Digital Twinning and LSTM-based Forecasting Model of Solar PV Power Output-Reference-Cited by-同舟云学术

Digital Twinning and LSTM-based Forecasting Model of Solar PV Power Output

Published:2023-02-20 Issue: Volume: Page:
ISSN:
Container-title:2023 Advances in Science and Engineering Technology International Conferences (ASET)
language:
Short-container-title:

Author:

Al-Isawi Omar Adil¹,Amirah Lutfi Hatem²,Al-Mufti Omar Ahmed³,Ghenai Chaouki²

Affiliation:

1. Khalifa University,Electrical and Computer Engineering Department,Abu Dhabi,United Arab Emirates

2. University of Sharjah,Sustainable and Renewable Energy Engineering Department,Sharjah,United Arab Emirates

3. Khalifa University,Mechanical Engineering Department,Abu Dhabi,United Arab Emirates

Funder

University of Sharjah

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10180403/10180404/10180431.pdf?arnumber=10180431

Reference14 articles.

1. Short-term building electrical load forecasting using adaptive neuro-fuzzy inference system (ANFIS)

2. Artificial Neural Network PV Performance Prediction and Electric Power System Simulation of a Ship-tracking CubeSat

3. Digital Twinning and ANN-based Forecasting Model for Building Energy Consumption;al-mufti;2023 International Conference on Renewable and Sustainable Energy - 2023 Advances in Science and Engineering Technology (ASET) International Conferences (RSE-2023 ASET),2023

4. Artificial neural networks for power output forecasting from bifacial solar PV system with enhanced building roof surface Albedo

5. Estimating PV models using multi-group salp swarm algorithm

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Review on Digital Twins and Its Application in the Modeling of Photovoltaic Installations;Energies;2024-03-04