VIRTUAL: Graduate Seminar with Kai Zhou: A Markovian Influence Graph Formed From Utility Line Outage Data To Mitigate Large Cascades

When

March 17, 2021    
1:10 pm - 2:00 pm

Event Type

This event will be held virtually.

Speaker: Kai Zhou, ECpE Graduate Student

Advisors: Ian Dobson and Zhaoyu Wang

Title: A Markovian Influence Graph Formed From Utility Line Outage Data To Mitigate Large Cascades

Abstract: A Markovian influence graph formed from observed transmission line outage data describes the probabilities of transitions between generations of cascading line outages. Each generation of a cascade consists of a single line outage or multiple line outages. The new influence graph defines a Markov chain and generalizes previous influence graphs by including multiple line outages as Markov chain states. The generalized influence graph can reproduce the distribution of cascade size in the utility data. In particular, it can estimate the probabilities of small, medium and large cascades. The influence graph has the key advantage of allowing the effect of mitigations to be analyzed and readily tested, which is not available from the observed data. The asymptotic properties of the Markov chain implies the lines most involved in large cascades and show how upgrades to these critical lines can reduce the probability of large cascades.

Bio: Kai Zhou is currently a PhD student in the Electrical Engineering department at Iowa State University. He works under the joint supervision of Prof. Ian Dobson and Prof. Zhaoyu Wang. His research focuses on cascading outages in power systems.

Webex Link: https://iastate.webex.com/iastate/j.php?MTID=m0ef71df961c060fea6a6af57a1d38539

Webinar Recording: https://iastate.webex.com/iastate/ldr.php?RCID=3f5224b578a54b79bda9c17a629929ff

Loading...