Elsevier-SDAIMLRE-2021: Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies |
Website | https://easychair.org/cfp/Elsevier-SDAIMLRE-2021 |
Submission link | https://easychair.org/conferences/?conf=elseviersdaimlre2021 |
Abstract registration deadline | March 15, 2021 |
Submission deadline | April 30, 2021 |
Elsevier - Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
About the Book
Energy is the basic need for the development of a human’s life. Renewable energy is a sustainable source of energy. Presently around 17 % of the energy requirement in the world is fulfilled by renewable energy. Hydropower, solar energy, and wind energy are the primary sources of renewable energy generation. Development in capacity building for renewable energy generation has sparked a paradigm change in the energy sector. Because of changes in sources of energy generation shift, issues of grid stability occurred, as the traditional baseload energy generation is less variable because of weather than renewable energy resources. Also, in changing, the energy demand market speeds up to focus on innovative technologies to integrate renewable energies. The various complex nonlinear interactions among different parameters drive the integration of renewable energy into the grid. Artificial Intelligence and Machine learning techniques are being developed to produce more reliable energy generation and to optimize system performance. Using artificial intelligence to revolutionise the energy market and harness the potential of renewable energy is essential. We aim to provide a practical introduction to the application of renewable energy, AI, and machine learning to design, model, characterise, optimize, forecast, and performance prediction of renewable energy systems. It will address the solutions to current critical environmental, economic, and social issues.
Key features
- The main key features of this book are to provide a book that covers all the latest developments and future aspects of Renewable Energy. Many aspects, such as concisely written, lucid, and comprehensive, practical application-based, graphical, schematics, and cover all areas of renewable energy, will make it distinctive.
- In this proposed book, the knowledge and insights provided will help students, researchers, as well as systems designers, to understand the fundamental technical requirements of Renewable Energy and for industrial applications have to meet.
- This book will be very beneficial for new researchers and practitioners working in the field to know the best-performing methods of Renewable Energy quickly. They would be able to compare different approaches and can carry forward their research in the most crucial area of research which has a direct impact on the betterment of human life and to understand how the design of renewable energy and AI helps in providing a real-time environment.
- This proposed book gives an advanced technique, monitoring the existing technologies, and efficiently utilizing the spectrum.
- This proposed book contains the topics which are the latest advances in the field of renewable energy, addressing original research, impact and idea development, and new applications of renewable energy in a single platform.
This book will target the Researchers, Academicians, Industry, and Peoples from Technical Institutes, R & D Organizations, and students, a Data scientist working in Renewable Energy, AI, Machine Learning, Micro-grid, Grid Stability, Water Resource, and Energy Trading. This book covers the maximum branches of engineering as well as science discipline and related disciplines such as Electronics and Communication Engineering, Computer Science & Engineering, Electrical Engineering, Telecommunications, Electrical and Electronics Engineering, Artificial Intelligence, Information Technology, Computer Applications and many more. The target audience may include:
- Researchers and scholars who are pursuing research in renewable energy and AI.
- Graduate and postgraduate students are pursuing renewable energy as a course.
- Hardware engineers, R & D organisations, and industry people who are interested in offering services with renewable energy, and AI.
Submission Guidelines and Important Dates:
Authors are invited to submit the full chapter in A4 format with single-line spacing with high-quality images of diagrams, figures and numerical/experimental results with minimum 300 DPI resolution.
Full Chapter Submission - 15/04/2021
First Decision - 15/05/2021
Revised Chapter Submission - 15/06/2021
Final Decision - 30/06/2021
Submission link | https://easychair.org/conferences/?conf=elseviersdaimlre2021 |
List of Topics (Table of Contents) - Authors chapter invited not limited too:
- Introduction of Artificial Intelligent and Machine Learning.
- Energy systems and the present status of renewable energy systems.
- Role of Artificial Intelligent in renewable energy.
- Energy market, demand analysis, and forecasting.
- E-Mobility- a growing energy trade market case study.
- Renewable energy generation forecasting, and operation & maintenance optimization.
- Primary & secondary parameters forecasting, and operation & maintenance optimization of hydropower plants.
- Hydrogen energy generation optimization.
- Optimization of Hybrid energy generation.
- Introduction –Blockchain and Smart Grid.
- Transformation of Smart Grid to IoE.
- Building Blockchain-based IoE Infrastructure.
- Energy storage technologies and their parameter optimization.
- Machine learning-based hybrid demand-side controller for renewable energy management.
- Machine learning-based robust and reliable design on PCMs-PV systems with multilevel scenario uncertainty.
- Agent-based peer-to-peer energy trading with cost-benefit business models.
- IoT and SCADA system for monitoring and control of plants.
- Application of Big Data, Cloud Computing, and Blockchain for renewable energy optimization.
- Policies and case studies for renewable energy development.
Editors
- Er Krishna Kumar, Research and Development Unit, UJVN Ltd., Uttarakhand, India. (Email: kkumar@ah.iitr.ac.in, Mob. No.+91-9557074596) https://scholar.google.co.in/citations?user=PV5af9AAAAAJ&hl=en
- Dr. Ram Shringar Rao, Ambedkar Institute of Advanced Communication Technologies and Research, Delhi, India. (Email: rsrao@aiactr.ac.in, Mob. No.+91-9968408090) https://scholar.google.com/citations?user=5K3ioE8AAAAJ&hl=en
- Dr. Omprakash Kaiwartya, Nottingham Trent University (NTU), UK (Email: omprakash.kaiwartya@ntu.ac.uk, Mob. No. +44 (0)115 848 3567) https://scholar.google.co.in/citations?user=kSxzIsIAAAAJ&hl=en
- Dr. M. Shamim Kaiser, Institute of Information Technology, Jahangirnagar University, Bangladesh. (Email: mskaiser@juniv.edu, Mob. No. +880- 01711932323) https://scholar.google.com/citations?user=yjrSXiEAAAAJ&hl=en
- Dr. Sanjeevikumar Padmanaban, Department of Energy Technology,Aalborg University, Esbjerg, Denmark. (Email: san@et.aau.dk, Mob. No. +45-91406361) https://scholar.google.co.in/citations?user=KyuMg7IAAAAJ&hl=en
Publication
Elsevier-SDAIMLRE-2021 chapters will be published as Edited Book by Elsevier Publication, 50 Hampshire St., 5th Floor, Cambridge, MA 02139, USA
Contact
All questions about submissions should be emailed to Er Krishna Kumar, Email: kkumar@ah.iitr.ac.in, P. Sanjeevikumar, san@et.aau.dk