Loi Lei Lai
Guangdong University of Technology, Guangzhou, China
Smart Grid for Smart Cities – A Decision Support System with consideration of Natural Disaster
Abstract: As a result of information
technology advancement and its deep integration with the electric power
industry, smart grid forms a solid foundation to build smart city. Meanwhile,
the construction of smart city will also greatly stimulate the enormous
potential of smart grid. City managers must be fully aware of the potential of
the smart grid, so that the smart urban construction can play an important role.
It is expected that with the continuous advancement of technology, smart grid
and smart city construction will mutually promote and facilitate each other.
Current system defensive method estimates failure risk based on online operation conditions. Preventive control and emergency control measurements need to be stipulated to deal with those failures with high risk and ensure the system can operate steadily after fault clearance. However, the anticipated faults in the current risk assessment are in accordance with fixed average failure rate obtained by off-line historical data statistical analysis. Power system malfunctions are mainly from component defect, manual mistake, unreasonable operation mode and natural disasters. The first three factors have fixed failure rate and can be obtained by off-line historical data statistical analysis. Natural disasters have prominent spatial and temporal distribution features. Using fixed rate can cause large statistical error.
The selection of data mining technology to analyze the mass amount of data from smart grid to support decision-making for the government to effectively reduce operating costs and improve operational efficiency of smart city will be one of the big issues. Data exchange platform gathers all information from EMS, weather forecasting, wildfire monitoring, icing monitoring and lighting orientation monitoring systems, and send the information to data integration module. After data integration, preprocessing and checking, the processed data is send to analyzing and warning module and control and decision-making module for assessment. Finally, the result will be shown in environment and power network information display module. Some initial results will be discussed. Sources of Big Data in Smart Grid will be considered. Different methods for data analytics will be investigated.
Bio: Professor Loi Lei Lai received
the BSc (first class Hons., the only one) degree in electrical and electronic
engineering and the PhD degree in electrical and electronic engineering from the
University of Aston, Birmingham, UK in 1980 and 1984 respectively, and the DSc
degree in electrical, electronic, and information engineering from City,
University of London, UK in 2005.
Currently, he is University Distinguished Professor at the Guangdong University of Technology, Guangzhou, China. He was Director of the Research and Development Centre, Beijing, China, the Pao Yue Kong Chair Professor, Guest Professor, the Vice President and Professor and Chair in Electrical Engineering for the State Grid Energy Research Institute, Beijing, China; Zhejiang University, Hangzhou, China; Fudan University, Shanghai, China; IEEE Systems, Man, and Cybernetics Society (IEEE/SMCS), USA; and City, University of London, respectively. He conducted high-level consultancy for major international projects such as the Channel Tunnel between UK and France. His research interests are in smart grid, clean energy, and computational intelligence applications in power engineering. Dr Lai is a Fellow of IEEE, IET, Distinguished Expert in State Grid Corporation of China, National Distinguished Expert in China, Member of IEEE Smart Grid Steering Committee, Member of IEEE Smart City Steering Committee and IEEE Industrial Electronics Society Fellow Evaluation Committee evaluator. He was the recipient of an IEEE Third Millennium Medal, IEEE Power and Energy Society (IEEE/PES) Power Chapter Outstanding Engineer Award in 2000, IEEE/PES Energy Development and Power Generation Committee Prize Paper in 2006 and 2009, People of the 2012 Scientific Chinese Prize, IEEE/SMCS Outstanding Contribution Award in 2013 and 2014, and is listed in the honor list of the 2014 the Thousand Talents Plan, China.