Rotational Speed Control Using ANN-Based MPPT for OWC Based on Surface Elevation Measurements
Rotational Speed Control Using ANN-Based MPPT for OWC Based on Surface Elevation Measurements
复制标题
DOI：
10.3390/app10248975
复制
发表时间：
2020-12
期刊：
影响因子：
--
通讯作者：
Fares M’zoughi;I. Garrido;A. Garrido;M. de La Sen
中科院分区：
文献类型：
--
作者：
Fares M’zoughi;I. Garrido;A. Garrido;M. de La Sen
本文提出了一种基于人工神经网络的转速控制，以避免失速行为的振荡水柱由双馈感应发电机驱动的威尔斯涡轮机。该控制策略使用基于人工神经网络的最大功率点跟踪提供的转速参考。基于人工神经网络的MPPT预测的最佳转速参考波的振幅和周期。神经网络已被训练，并使用声学多普勒海流剖面仪收集的波面高程测量。在两种不同的波浪条件下对所实现的基于人工神经网络的转速控制进行了测试，结果证明了避免失速效应的有效性，从而提高了发电量。
This paper presents an ANN-based rotational speed control to avoid the stalling behavior in Oscillating Water Columns composed of a Doubly Fed Induction Generator driven by a Wells turbine. This control strategy uses rotational speed reference provided by an ANN-based Maximum Power Point Tracking. The ANN-based MPPT predicts the optimal rotational speed reference from wave amplitude and period. The neural network has been trained and uses wave surface elevation measurements gathered by an acoustic Doppler current profiler. The implemented ANN-based rotational speed control has been tested with two different wave conditions and results prove the effectiveness of avoiding the stall effect which improved the power generation.