AIRES2021: Artificial Intelligence in Renewable Energy Systems |
Submission link | https://easychair.org/conferences/?conf=aires2021 |
Abstract registration deadline | October 15, 2020 |
Submission deadline | February 28, 2021 |
Book: Artificial Intelligence in Renewable Energy Systems (AIRES2021)
Publisher: This book series in Scrivener Publishing is partnered with John Wiley (USA).
Editors:
- Ajay Kumar Vyas, Ph.D. Adani Institute of Infrastructure Engineering, Ahmedabad, India
- S. Balamurugan, Ph.D. Head – R& D, QUANTS IS & CS, Coimbatore, Tamil Nadu, India
- Kamal Kant Hiran, Sir Padamapat Singhania University, Udaipur, India
- Harsh Dhiman, Ph.D, Adani Institute of Infrastructure Engineering, Ahmedabad, India
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
This book presents the application of machine learning and deep learning techniques for renewable energy system modelling, forecasting, and optimization for efficient system design. The renewable energy includes solar, wind, biodiesel, hybrid energy and another relevance field. This book also provides feature extraction and selection for machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation. This book targets intelligent data, renewable energy informatics based on SCADA and intelligent condition monitoring for solar and wind energy systems. In other parts also delivered the AI-based system for real-time decision making for renewable system, energy consumption prediction in green buildings using machine learning.
The authors provide the experimental and real data set for major possibilities of the renewable energy sector by applying ML and DL algorithms which will be helpful for economic and environmental forecasting of the renewable energy business.
Tentative Topics (But not limited)
- Optimization of biodiesel energy
- Supervised Machine Learning for Wind Energy Systems
- Feature Extraction and Selection for Machine Learning Algorithms for Renewable Energy Systems
- Intelligent data analysis for energy system
- Machine learning and Deep Learning methods for solar radiation forecasting
- Energy consumption prediction in Green Buildings using Machine Learning
- Renewable energy informatics based on SCADA
- Intelligent Condition Monitoring for Solar and Wind Energy Systems
- Artificial Intelligence Methods for Hybrid Energy System
- Real-time Decision Making for Renewable System
- Deep Feature Selection for Wind Forecasting
Key Features:
- Machine intelligence for renewable energy systems.
- Intelligent condition monitoring for renewable energy systems.
- Global case studies for solar, wind and hybrid power plants.
- Deep learning-based regression, classification and clustering applications.
- Hybrid models based on machine learning and deep learning techniques.
Important Dates
Abstract Submission: 30 June 2020, 15 September 2020 (Ext.)
Full-Chapter Submission: November 15, 2020
Camera-Ready Copy Submission : December 30, 2020
Contact
All questions about submissions should be emailed to
Ajay Kumar Vyas, Email: ajay_ap7@yahoo.com, Phone No: +918758533735
S. Balamurugan Email: sbnbala@gmail.com, Phone No: +91-9952521935
Kamal Kant Hiran, Email: kamalhiran@gmail.com Phone No: + 91 8860209177
Harsh Dhiman, Email: harshdhiman@ieee.org Phone No: +91-9099660924