基于AO-ESN的海上风电机组接地电阻预测

张萍; 杨晓磊; 张国峰; 陈程; 尹军杰; 李练兵

doi:10.19912/j.0254-0096.tynxb.2022-1107

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (5) : 480-486. DOI: 10.19912/j.0254-0096.tynxb.2022-1107

基于AO-ESN的海上风电机组接地电阻预测

张萍¹, 杨晓磊², 张国峰³, 陈程³, 尹军杰³, 李练兵¹

作者信息 +

PREDICTION OF IMPACT RESISTANCE OF OFFSHORE WIND TURBINE BASED ON AO-ESN

Zhang Ping¹, Yang Xiaolei², Zhang Guofeng³, Chen Cheng³, Yin Junjie³, Li Lianbing¹

Author information +

文章历史 +

摘要

针对目前2种主流求解海上风电机组接地电阻值精度不足的问题,该文提出基于天鹰算法改进的回声状态网络（AO-ESN）,对海上风电机组接地电阻进行预测分析。分别利用BP、ESN、AO-ESN这3种网络进行预测,结果表明：AO-ESN模型的预测精度相较于BP和ESN模型分别提高了18%和14.46%,误差低至0.54%,所搭建的模型可对海上风电机组接地电阻进行精准预测。

Abstract

In response to the current two mainstream solution of offshore wind turbine with insufficient accuracy of ground resistance methods, in this paper, the improved Echo state network （AO-ESN） based on the Aquila optimizer is proposed to predict and analyze the grounding resistance of offshore wind turbines. The three networks of BP, ESN and AO-ESN are used to make predictions. The results show that the prediction accuracy of the AO-ESN prediction model is 18% and 14.46% higher than the BP and ESN models, and the error is as low as 0.54%. The model built in this paper can be accurately predict the grounding resistance of offshore wind turbines, and provide reference for transient analysis and lightning protection of offshore wind turbines

导出引用

张萍, 杨晓磊, 张国峰, 陈程, 尹军杰, 李练兵. 基于AO-ESN的海上风电机组接地电阻预测[J]. 太阳能学报. 2023, 44(5): 480-486 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1107

Zhang Ping, Yang Xiaolei, Zhang Guofeng, Chen Cheng, Yin Junjie, Li Lianbing. PREDICTION OF IMPACT RESISTANCE OF OFFSHORE WIND TURBINE BASED ON AO-ESN[J]. Acta Energiae Solaris Sinica. 2023, 44(5): 480-486 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1107

中图分类号： TU856

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