Topic: Graph Database and Graph Computing for Power System Analysis
Presented by: Renchang Dai, PhD, Puget Sound Energy
This webinar:
The worldwide accelerating decarbonization of energy systems requires a rising penetration of renewable energy, distributed energy, and energy storage, making the power system ever large and more complex. To make the large, complex, and dynamic power system secure and cost-effective, accurate and fast analysis are crucial. To address the increasing needs for computational efficiency in both steady-state and dynamic power system analyses, we have developed an innovative graph computing technology based on a graph database, which will be presented in this webinar. This graph-based approach closely aligns with the nature of power systems, as the graph data structure inherently represents the power network’s topology and the connectivity of its components. In this webinar, we will deep dive into the concept and methodology of graph nodal and hierarchical parallelism. Additionally, we will explore how graph computing technologies can be effectively applied to power system analysis, including steady-state analysis, transient simulation, and operation optimization.
Presenter Bio:
Renchang Dai, PhD, is a Consulting Engineer and Project Manager at Puget Sound Energy. He received his Ph.D. degree in Electrical Engineering from Tsinghua University, China, in 2001. Dr. Dai has worked on a variety of power system problems, including power system planning, operations, and control. He was a Principal Engineer and Group Manager for Global Energy Interconnection Research Institute North America, where he led a team of engineers in researching and developing graph database and graph computing technologies for power system planning and operations. Dr. Dai was a team leader for GE Energy. In GE Energy, he designed, developed, and implemented Energy Management System. He was also a founding member of the GE Energy Consulting Smart Grid Center of Excellence, where he consulted on smart grid deployment and renewable energy grid integration projects. In 2005, when he was a lead scientist in GE Global Research, he was awarded the GE Global Technical Award for his contributions to the development of wind turbine generator fault ride-through technology. Dr. Dai is a Senior Member of the IEEE.