Icon for: Mark Wagy

MARK WAGY

University of Vermont
Years in Grad School: 1
Judges’ Queries and Presenter’s Replies
  • Icon for: Ananth Iyer

    Ananth Iyer

    Judge
    Faculty: Project Co-PI
    May 20, 2013 | 12:56 p.m.

    Does this model also permit contingent actions (such as reacting to failures by shutting off power demand points) to be included in assessing risk ?

  • Icon for: Mark Wagy

    Mark Wagy

    Lead Presenter
    May 21, 2013 | 07:05 p.m.

    The model allows for that type of contingent action to be simulated, however we are not yet incorporating it into our risk statistic.

  • Icon for: Paulette Clancy

    Paulette Clancy

    Judge
    Faculty: Project Co-PI
    May 20, 2013 | 09:14 p.m.

    Why did you choose the Random Chemistry Model over other possible representations? What particular characteristics of this model were seen as especially relevant for modeling cascading blackouts?

  • Icon for: Mark Wagy

    Mark Wagy

    Lead Presenter
    May 21, 2013 | 07:05 p.m.

    Random Chemistry is an algorithm that allows us to more quickly find branch outages that might result in a cascading blackout. So Random Chemistry is not the model of the cascading blackouts, but rather an algorithm that we can use to quickly find branch combinations that might cause cascades. We use Random Chemistry because it is a method of finding these branch combinations more quickly than other methods.

  • Icon for: Ranjit Koodali

    Ranjit Koodali

    Judge
    Faculty: Project Co-PI
    May 21, 2013 | 06:53 p.m.

    Can this model be used to predict brownouts?

  • Icon for: Mark Wagy

    Mark Wagy

    Lead Presenter
    May 21, 2013 | 07:05 p.m.

    My understanding is that brownouts are intentional, human-initiated outage events; as such, this model might not be an appropriate tool to use in their prediction.

  • Icon for: Ranjit Koodali

    Ranjit Koodali

    Judge
    Faculty: Project Co-PI
    May 22, 2013 | 08:18 a.m.

    Thanks!

  • Icon for: Ian Harrison

    Ian Harrison

    Judge
    Faculty: Project PI
    May 21, 2013 | 09:44 p.m.

    What algorithm is currently used by grid operators to prioritize repair of potentially malignant branch outages given the new NERC guidelines for n-k contingency testing? Could you explain the particular advantages of your algorithm? (I’m assuming the current NERC suggested method is not brute force computing…)

  • Icon for: Mark Wagy

    Mark Wagy

    Lead Presenter
    May 21, 2013 | 11:22 p.m.

    Just as a clarification: the Random Chemistry algorithm was developed by Maggie Eppstein (indicated in the poster reference), which was inspired by the concept of Random Chemistry by Stuart Kauffman – I am not claiming it to be my own.

    In answer to your questions, I believe that the grid operators do perform brute-force testing for n-1 testing since it is feasible to do that many simulations (for n-1, they are not burdened by the combinatorial search space) and then focus on testing a small subset of the n-k outage scenarios for k greater than one (though this is with the intent not necessarily to repair outages but rather to adjust load to prevent possible cascading outages). To my knowledge, full n-k testing is not currently performed to characterize all malignancies for k>1. The Random Chemistry algorithm makes the discovery of n-k outages (particularly for k values of, say, 2 and 3) feasible in a shorter number of simulation evaluations than using either brute force or Monte Carlo-based methods for finding possible malignant subsets.

  • Icon for: Ian Harrison

    Ian Harrison

    Judge
    Faculty: Project PI
    May 22, 2013 | 09:39 p.m.

    Thanks, this does seem to be computationally interesting problem.

  • Icon for: Matthew Yates

    Matthew Yates

    Judge
    Faculty: Project Co-PI
    May 21, 2013 | 10:59 p.m.

    Can you explain some of the actions a grid operator may take based on your results?

  • Icon for: Mark Wagy

    Mark Wagy

    Lead Presenter
    May 22, 2013 | 09:21 a.m.

    A grid operator might, for example, adjust the dispatch of generators in response to a high risk characterization of the grid to a state of lower risk to cascading blackouts.

Presentation Discussion
  • Icon for: Paul Hines

    Paul Hines

    Faculty: Project Co-PI
    May 21, 2013 | 06:53 a.m.

    Excellent use of animation to illustrate the operation of this algorithm.

  • Icon for: Margaret (Maggie) Eppstein

    Margaret (Maggie) Eppstein

    Faculty: Project Co-PI
    May 21, 2013 | 11:16 a.m.

    Very clear explanations of this important problem and illustration of your approach to solving it.

  • Further posting is closed as the event has ended.