2022 International Conference on Power Grid Systems and Energy Storage Technology (PGSEST 2022)



Prof. Jizhong Zhu

School of Electric Power Engineering

South China University of Technology

National Distinguished Expert

Chairman of IEEE PES China Chapters Council SBLC Satellite Committee

IEEE Fellow, IET Fellow, Alstom Fellow, CSEE Fellow

Jizhong Zhu holds the following titles: Guangzhou Innovation Leading Talent, Professor and Doctoral Supervisor of the South China University of Technology, Head of the Integrated Smart Energy System Optimal Operation and Control (ISESOOC) Team/Center, Adjunct Professor and Doctoral Supervisor of Chongqing University, chairman of IEEE PES China Chapters Council SBLC Satellite Committee, editorial board member of MPCE and other international journals, chairman of IEEE P2781 International Standard Working Group for Load Modeling and Simulation, Chairman of IEEE P2783 International Standard Working Group for Rapid Load Response System, member of IEEE SMC Standards Committee, member of the IEEE SMC Smart Power and Energy System Special Committee, member of the Sino-Swiss Smart Grid Technical Expert Committee, and member of the National Power Demand Side Management Standard Expert Committee. He has served as a member of the first National Innovation Award Evaluation Expert Committee, an evaluation expert for various national, provincial and municipal talents and projects, the chairman of the IEEE Power Load Sub-Committee in the United States, and the chairman of the IEEE SBLC Asia-Pacific Working Group.


Prof. Tao Yu

School of Electric Power Engineering

South China University of Technology

Chairman of the IEEE PCCC SBLC Power Load Sub-committee

Vice-Chairman of the IEEE PES Flexible Resource Interconnection Committee (China)

Prof. Tao Yu has been appointed as "Pearl River Scholar" Professor, Doctoral Supervisor, and Deputy Director of Guangdong Key Laboratory of Power Grid Smart Energy Measurement and Advanced Metrology Enterprise. He received his bachelor's degree from Zhejiang University and completed his Ph.D. degree from Tsinghua University. He is the secretary-general of the Artificial Intelligence and Electrical Application Committee of China Electrotechnical Society, the chairman of the IEEE PES SBLC Power Load Characteristics Sub-committee (China), and the vice-chairman of the IEEE PES Flexible Resource Interconnection Committee (China). He focuses on intelligent distribution network planning and operation technology, artificial intelligence application theory in power system perception and decision-making, and other fields. So far, he has presided over 4 projects of the National Natural Science Foundation of China, undertaken a key project of the National Natural Science Foundation of China, and 15 key scientific and technological projects of the two major power grid companies. He has published 4 monographs and more than 160 SCI journal papers and was awarded the "2020 China Highly Cited Scholar" by Elsevier. He has won 12 provincial and ministerial awards, including the first prize of the China Electric Power Innovation Award, the second prize of the China Electric Power Technology Invention Award, and the third prize of the Jiangsu Science and Technology Award.



Director Yebing Liu

New Energy Center

Chinese Society For Urban Studies

Yebing Liu graduated from Northeastern University in 1982, serving as a visiting scholar at the University of Liverpool (UK) and a Ph.D. at Liverpool Johnmouth University (UK). He used to be the director of the automatic control room of Shenyang Aluminum and Magnesium Design and Research Institute, the chairman of Xidong Control Group, the chairman of the Digital Community Industry Alliance (China), the director of the (Ministry of Housing and Urban-rural Development) Digital Community Industrialization Center, the vice-chairman of the Liaoning Intelligent Building Expert Committee, the director of China Software Association, vice chairman of Liaoning Provincial Software Association, and member of the National Standardization Technical Committee for Digitalization of Intelligent Buildings and Residential Areas (SAC/TC426). He is currently the director of the New Energy Center of the Chinese Society of Urban Studies. He participated in the compilation of the national standard "Digital Technology Application in Buildings and Residential Areas", acting as the editor-in-chief of the Ministry of Housing and Urban-Rural Development "DCN Control Network Communication Protocol in Residential Areas" CJ/T281-2008 and the Ministry of Housing and Urban-Rural Development "Photovoltaic Microgrid Shared Grid Control Inverter Device". His main works are "Intelligent Building Design, Management and Operation" and "Intelligent Design and Implementation of Residential Quarters".



Researcher-level Senior Engineer Yubo Yuan

Electric Power Research Institute

State Grid Jiangsu Electric Power Co., Ltd.

Yuan Yubo, Senior Engineer, Ph.D., is currently engaged in technical research on relay protection and control of power systems, AC-DC flexible distribution networks, and source-grid-load-storage coordination and control. He is also the convenor of the CIGRE WG B5/D2.67 working group of the International Conference on Large Power Grids.


Prof. Kai Wang, Qingdao University

Prof. Kai Wang graduate from Dalian University of Technology in College of Electrical Engineering. The applicant is employed as a member of the Component Professional Committee of the Chinese Power Supply Society and a member of the Shandong Electronic Ceramics Committee, a distinguished professor of the school, a dean of the electrical engineering department, a core member of the National and Local Joint Engineering Research Center for Intelligent Power Integration Technology of Electric Vehicles (Qingdao), Shandong Deputy Director of Provincial New Energy Automobile Electrical and Electronic Engineering Technology Research Center, Deputy Director of Qingdao Intelligent Electrical Appliances and Intelligent System Engineering Laboratory, and master's supervisor. The first author of the applicant published an academic monograph-supercapacitors and their applications in energy storage systems (Machinery Industry Press, 2019, CIP (2019) No. 276376). Outstanding reviewer of the Proceedings of the Chinese Society of Electrical Engineering and Applied Energy in 2019. The applicant has published more than 20 SCI research papers, which have been cited more than 900 times, and 6 ESI highly cited papers.

Speech Title: Research on life prediction of supercapacitor based on improved long-term and short-term memory neural network

Abstract: Due to the rapid consumption of fossil fuels and environmental problems caused by large amounts of greenhouse gases, people are eagerly seeking green alternative energy sources and energy storage equipment. The development of high-performance energy storage equipment is crucial to the development of environmental friendly society and renewable energy. Because of the high power density, supercapacitors have great potential for development in the energy field and are the core devices in energy storage systems. Therefore, the health status of supercapacitors seriously affects the safe operation of the entire energy storage system, which has aroused great concern.
Long short-term memory neural network optimized based on hybrid genetic algorithm is proposed to predict the remaining useful life of supercapacitors. First, determine the input variables of the deep neural network. By analyzing the structural characteristics between the electrode and the solution, and the characteristics and laws of the movement of internal charges, the energy storage mechanism of the supercapacitor is studied, and the influencing factors of the supercapacitor performance aging are obtained. The input variables of the neural network model are determined according to the influencing factors of the performance aging of the supercapacitor, in order to achieve accurate prediction of the remaining useful life of the supercapacitor. Secondly, two tests are designed to obtain supercapacitor aging data. A large amount of data is the basis of high precision for life prediction, to fully reflect the aging condition of the power supply under different running environment, this paper uses different charge and discharge strategies based on different temperatures and voltages to perform a steady-state cycle life test and Hybrid Pulse Power Characteristic test on the supercapacitors to make the measured data more real and effective.
After determining the input variables of the neural network and obtaining a large amount of experimental data, a prediction model of the long short-term memory neural network optimized based on the hybrid genetic algorithm is constructed. The model uses a hybrid genetic algorithm to automatically find the optimal dropout probability of the neural network and the number of hidden layer units. The hybrid genetic algorithm uses the root mean square error of remaining useful life of the supercapacitor between which predicted by the long short-term memory neural network and the groundtruth as its fitness function. During the optimization process, the genetic algorithm converges to the vicinity of the local optimal solution, the sequential quadratic programming algorithm is utilized for further local search, the dropout probability and the number of hidden layer units are optimized quickly and accurately, and the obtained optimal parameters are input into the long short-term memory neural network to predict the remaining useful life of the supercapacitors.
After the deep learning model is designed, the cycle life prediction experiment is conducted on the aging data of trained and untrained supercapacitors, and compared with other prediction models, the results prove that the prediction model proposed in this paper has higher prediction accuracy and strong generalization ability. In addition, a life prediction experiment of supercapacitors under dynamic test conditions was conducted to further confirm the versatility of the prediction model.


Prof. Jianmin Zhang, Hangzhou Dianzi University

Jianmin Zhang received B.S., M.S. from Huazhong University of Sci.& Tech.(HUST), Wuhan, China, and M.E. from Indian Institute of Technology (ITT, Roorkee), all in electrical engineering, in 1984, 1987, 1992 respectively. He joined Hangzhou Regional Center of Small Hydro Power (HRC) and National Institute of Rural Electrification, Hangzhou, China from 1987 to 1997. He is a full professor of Electrical Engineering and Automation at Hangzhou Dianzi University. His research interests include electric power and energy system modeling, optimal operation and dispatching, intelligence engineering and automation, information system integration, etc.

Speech Title: 61850-based unified physics-cyber-logic-security space modelling for regional energy interconnected power grid
Abstract: Regional energy interconnected power grids (REIG) refer to the smart distribution networks supporting regional energy internet. Carbon reduction through regional energy interconnection and new energy consumption is the fundamental goal of its operation, but the cross-domain cyber- physical attacks, especially the space and time coordination of cyber and physical attacks, have formed a great threat to it.  The current cyber-physical security theory is seriously out of line with the modern electric power automation system based on IEC61850 standard system, lack of unified modeling of the logic space, ignore the ability to suppress cyber and physical attacks by automation system, ignore the essence of cyber security system as one type of the automation system, whole causes the lack serious engineering usability.  To this end, based on the thoughts of IEC61850, static logical cyberspace modeling of unified physics-cyber-logic-security is studied to support a whole domain logic as one map and "fully transparent" intrinsic security early warning system.


Prof. Jinghong Zhou, Changchun Institute of Technology

Prof. Zhou, Ph.D., postdoctoral fellow, Professor of Changchun Institute of Technology, the seventh batch of experts with outstanding contributions in Changchun City, review expert of National key R & D plan "Smart Grid Technology and Equipment" key special evaluation, member of China Electrical Engineering Society Kinetic Energy Special Committee, Northeast Electric Power University part-time master tutor in electrical engineering, the review experts of State Grid Corporation science and technology project. He mainly engaged in production and scientific research in the field of power system planning and power economic analysis.

Speech title: Economic Evaluation Methods for Power System Flexibility Resources
Abstract: Power system flexibility resources are an important part of the future high percentage of the new energy grid. However, the development speed of power system flexibility resources is relatively slow. The main reason is that the economy of power system flexibility resources is poor and the investment in power system flexibility projects is difficult to obtain a reasonable return, or even loss. The report mainly introduces the economic evaluation method and application of power system flexibility.