太阳能学报2024,Vol.45Issue(3) :65-72.DOI:10.19912/j.0254-0096.tynxb.2022-1790

海上风力机前端风电场瞬态重构研究

TRANSIENT RECONSTRUCTION OF WIND FARM AHEAD OF OFFSHORE WIND TURBINES

姜贞强 王滨
太阳能学报2024,Vol.45Issue(3) :65-72.DOI:10.19912/j.0254-0096.tynxb.2022-1790

海上风力机前端风电场瞬态重构研究

TRANSIENT RECONSTRUCTION OF WIND FARM AHEAD OF OFFSHORE WIND TURBINES

姜贞强 1王滨2
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作者信息

  • 1. 中国海洋大学工程学院,青岛 266100
  • 2. 浙江省深远海风电技术研究重点实验室,杭州 311122;中国电建集团华东勘测设计研究院有限公司,杭州 311122
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摘要

针对海上风电单机位风速测点有限的关键问题,提出一种基于少数风速测点的海上风力机前端风电场瞬态扩展方法.基于本征正交分解(POD)将先验风电场数据分解为时间系数与空间模态特征信息,通过循环神经网络(RNN)建立有限风速测点到全局风电场的非线性映射关系,实时构建海上瞬态风电场.结果表明基于POD-RNN的重构模型可通过有限风速测点准确重构海上风力机前端风电场,全局风电场瞬态重构均方根误差(RMSE)可控制在1.8136 m/s内.

Abstract

To address the key problem of insufficient measurement locations of wind speed for the individual offshore wind power structure,a transient expansion method of the wind farm ahead of offshore wind turbines based on limited measurement data for wind speed is proposed.The prior farm data is decomposed into feature information for both the temporal coefficients and the spatial modes based on proper orthogonal decomposition(POD).A nonlinear mapping relationship from insufficient measurement locations of wind speed to the global wind farm is established by recurrent neural networks(RNN)to construct the offshore transient wind farm in real time.The results show that the proposed POD-RNN method can accurately reconstruct the wind farm ahead of the offshore wind turbine using limited measurement data for wind speed,where the root mean square error(RMSE)of the transient reconstruction of wind farm is within 1.8136 m/s.

关键词

海上风力机/风电场/循环神经网络/本征正交分解/瞬态重构

Key words

offshore wind turbines/wind farm/recurrent neural networks/proper orthogonal decomposition/transient reconstruction

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基金项目

国家自然科学基金(52071301)

国家自然科学基金(51939002)

出版年

2024
太阳能学报
中国可再生能源学会

太阳能学报

CSTPCDCSCD北大核心
影响因子:0.392
ISSN:0254-0096
参考文献量18
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