ACM eEnergy 2017, May 17-19, 2017, Hong Kong
Site Menu

Keynote Speakers

Professor David J Hill, The University of Hong Kong

Professor David J Hill, The University of Hong Kong

Control Architectures for Power Grids with High Renewables

This talk will consider the long-term structure of electrical power delivery systems assuming high levels of renewable energy sources (RES). The problems of operating such systems in a whole of system sense go way beyond recent considerations of smart grids and appropriate research is in early stages. The issues and some progress to date will be described with emphasis on the projects led by the speaker in HK-China.

The proper operation of an electricity grid involves an intricate set of balancing processes for energy, power and ramping all while achieving the regulation of system variables, e.g. voltages, frequency, line powers, and keeping the system protected and secure following disturbances. This is achieved with layers of system control (and market) processes. These processes all need to be redesigned for high levels of renewable power due to the weather driven variability of the power supply (adding to variability already there elsewhere). Further, the solutions will vary according to interconnection circumstances, i.e. an isolated large island like Australia has a much different problem than the highly interconnected European countries aiming at high RES. Some studies have been made by governments worldwide to answer the question: what percentage levels of renewable energy are achievable? The answer will be dependent on the control architectures in place. It is possible that this is all this development is limited by stability problems caused by the variable generation and network structure.

As the recent blackout in South Australia illustrates, questions on the viability of RES for major power production can be very complex (except to the eyes of politicians). The importance of good science playing a role and being seen to have a role will be given some attention.


David J. Hill received the PhD degree in Electrical Engineering from the University of Newcastle, Australia, in 1976. He holds the Chair of Electrical Engineering in the Department of Electrical and Electronic Engineering at the University of Hong Kong. He is also a part-time Professor in the Centre for Future Energy Networks at The University of Sydney, Australia.

During 2005-2010, he was an Australian Research Council Federation Fellow at the Australian National University. He has held various positions at the University of Sydney since 1994 including the Chair of Electrical Engineering until 2002 and again during 2010-2013 along with an ARC Professorial Fellowship. He has also held academic and substantial visiting positions at the universities of Melbourne, California (Berkeley), Newcastle (Australia), Lund (Sweden), Munich and in Hong Kong (City and Polytechnic Universities).

His general research interests are in control systems, complex networks, power systems and stability analysis. His work is now mainly on control and planning of future energy networks and basic stability and control questions for dynamic networks. Professor Hill is a Life Fellow of the Institute of Electrical and Electronics Engineers, USA. He is a Fellow of the Society for Industrial and Applied Mathematics, USA, the Australian Academy of Science, the Australian Academy of Technological Sciences and Engineering and the Hong Kong Academy of Engineering Sciences. He is also a Foreign Member of the Royal Swedish Academy of Engineering Sciences.

Jiannong Cao (Full professor and Head of the Department of Computing at Hong Kong Polytechnic University)

Jiannong Cao

Toward Energy Efficient Wireless Sensor Networks

In the last decade, wireless sensor networks (WSNs) have appeared as a new form of distributed embedded system and have been applied in various areas including structural health monitoring, volcanic monitoring and smart grid. WSNs contain a large collection of autonomous devices that collaborate with each other to achieve the assigned tasks. In many applications of WSNs, energy efficiency has been regarded as one of the most important bottlenecks. To realize an energy efficient WSN system entail the design considerations from various aspects including data sampling, in-network processing, and energy harvesting. In this talk, I will describe a framework of achieving energy efficient WSNs and discuss our previous research outputs on designing energy-efficient WSNs, with particular focus on the application of structural health monitoring.


Dr. Cao is currently a chair professor and head of the Department of Computing at Hong Kong Polytechnic University, Hung Hom, Hong Kong. His research interests include parallel and distributed computing, wireless networks and mobile computing, big data and cloud computing, pervasive computing, and fault tolerant computing.. He has co-authored 3 books, co-edited 9 books, and published over 300 papers in major international journals and conference proceedings. He is a fellow of IEEE, a senior member of China Computer Federation, and a member of ACM. He was the Chair of the Technical Committee on Distributed Computing of IEEE Computer Society from 2012 - 2014. Dr. Cao has served as an associate editor and a member of the editorial boards of many international journals, including ACM Transactions on Sensor Networks, IEEE Transacitons on Computers, IEEE Transactions on Parallel and Distributed Systems, IEEE Networks, Pervasive and Mobile Computing Journal, and Peer-to-Peer Networking and Applications. He has also served as a chair and member of organizing / program committees for many international conferences, including PERCOM, INFOCOM, ICDCS, IPDPS, ICPP, RTSS, DSN, ICNP, SRDS, MASS, PRDC, ICC, GLOBECOM, and WCNC. Dr. Cao received the BSc degree in computer science from Nanjing University, Nanjing, China, and the MSc and the Ph.D degrees in computer science from Washington State University, Pullman, WA, USA

Download Proceedings

Enter the “Registration ID” from your registration confirmation email.

The ACM eEnergy 2017 Website by ACM SIGCOMM 2012 is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Source code is available at