Shu Zhen has 5 years of research experience in power systems. She received her B.Eng. Degree in Electronics and Information Engineering from Huazhong University of Science and Technology, China, and M.S. and Ph.D degrees in Electrical and Computer Engineering from National University of Singapore, in 2006, 2009 and 2014, respectively. Her areas of expertise include power system reliability, Monte Carlo simulation techniques, machine learning, and optimization for power system problems including planning, operation, renewable integration and energy storages. She has been working on the similar areas in R&D team of DNV GL since May 2014.
Presentation Title
Power System Reliability Assessment Considering Bus Load Correlation and Extreme Events
Abstract
This paper proposes a simulation approach based on accelerated state evaluation (ASE) for power system reliability analysis. This approach is developed for systems with various bus-load patterns including extreme cases. Its performance is demonstrated through case studies on IEEE Reliability Test System, where reliability indices – loss of load probability, expected unserved energy, loss of load frequency and duration are achieved. Compared to conventional approach, this approach achieves much higher computing efficiency while providing solutions of similar quality. It can serve as a very useful tool for generation and transmission system analysis, especially for systems of high complexities and large sizes.