Prof. Minjie Zhang from the University of Wollongong, in Australia was invited to Mid Sweden University to hold a seminar on Big Data in smart grids. This was Prof. Minjie Zhangs first visit to Sweden and the start of a new collaboration between the two universities.
Prof. Minjie Zhang was invited to Mid Sweden University in December 2016. At her visit she held an open seminar called “Multi-agent Solution for Supply-Demand Management in smart grid markets” to the master- and PhD-students. She also met the researchers within the STC Research Centre to learn more about the research that are conducted at Mid Sweden University and find new cooperation opportunities between the two universities.
The first time Prof. Minjie Zhang got in contact with Mid Sweden University was when she met a PhD-student from Mid Sweden University at a conference in Europe. It turned out that the PhD-student's supervisor, Prof. Tingting Zhang at Mid Sweden University, was Prof. Minjie Zhang's old classmate from Fudan University, China. The two professors resumed contact again and it turned out that they once again worked in the same research area. They applied and received a grant from funder Faculty of Science, Technology and Media that made it possible for Prof. Zhang Minjie to visit Mid Sweden University and now the two professors hope to deepen cooperation between the University of Wollongong and Mid Sweden University. Hopefully there will be funding for student exchange and a joint research collaboration in the future.
At the lecture Prof. Minjie Zhang presented the complex and dynamic smart grid market where consumer where consumer demand and market be assets controlled by several factors. She presented an agent-based broker model for power trading in smart grid markets and a load forecasting approach in smart grid market through customer behaviour learning.
Brief CV of Prof Minjie Zhang
Dr Minjie Zhang received her Bachelor of Computer Science degree from Fudan University, China in 1982 and her Ph.D. degree from the University of New England, Australia in 1996. She had been employed as a lecturer in Edith Cowan University and in Newcastle University; and a senior lecturer, then an associate professor in the University of Wollongong. Currently she is a full professor, the Head of Postgraduate Studies (HPS) in the School of Computing and Information Technology, and the Director of Intelligent Systems Research Centre at the University of Wollongong, Australia. She is a senior member of the IEEE and IEEE Computer Society.
Dr Zhang is a leading researcher in the field of agent and multi-agent research and has edited 14 scholarly books with Springer and 5 special issues with reputable journals. She is the author, or co-author, of over 200 research papers including 60 papers in high impact journals. Dr Zhang is the chief investigator of 2 Australia Research Council (ARC) Discovery Grants, 1 ARC Linkage Grant and 1 ARC International Linkage Award and 1 large grant from Australia Defense Department. She has been the chair/co-chair of over 20 International conferences/workshops. She is also a Senior Committee Member for the International Conference on Autonomous Agent and Multi-agent Systems (AAMAS, the world top conference in agent and multi-agent research). She was the winner of the vise chancellor’s “The Best Research Supervision Award” in 2009 and 2013 from the University of Wollongong. Her research interests include multi-agent systems and their applications in complex domains, distributed artificial intelligence, smart modeling and simulation in complex systems, data mining and knowledge discovery, service-oriented systems, agent-based grid/cloud computing, and smart grid systems.
Seminar Title: Multi-agent Solutions for Supply-Demand Management in smart grid markets
A smart grid market is a complex and dynamic market with various participators, including energy generators, general consumers, interruptible consumers, storage consumers, or even small renewable energy producers, such as solar systems and windmills. Moreover, different participators exhibit a variety of behaviours. For instance, the behaviours of solar and wind energy producers are closely related to the weather conditions, while some interruptible consumers can contribute extra energy to supply-demand balance. Besides, the large energy generators may produce variant quantities of energy from day to day. Due to the complexity and dynamics, it is of great challenge to manage supply-demand balance in the Smart Grid market.
Agent and multi-agent technologies offer potential solutions to the above challenge, by using the capabilities of intelligent modelling, management and group collaboration, in addition to the learning and self-organising abilities and autonomous decision making of individual agents. This talk will introduce our two new solutions in smart grid research, including (1) an agent-based broker model for power trading in smart grid markets; and (2) a load forecasting approach in smart grid market through customer behaviour learning.