The use of exergy methods is described as tools for addressing climate change so the benefits can be appreciated and attained. Exergy can be used to understand climate change measures and to assess and improve energy systems, and can help better understand the benefits of utilizing sustainable energy by providing more useful and meaningful information than energy provides. Exergy clearly identifies efficiency improvements and reductions in wastes and environmental impacts attributable to sustainable energy. Exergy can also identify better than energy the environmental benefits and economics of energy technologies. Exergy should be applied in addressing climate change

Exergy; climate change; environment; ecology; energy.

Marc A. Rosen, Ph.D., is a Professor at University of Ontario Institute of Technology in Oshawa, Canada, where he served as founding Dean of the Faculty of Engineering and Applied Science. Dr. Rosen has served as President of the Engineering Institute of Canada and of the Canadian Society for Mechanical Engineering. He has acted in many professional capacities, including Editor-in-Chief of various journals and a Director of Oshawa Power and Utilities Corporation. With over 70 research grants and contracts and 900 technical publications, Dr. Rosen is an active teacher and researcher in sustainable energy, sustainability, and environmental impact. Much of his research has been carried out for industry. Dr. Rosen has worked for such organizations as Imatra Power Company in Finland, Argonne National Laboratory near Chicago, the Institute for Hydrogen Systems near Toronto, and Ryerson University in Toronto, where he served as Chair the Department of Mechanical, Aerospace and Industrial Engineering. Dr. Rosen has received numerous awards and honours, and is a Fellow of numerous societies .

TBA.

Solids can have a wide variety of structural and functional properties. In terms of electrical conductivity, they are used as metallic conductors, semiconductors or insulators. Ceramic materials can even show superconductivity at practically usable temperatures. In addition, ceramics are also able to transport ions. In many cases this conductivity is low, but in some cases it is very high and of practical importance due to structural disorder in the crystal lattice. As a result, solids can take on tasks that electrons are unable to perform. These are particularly important in the area of energy conversion and storage as well as environmental protection. In times of climate change and resource conservation, they are of outstanding practical importance. Applications include new generations of solid state batteries, fuel cells, electrochromic windows, and chemical sensors. In addition to ceramics with predominantly ionic conduction, such solids with mixed electronic-ionic conduction play an important role that has so far been neglected, e.g. for electrodes for rapid charging and discharging. The possibilities of developing and using such ceramics with predominantly ionic conduction as well as mixed electronic-ionic conduction are shown in particular using the example of all-solid-state high-performance batteries. Applications in fuel cells and electrochromic systems are also briefly touched upon.

TBA.

Prof. Werner Weppner holds since 1993 the Chair for Sensors and Solid State Ionics at the Faculty of Engineering of Christian Albrechts University, Kiel, Germany. He has been earlier at the Max-Planck-Institute for Solid State Research, Stuttgart and a Research Professor at Stanford University, CA, USA, in the Department of Materials Science and Engineering. Prof. Weppner holds a diploma in physics from Mainz University and a Ph.D. in chemistry from Dortmund University, both Germany. His research interests are based on fast ionic transport in solids and include both fundamental understanding and practical application aspects.

TBA.

In this talk, three machine learning (ML) algorithms viz. Support Vector Regression (SVR), Artificial Neural Networks (ANN), and Extreme Gradient Boosting (XGBoost) are implemented to predict wake velocity and turbulence intensity from a wind turbine at different downstream distances. To this end, a set of high-fidelity numerical simulations are performed for the NREL Phase VI wind turbine to produce training and test datasets for the three machine learning algorithms. Using the trained model, the wake flow field downstream of the blade and turbulence intensity are predicted on the test datasets which are hidden from the trained model. The prediction of wake velocity deficit and turbulence level in the wake from the machine learning algorithms are commensurate to the Computational Fluid Dynamics (CFD) simulations while running as fast as low-fidelity wake models. The wake velocity and turbulence intensity obtained from the ML models are also compared with some of the analytical wake models. The results reveal that machine learning-based algorithms can approximate wake and turbulence intensity characteristics better than the traditional analytical wake models..

Wake velocity, turbulence intensity, Support Vector Regression (SVR), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost).

Eddie is elected as:

• Academician for European Academy of Sciences and Arts (EASA, EU);
• Fellow of the American Society of Mechanical Engineers (FASME, USA);
• Fellow of Institute of Engineering and Technology (FIET, United Kingdom);
• Fellow of International Engineering and Technology Institute (FIETI, Hong Kong), 
• Distinguished Fellow for Institute of Data Science and Artificial Intelligence, (DFIDSAI, China), and, Academician for Academy of Pedagogy and Learning, (USA).

He has published numerous papers in SCI-IF int. journal (430); int. conf. proceedings (130), textbook chapters (>105) and others (32) over the 29 years. Co-edited 14 books in STEM areas.

He is the:

• Lead Editor-in-Chief for the ISI Journal of Mechanics in Medicine and Biology for dissemination of original research in all fields of mechanics in medicine and biology since 2000;
• Founding Editor-in-Chief for the ISI indexed Journal of Medical Imaging and Health Informatics;
• Associate editor or EAB of various referred international journals such as Applied Intelligence, BioMedical Engineering OnLine, Computers in Biology & Medicine, and, Journal of Advanced Thermal Science Research.

TBA.

Electricity systems around the world are experiencing a radical transition as the consequence of replacing fossil fuels, used for electricity production, by sustainable and cleaner energies. The growing penetration of renewable energies requires smarter techniques capable of handling the uncertainties of these intermittent sources. Along with this change, traditionally centralised power systems are also converting into distributed self-sufficient systems, often referred to as microgrids, that can operate independently. This talk will focus on remote area microgrids as a hot research topic in Australia and Southeast Asia that have hundreds of remote and off-grid towns and communities, and islands. It is expected that remote area microgrids will strongly benefit these remote locations in the forthcoming years. This talk will briefly introduce the progress of research in this field around the world and Australia, and will also discuss some of the technical challenges associated with interconnection of neighbouring microgrids as a key step to improve their survivability in the course of unexpected imbalances between the demand and the available generation from intermittent renewable resources.

TBA.

A/Professor Farhad Shahnia received his PhD in Electrical Engineering from Queensland University of Technology (QUT), Brisbane, in 2012. He is currently an A/Professor at Murdoch University. Before that, he was a Lecturer at Curtin University (2012-15), a research scholar at QUT (2008-11), and an R&D engineer at the Eastern Azarbayjan Electric Power Distribution Company, Iran (2005-08). He is currently a Fellow member of Engineers Australia, Senior Member of IEEE, and member of the Australasian Association for Engineering Education.

Farhad’s research falls under Distribution networks, Microgrid and Smart grid concepts. He has authored one book and 11 book chapters and 100+ peer-reviewed scholarly articles in international conferences and journals, as well as being an editor of 6 books.

Farhad has won 5 Best Paper Awards in various conferences and has also received the IET Premium Award for the Best Paper published in the IET Generation, Transmission & Distribution journal in 2015. One of his articles was listed under the top-25 most cited articles in the Electric Power System Research Journal in 2015 while one of his 2015 journal articles has been listed under the top-5 most read articles of the Australian Journal of Electrical and Electronics Engineering. He was the recipient of the Postgraduate Research Supervisor Award from Curtin University in 2015 and the Australia-China Young Scientist Exchange Award from the Australian Academy of Technology and Engineering in 2016.

Farhad is currently a Subject Editor, Deputy Subject Editor, and Associate Editor of several journals including IEEE Access, IET Generation, Transmission & Distribution, IET Renewable Power Generation, IET Smart Grid, IET Energy Conversion and Economics, and International Transaction on Electrical Energy Systems and has served 35+ conferences in various roles such as General, Technical, Publication, Publicity, Award, Sponsorship, and Special Session Chairs.

Farhad is currently the Chair of the IEEE Western Australia Section and a member of IEEE’s Industrial Electronics Society (IES)’s Technical Committees of Smart Grid and Energy Storage

TBA.