Developing a Deep Learning and Reliable Optimization Techniques for Solar Photovoltaic Power Prediction-Reference-Cited by-同舟云学术

Developing a Deep Learning and Reliable Optimization Techniques for Solar Photovoltaic Power Prediction

Published:2024-02-29 Issue: Volume: Page:1-15
ISSN:1532-5008
Container-title:Electric Power Components and Systems
language:en
Short-container-title:Electric Power Components and Systems

Author:

Shivashankaraiah Kumaraswamy¹,Shashibhushan Gadigi²,Prema Kirubakaran Arumugam³,Anjanappa Chowdappa⁴,Sharma Pradosh Kumar⁵,Mayiladuthurai Vaidyanathan Ishwarya⁶,Taqui Syed Noeman⁷,Obaid Sami Al⁸,Alfarraj Saleh⁹

Affiliation:

1. Department of Computer Science and Engineering, UVCE (University Visvesvaraya College of Engineering), Bangalore, Karnataka, India

2. Department of Electronics and Communication Engineering, Sir M Visvesvaraya Institute of Technology, Bengaluru, Karnataka, India

3. Department of Information Technology and Information Systems, Nile University of Nigeria, Abuja, FCT, Nigeria, India

4. Department of Electronics and Communication Engineering, The National Institute of Engineering, Mysore, Karnataka, India

5. Department of Physics, Chinmaya Degree College BHEL Haridwar, Uttrakhand, India

6. Artificial Intelligence and Data Science Department, Agni College of Technology, Chennai, Tamil Nadu, India

7. Department of VLSI Microelectronics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India

8. Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia

9. Zoology Department, College of Science, King Saud University, Riyadh, Saudi Arabia

Funder

King Saud University

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15325008.2024.2317369

Reference29 articles.

1. Solar Power Forecasting Using Deep Learning Techniques

2. Solar Panel Tilt Angle Optimization Using Machine Learning Model: A Case Study of Daegu City, South Korea

3. Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review

4. AB-Net: A Novel Deep Learning Assisted Framework for Renewable Energy Generation Forecasting

5. Forecasting Solar Power Output Generation: A Systematic Review with the Proknow-C

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