proposed by combining data resampling technology with GRU neural network.A new time series of wind power is obtained by using data resampling technology to resample the original time series of wind power;Using GRU neural network to perform one-step advance prediction on the resampling time series,achieving multi-step advance prediction of the original wind power time series.Experiments were conducting by using data from a wind power plant in Australia in 2022 and 2023,and the results showed that the proposed method outperformed existing methods in predicting results,the mean absolute percentage error and root mean square error were reduced by at least 1.94%and 6.13.关键词
风电功率预测/数据重采样/GRU神经网络/多步预测Key words
wind power prediction/data resampling/GRU neural network/multi-step forecast分类
信息技术与安全科学引用本文复制引用
胡珈宁,王旭,周振雄..基于数据重采样与GRU神经网络的风电功率多步提前预测[J].北华大学学报（自然科学版）,2024,25(5):688-693,6.基金项目
吉林省科技发展计划项目(YDZJ202303CGZH001). （YDZJ202303CGZH001）
