相关实验视频

Updated: Jan 11, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

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优化太阳能发电预测,利用光伏电网连接系统的元启发算法和深度学习模型来优化太阳能发电预测

Putri Nor Liyana Mohamad Radzi1, Saad Mekhilef2,3, Noraisyah Mohamed Shah4

  • 1Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, 50603, Kuala Lumpur, Malaysia. 17013615@siswa.um.edu.my.

Scientific reports
|November 14, 2025
PubMed
概括

准确的太阳能预报对于电网稳定性至关重要. 一个新的火优化-门式循环单元-长期短期存储器 (FHO-GRU-LSTM) 模型显著提高了光伏系统的预测准确性.

关键词:
深度学习是一种深度学习.预测 预测 预测 预测超启发式算法 超启发式算法神经网络的神经网络的神经网络优化优化 优化优化太阳能光伏系统的使用

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