电气技术2024，Vol.25Issue(11)：1-9,9.
基于变分模态分解和极限学习机的换流站直流极线光学电流测量装置误差预测
Error prediction of optical current measurement device for DC pole line in converter station based on variational mode decomposition and extreme learning machine
摘要
Abstract
With the rapid development of high voltage direct current(HVDC)transmission in China,optical principle based pole-to-pole DC measurement devices are widely used.Accurately predicting the trend of measurement errors is crucial for the operation and protection of HVDC transmission systems.In response to the problems of large prediction errors and low training efficiency in existing methods,a prediction method based on variational mode decomposition and extreme learning machine is proposed.The error time series of the measurement device is decomposed using variational mode decomposition,and then a particle swarm optimization algorithm is used to optimize the extreme learning machine for multi-step prediction of each mode.The predicted measurement error is obtained through reconstruction.Through comparison with multiple models,the superiority of the proposed method is verified.关键词
光学直流测量装置/误差预测/极限学习机/粒子群优化/变分模态分解Key words
optical DC measurement device/error prediction/extreme learning machine/particle swarm optimization/variational mode decomposition引用本文复制引用
罗强,黄玉磊,颜俊,自越华,徐天奇..基于变分模态分解和极限学习机的换流站直流极线光学电流测量装置误差预测[J].电气技术,2024,25(11):1-9,9.基金项目
国家自然科学基金项目(62062068) （62062068）
