Keynote Speakers

Keynote Speaker I

Prof. Qiang Yang
 Zhejiang University, China

Title: AI Empowered Sustainable Energy Systems: Challenges and Case Studies

Abstract: The current power systems are undergoing a rapid transition towards their more active, flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in many domains, e.g., integration of various distributed renewable energy sources, cyberspace security, demand-side management, and decision-making of system planning and operation. The fulfillment of advanced functionalities in the smart grid firmly relies on the underlying information and communication infrastructure, and the efficient handling of a massive amount of data generated from various sources, e.g., smart meters, phasor measurement units, and various forms of sensors. This talk will briefly cover the AI empowered sustainable energy systems from the aspects of technical challenges and case studies. It demonstrates the increasing interest and rapid expansion in the use of machine learning techniques to successfully address the technical challenges of the smart grid from various aspects. It is also revealed that some issues still remain open and worth further research efforts, such as the high-performance data processing and analysis for intelligent decision-making in large-scale complex multi-energy systems, lightweight machine learning-based solutions, and so forth. Moreover, the future perspectives of utilizing advanced computing and communication technologies, e.g., edge computing, ubiquitous internet of things and 5G wireless networks, in the smart grid are also highlighted. To the best of our knowledge, this is the first review of machine learning-driven solutions covering almost all the smart grid application domains. Machine learning will be one of the major drivers of future smart electric power systems, and this study can provide a preliminary foundation for further exploration and development of related knowledge and insights.

Biodata: Qiang Yang (M'03-SM'18) received Ph.D. degree in Electronic Engineering and Computer Science from Queen Mary, University of London, London, U.K., in 2007 and worked in the Department of Electrical and Electronic Engineering at Imperial College London, U.K., from 2007 to 2010. He visited the University of British Columbia and the University of Victoria Canada as a visiting scholar in 2015 and 2016. He is currently a full Professor at the College of Electrical Engineering, Zhejiang University, China, and has published more than 240 technical papers, filed more than 60 national and international patents, co-authored 2 books, and edited 2 books and several book chapters. His research interests over the years include smart energy systems, large-scale complex network modeling, control and optimization, learning based optimization and control. He is a Fellow of the British Computer Society (BCS), a Senior Member of IEEE and the Senior Member of China Computer Federation (CCF).


Keynote Speaker II

Prof. Yunhe Hou
 The University of Hong Kong, Hong Kong, China

Title: Resilient Operation of Urban Power Grids under the New Energy Paradigm

Abstract: A reliable power supply is essential for maintaining societal and economic well-being. Strengthening resilience in the emerging energy infrastructure is a critical aspect of modernization. This presentation will explore urban energy systems operation during extreme weather events, with an emphasis on renewable energy integration. Proactive resilient operating strategies for extreme events and coordination approaches for various stages of these events will be demonstrated. A systematic method for modelling aleatoric and epistemic uncertainties will be proposed to quantify the different uncertainties during extreme events. Additionally, the potential applications of innovative power-electronic devices to enhance resilience will be discussed in this talk.


Biodata: Yunhe Hou received the B.E. and Ph.D. degrees in electrical engineering from Huazhong University of Science and Technology, Wuhan, China, in 1999 and 2005, respectively. He was a Post-Doctoral Research Fellow at Tsinghua University, Beijing, China, from 2005 to 2007, and a Post-Doctoral Researcher at Iowa State University, Ames, IA, USA, and the University College Dublin, Dublin, Ireland, from 2008 to 2009. He was also a Visiting Scientist at the Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA, in 2010. He has been a Guest Professor with Huazhong University of Science and Technology, China from 2017 and an Academic Adviser of China Electric Power Research Institute from 2019. He joined the faculty of the University of Hong Kong, Hong Kong, in 2009, where he is an Associate Professor with the Department of Electrical and Electronic Engineering. Dr. Hou was an Associate Editor of the IEEE Transactions on Smart Grid from 2016 to 2021. Dr. Hou is currently an Associate Editor of the IEEE Transactions Power Systems and Journal of Modern Power Systems and Clean Energy.

Keynote Speaker III

Prof. Feng Deng
 Changsha University of Science and Technology, China

Title: Research on High Impedance Fault Sensing and Accurate Identification in New Distribution System

Abstract: The construction of the new distribution system makes the distribution network a significantly high-dimensional, stochastic, complex and large-scale nonlinear system, which brings new challenges to the accurate identification of high impedance faults (HIFs). Therefore, the research on sensitive perception and accurate identification of HIFs in new distribution system has been carried out. Firstly, the survival and development mechanisms of HIFs in the distribution network were studied. On this basis, a HIFs model using dynamic impedance in series was proposed, which can accurately simulate the nonlinear characteristics of fault. And then, by analyzing the difference of the time-frequency energy distribution of the signal in the case of HIFs and normal transient disturbance, the theoretical foundation is laid for the recognition of HIFs. Next, a PCB traveling wave sensor based on Rogowski coil was developed, which has the advantages of wide frequency band response and strong anti-interference capability. Subsequently, research was conducted on high-precision voltage traveling wave detection methods based on L1 regularization inversion and the fault traveling wave time-frequency analysis method based on variational modal decomposition and wigner ville distribution (VMD-WVD). These methods aim to achieve sensitive detection of HIF signals and provide technical support for the identification of HIFs. Finally, a convolutional neural network and support vector machine (CNN-SVM) hybrid neural network is used to solve the problem of difficult model training under small sample scenarios of HIFs, a graph attention neural network is utilized to overcome the impact of network topology changes. additionally, a data-knowledge fusion-driven approach is employed to construct a fault identification model that adapts to various fault scenarios, which ultimately realize the sensitive sensing, effective identification, accurate line selection and precise location of HIFs in the new distribution system.


Biodata: Deng Feng, Distinguished Professor, PhD supervisor, Hunan Provincial Distinguished Youth Scholar, Hunan Provincial "Huxiang Young Talent" in Science and Technology Innovation, Teaching Master of Ideological and Political Education Demonstration Courses sponsored by the Ministry of Education, currently serves as the Deputy Director of the Academic Affairs Office at Changsha University of Science and Technology. She has long been engaged in long-term research in the fields of power system protection and fault localization, as well as weak fault detection in distribution networks. In the past five years, she has led two General Programs of National Natural Science Foundation of China and over 10 provincial and ministerial-level programs, including the Hunan Provincial Science Foundation for Distinguished Young Scholars, and undertaken two national key research and development programs as a key researcher. She also serves as the Deputy Secretary-General of the IEEE PES Power System Protection and Control Technical Committee and a young editorial board member of "Power System Protection and Control." She received the Hunan Provincial Science and Technology Progress First Prize in 2020, the Gold Medal at the International Exhibition of Inventions Geneva in 2021, the First Prize in the Hunan Provincial Higher Education Teaching Achievement Awards in 2022, and the Third Prize in the National University Young Teachers Teaching Competition in 2023.

Keynote Speaker IV

Dr. Kai Shi
TAE Power Solutions Ltd. UK & TAE Technologies California, USA
The University of Warwick, UK

Title: Industrial Applications of the Hardware-in-the-loop Testing for Battery System Developing in the Area of Automotive, Aerospace, and Grid Storage

Abstract: Hardware-in-loop (HiL) testing has come an important part of the research and development (R&D) of complex systems for both academic research and industrial applications. An increasing number of industrial companies have integrated the HiL testing into their V-model for the R&D. This presentation will give an introduction to the HiL system and its application in developing battery systems for automotive, aerospace, and grid storage applications. The concept of HiL testing, the architecture of a HiL system, and the approach of designing HiL testings will be introduced. Several case studies about the integration of HiL testing for automotive and aerospace applications will be demonstrated.


Biodata: Dr Kai Shi received his BEng and PhD in electrical engineering and electronics from the University of Liverpool UK, in 2013 and 2018, respectively. From 2018 to 2023, he worked as a research fellow in the Hardware-in-the-loop Laboratory supported by the High Value Manufacturing Catapult (HVMC) funds at the Warwick Manufacturing Group (WMG), the University of Warwick UK. Being with WMG for 5 years, he worked closely with industries and had been involved in several R&D projects with automotive and aerospace companies such as Lotus, BMW, Vertical Aerospace UK, and Rolls Royce Aerospace etc. In 2023, he moved to industry and joined the TAE Power Solution UK as a senior engineer for developing the next generation of the battery and power electronics systems.

Keynote Speaker V

Prof. Jianzhong Xu
North China Electric Power University, China

Title: Unified iterative algorithm for power flow of AC/DC system with multi-type DC links

Abstract: As an emerging trend in power grid development, the AC/DC hybrid power grid presents the characteristics of multi-type DC links and large-scale AC/DC interconnection. This presentation will explore a power flow calculation algorithm for large-scale AC/DC systems with multi-type DC links. The power grid dispatching system's CIM/XML file is converted into power flow calculation data, and a unified approach to model the AC/DC system's power flow discussed. A unified iterative algorithm for large-scale AC/DC system with multi-type DC links is then proposed. The algorithm's correctness and effectiveness are verified by comparing with actual measurements from southern power grid of China.


Biodata: Jianzhong Xu (Senior Member, IEEE) was born in June 1987, Shanxi, China. He received the B.S. and Ph.D. degrees from North China Electric Power University (NCEPU) in 2009 and 2014 respectively, majoring in Power System and Its Automation. Currently, he is a professor of the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (NCEPU), Beijing, China. From 2012 to 2013, and 2016 to 2017, he was respectively a Visiting Ph.D. Student and Post-Doctoral Fellow at the University of Manitoba, under supervision of Prof. Ani Gole. He has published 120 journal papers with 4 Highly Cited Papers, 3 books and 60 patents. He also serves as Editorial Committee Members/Reviewers of 12 journals, and was outstanding reviewer of IEEE TPWRD in 2020. He is now working on the electromagnetic transient (EMT) simulations of emerging power electronic converters (MMC, SST, etc.), renewable energy source generations and large-scale AC/DC power gird.