IARES2022: IoT and Analytics in Renewable Energy Systems Chennai, India, September 15-18, 2022 |
Submission link | https://easychair.org/conferences/?conf=iares2022 |
IoT and Analytics in Renewable Energy Systems (IARES2022)
Scope of the Call – Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
This book contributes in applying the concepts of IoT and Analytics in renewable energy systems which in turn solves real life problems. The book focusses on futuristic intelligent paradigms such as modeling, smart objects integration, advanced optimization computing which would provide the optimal renewable energy. IoT and Analytics is significantly important in modeling, analysis, and prediction of the performance and control of renewable energy systems. The algorithms involve complex problem solving, demands exorbitant computational power and consume lot of time. In order to ease the system from its complex mathematical modeling, IoT aided Analytics are deployed in renewable energy systems for handling multidimensional information domain. Design, control, and operation of renewable energy systems require huge quantum of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements demand the application of analytics to facilitate easy computation. This book presents the application of analytics like machine learning and deep learning techniques for modeling, forecasting, and optimization for efficient system design of renewable energy system. The pivotal role of feature extraction and selection for machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are analyzed. 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 analytics 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 Machine Learning and Deep Learning algorithms which will be helpful for economic and environmental forecasting of the renewable energy business. The domains of smart grid applications & technologies are crucial for engineering dynamics. The curtailment of intelligent energy, distributed renewable generation, intelligent fulfilment of demand responses and energy storages are some common parameters shared in most of the IoT based smart grid applications. The book summarizes about extensive applications of IoT and analytics which paves way for realizing sustainable, low cost, smart and efficient solutions for renewable energy systems.
Important Deadlines
Abstract Submission (approx. 500 words, single column, A4 size, single-line spacing): before 1st June 2022
Acceptance Notification: before 15th June 2022
Full-Article Submission: 1st July 2022
Full length chapter decision: 1st August 2022
Camera-Ready Submission: 15th August 2022
Topics
IoT in Renewable Energy Systems
- IoT towards leveraging renewable energy
- IoT contribution in construct of green energy
- IoT, Smart Grids and Bigdata – renewable energy insights
- IoT infrastructure to energize Electromobility
- Building Sustainable charging infrastructure – smart solutions
- Empowering Renewable Energy using Internet of Things
- IoT for Transactive Energy
- IoT and SCADA system for monitoring and control of plants.
- Ensemble learning technique for Green IoT
- IoT,Smart Grids & Renewable Energy: An Economic Approach
- Innovations in Smart Traffic Management System Using IoT and Big Data.
- Big Data Algorithms and Applications for IoT systems.
- Intelligent decision making systems using IoT and Big Data Analytics.
- Security and Privacy challenges and solutions in IoT Data Analytics.
- Novel Designs of IoT systems such as Smart Healthcare, Smart Transportation, Smart Home, Smart Agriculture, Smart Manufacturing, Smart Grid, Smart Education, Smart Government etc. based on Big Data Analytics.
- Case Studies
Analytics in Renewable Energy Systems
- 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
- Deep Feature Selection for Wind Forecasting
- AI and ML towards Sustainable solar energy
- AI and intermittency management of renewable energy
- AI impact on Energy and utilities
- AI and IoT in improving resilience of Smart Energy infrastructure
- 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.
- Green IoT and Machine Learning a combinatory approach and synthesis
- ML enabling techniques for reducing energy consumption of IoT devices
- Incremental learning for real time data
- Taxonomy and energy optimization techniques in IoT
- Deep Learning and Green IoT
- IoT-BDA Architecture for smart cities.
Applications in Renewable Energy Systems
- Optimization of biodiesel energy
- Hydrogen energy generation optimization.
- Optimization of Hybrid energy generation.
- 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
- Energy intelligence – The Smart Grid perspective
- Biomass Renewable energy: Introduction and application of AI and IoT
- Modernization of Rural Electric infrastructure
- Role of Artificial Intelligence in renewable energy
- IoT and sustainable energy system: Risk and opportunity
- Powering the Geothermal energy with AI, IOT, and ML
- Agent-based peer-to-peer energy trading with cost-benefit business models.
- Application of Big Data, Cloud Computing, and Blockchain for renewable energy optimization.
- Application of AI to Power Electronics and drives systems
- Case Studies
Sustainable Renewable Energy Systems
- Soft Computing Techniques in Energy System
- Grids of microgrids
- Building-to-Grid Convergence
- Intelligent Computing for Smart Grid Applications
- Transportation Electrification
- Smart Grid Monitoring and Control
- Integrated and distributed control
- Impact of Extreme weather on power grid
- Electrical Vehicles & Smart Grid
- Smart Grid to the Smart Customer
- Green Energy and Grid Modernization Solutions
- Hybrid Renewable Energy System
- Energy market, demand analysis, and forecasting.
- Renewable energy generation forecasting, and operation & maintenance optimization.
- Primary & secondary parameters forecasting, and operation & maintenance optimization of hydropower plants.
- Energy storage technologies and their parameter optimization.
- Policies and case studies for renewable energy development.
- Energy-Efficient solutions for Emergency vehicles management system.
- Intelligent framework for smart traffic management system : case study
- Energy-Efficient solutions for Smart Environment : case study
- Energy-Efficient solutions for Smart healthcare systems : case study
- Challenges and Future Research Directions of Smart City Applications.
- Case Studies
Editors
Dr. O.V. Gnana SwathikaAssociate Professor,
School of Electrical Engineering
VIT Chennai, Chennai, India
Email: gnanaswathika.ov@vit.ac.in
Mr.K.Karthikeyan
Chief Engineering Manager,
Larsen & Toubro Pvt. Ltd., Chennai, India
Email: kskk@lntecc.com
Dr. Sanjeevikumar Padmanaban
Assistant Professor
CTiF Global Capsule,
Department of Business Development & Technology,
Aarhus University, Denmark
Email: sanjeevi_12@yahoo.co.in
Publishers
IARES2022 proceedings will be published by CRC Press, Taylor & Francis Group.
NO PUBLICATION FEES.
Contact
All questions about submissions should be emailed to the editors.