Special Session 7

With rapid degeneration of conventional sources of energy, it is time to prepare our existing system to adapt to renewable power generation; a task full of challenges till today. Smart grid, an advanced version of a present power system grid is expected to meet the challenges of future power demand by using advanced techniques. Along with the increase of the importance of renewable electricity generation especially, intelligent systems are needed in the electricity market using real-time pricing. Smart grid structure will offer opportunities to progress within a layout by providing many facilities and work to be done in the operation of the distribution network that is not limited to energy supply and demand balance, but to ensure providing the quality criteria of energy and energy measurement. One of the chief challenges for Smart Grid application scenarios will be handling the massive amount of data that is expected to be collected from various sources and treated to optimize its operation. In this respect, different machine learning techniques such as deep neural networks, decision trees, evolutionary programming, fuzzy systems, and other artificial intelligence methods and their hybrid combinations can significantly contribute to solve problems in smart grid.

This special session will bring together researchers and developers from academia, industry and governmental sectors to share and exchange novel ideas, explore the inherent challenges in developing future smart grids, investigate novel designs, explore enabling technologies and share relevant experiences on machine learning methods in smart grid and its applications.

Topics for the session include, but are not limited to:

• Enabling technologies for smart grids
• Smart metering and non-intrusive load monitoring
• Short-term load forecasting
• Data management and grid analytics
• Planning of distributed storage for distribution systems
• Micro grids, clean & renewable energy resources and their integration
• Self-healing networks, power flow management and voltage control
• Energy management system, optimization and electricity markets
• Demand side management, optimization and integration of electrical vehicles
• Intelligent multi-agent system and IoT for power engineering
• Smart sensing, diagnostics, condition monitoring, predictive maintenance
• Applications of computational intelligent techniques and optimization techniques

Dr Wai Lok Woo received the BEng (Hons) in Electrical and Electronics Engineering, MSc and the PhD degrees from the Newcastle University, UK. He is Reader in Intelligent Signal Processing and Director Research for Newcastle Research and Innovation Institute. He is also the Director of Operations for Newcastle University in Singapore. His major research is in the mathematical theory and algorithms for machine learning. This includes areas of data analytics, artificial intelligence, signal processing and computational intelligence for smart grids. He chaired several international conferences and has published over 300 papers on these topics. He serves as Associate Editor of the IEEE, IET and Hindawi journals. Dr Woo is a Senior Member of the IEEE and Member of the Institution Engineering Technology (IET).

Dr Anurag Sharma received Bachelor’s Degree in Electrical Engineering from Malaviya National Institute of Technology (MNIT) Jaipur, India, and the PhD degree from Department of Electrical and Computer Engineering, National University of Singapore (NUS). He is currently Assistant Professor at Electrical Power Engineering at Newcastle University, Singapore campus. Before joining Newcastle University, he worked as a Research Engineer at Energy Management and Micro-grid Lab @ NUS. His main research interests include: fault management, service restoration in distribution systems, energy management in Micro-grids, Distributed energy resources – integration and their application for various ancillary services, machine learning and multi-agent system application in power systems.

Dr Thillainathan Logenthiran is an Assistant Professor at the school of Electrical and Electronic Engineering, Newcastle University. His main research areas of interest include smart grid, micro grid, renewable energy resources, and the applications of computational intelligent techniques & intelligent multi-agent system for development of smart grid and modern power systems. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), a Member of the Institution of Engineering and Technology (IET), and Associate Fellow of the Higher Education Academy (HEA), United Kingdom. Dr T Logenthiran is a Chairman of the IEEE PES Singapore Chapter for year 2018, Degree Programme Director (DPD) of the Master Programme in Electrical Power Engineering, Singapore, and Research Lead in the School of Electrical and Electronic Engineering, Singapore. He received several awards and scholarships including the first prize award in Siemens Smart Grid Innovation Contest and a Newcastle Teaching Award.