Assoc. Prof. Wei Lai, Chongqing University, China

Wei Lai, Associate professor, Master's/ Doctor's Supervisor, IEEE Senior member, Be selected Stanford University Top 2% Scientists List for two years. The main research interests are the reliability of power modules, the application of power electronics for electric power generation, and the development of condition monitoring methods for power electronic converters. Be awarded the 2nd Prize for Chongqing City Scientific and Technological Progress Award, Twice. Be awarded the First Prize for Chongqing City Excellent Teaching Achievement. Have published more than 50 papers in journals or conferences, which are cited more than 1160 times, H-index is 14, and i10-index is 26 in Google Scholar. Co-authored and published three monographs. More than 10 Chinese invention patents were authorized.

Title: Research on Reliability Evaluation Method for Traction System IGBT Devices of Electric Locomotives with Different Service Mileage

Abstract: In electric locomotive systems, the function of the traction converter depends heavily on the IGBT module, and IGBT module is prone to failure. Traditionally, ensuring safety has involved expensive and wasteful "mileage maintenance", which includes regular replacement of IGBT modules. Therefore, it is meaningful to evaluate the reliability by taking into account their different service miles. Firstly, the dynamic and static characteristics of IGBT modules under different service mileage are compared and analyzed. Secondly, power cycling tests for different mileage IGBT modules are carried out to analyze the differences, and the microscopic analysis of the failure module further confirms the results of the failure analysis. Finally, a remaining lifetime predicted method of power electronic devices is proposed.

Assoc. Prof. Lidan Chen, Guangzhou Maritime University, China

Lidan Chen, Associate Professor, Master Director, worked in building automation and industrial automation in enterprises for 3 years, worked as a research assistant in the Department of Electrical Engineering of the Hong Kong Polytechnic University, and was a visiting scholar at Zhejiang University and Michigan Technological University in the United States. Now he is a full-time faculty member of Guangzhou Maritime Academy, and he is a member of Institute of Electrical and Electronics Engineers (IEEE), a director of IEEE PES China Sub-committee on Convergence Technologies for Electric Vehicles and Energy Transportation Systems, and an expert of the Expert Pool of the National Assessment and Monitoring of Postgraduate Education in the Center for Development of Degree and Postgraduate Education of the Ministry of Education. He has published more than 30 scientific and technical papers in Chinese core journals of Peking University and SCI/ EI, and has been selected as one of the TOP 1% of highly cited scholars in 2024 China Knowledge Network; he has been authorized with more than 10 patents; he has presided over and participated in more than 20 textbook and research projects such as international (regional) cooperative research project of the National Natural Science Foundation of China, engineering and technology center of ordinary universities in Guangdong Province, and the provincial key laboratory open fund, etc. He has been awarded the prize of the Guangdong Province teaching achievement award. He has won the second prize of Guangdong Teaching Achievement Award, the annual excellent paper award of China Electrotechnical Society, the annual excellent reviewer of Grid Technology and Power System Automation, and more than 10 prizes of “Challenge Cup” Guangdong University Students' Extracurricular Academic and Technological Works Competition.

Title: Energy theft attack detection for smart grids

Abstract: The rapid evolution of smart grid technologies has revolutionized the way electricity is generated, distributed, and consumed. However, this transformation has also introduced new vulnerabilities, particularly in the form of energy theft attacks. These malicious activities not only result in significant financial losses for utility providers but also compromise the reliability and security of the entire power grid. In this invited talk, we will delve into the critical issue of energy theft detection in smart grids, exploring the latest advancements, challenges, and future directions in this field.

Energy theft in smart grids typically involves unauthorized manipulation of smart meters, tampering with communication networks, or exploiting vulnerabilities in the grid's infrastructure. Traditional methods of detecting energy theft, such as manual inspections and basic statistical analyses, are increasingly inadequate in the face of sophisticated attacks. Consequently, there is a pressing need for more advanced, automated, and intelligent detection mechanisms.

This talk will present a comprehensive overview of state-of-the-art techniques for energy theft detection, focusing on the application of machine learning (ML) and deep learning (DL) algorithms. These methods leverage vast amounts of data generated by smart meters and other grid components to identify anomalous patterns indicative of theft. We will discuss various ML/DL models, including supervised, unsupervised, and reinforcement learning approaches, and their effectiveness in different scenarios.

Furthermore, the talk will address the challenges associated with implementing these detection systems in real-world smart grids. Issues such as data privacy, computational complexity, and the need for real-time processing will be examined.

Finally, the speaker will give an example of a state-based approach to energy theft detection. 

Assoc. Prof. Song Hu, Changshu Institute of Technology, China

Song Hu, Ph.D./Postdoctoral Fellow, Associate Professor, Master Supervisor, graduated from Macau University of Science and Technology (MUST) in July 2018 with a Ph.D. degree, and has been teaching in the School of Electrical and Automation Engineering of Changshu Polytechnic University since September 2018. He has been selected as the third level training object of “333 high-level talents training project” in Jiangsu Province, the vice president of science and technology in Jiangsu Province, and the young science and technology talents support project of Suzhou Science and Technology Association, and has been awarded the “May 4th Youth Medal” of Changshu Polytechnic, and the Contribution Award of the School of Electrical and Automation Engineering. Honors. He has presided over 1 project of National Natural Science Foundation of China, 1 project of Natural Science Foundation of Jiangsu Province, 1 project of Jiangsu Universities and Colleges, 1 project of Postdoctoral Fund of Jiangsu Province, 1 project of Suzhou Young Scientific and Technological Talents Supporting Project, and 2 projects of enterprises' lateral projects. He has published more than 40 SCI/EI papers. Applied for/authorized 20 invention patents. He was awarded 1 Macao SAR Postgraduate Technology R&D Award, IEEE Member, China Electrotechnical Society, China Power Supply Society, China Automation Society. He is a member of IEEE Transactions on Power Electronics, IEEE Transactions on Industrial Electronics, IEEE Journal of Emerging and Selected Topics in Power Electronics, and so on. IEEE Transactions on Industrial Electronics, IEEE Journal of Emerging and Selected Topics in Power Electronics, and other top journals in the field of power electronics.

Title: The Study of Dual Bridge Resonant Converters

Abstract: The Dual Active Bridge (DAB) converter is widely recognized for its high efficiency, structural symmetry, and natural bidirectional power flow capability, making it a key component in applications such as renewable energy systems, electric vehicles, and microgrids. Building on the strengths of DAB, the Dual Bridge Resonant Converter (DBRC) has been developed to further enhance performance by addressing some of DAB's limitations, including high reactive power and challenges in achieving full-load Zero Voltage Switching (ZVS). The introduction of resonant components in DBRC topologies, such as the Dual Bridge Series Resonant Converter (DBSRC) and Semi-Dual Bridge Resonant Converter (SDBRC), has led to improved performance, including reduced conduction losses, wider ZVS ranges, and lower circulating energy. Various modulation techniques, including Single Phase Shift (SPS), Extended Pulse Width Modulation (EPWM), and Fast Transient Modulation (FTM), have been proposed to enhance the efficiency and dynamic response of DBRC. Control strategies like Minimum Current Trajectory (MCT) and Voltage Match Modulation (VMM) further optimize the converter's performance by minimizing resonant current and extending the ZVS range. This presentation will explore the evolution from DAB to DBRC, focusing on innovative topologies, advanced modulation methods, and effective control strategies, highlighting their impact on improving the operational range and efficiency of resonant converters in modern power systems.