Sample-Derived Disjunctive Rules for Secure Power System Operation

Jochen L. Cremer, Ioannis Konstantelos, Goran Strbac, Simon H. Tindemans

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

9 Citations (Scopus)
56 Downloads (Pure)


Machine learning techniques have been used in the past using Monte Carlo samples to construct predictors of the dynamic stability of power systems. In this paper we move beyond the task of prediction and propose a comprehensive approach to use predictors, such as Decision Trees (DT), within a standard optimization framework for pre- and post-fault control purposes. In particular, we present a generalizable method for embedding rules derived from DTs in an operation decision-making model. We begin by pointing out the specific challenges entailed when moving from a prediction to a control framework. We proceed with introducing the solution strategy based on generalized disjunctive programming (GDP) as well as a two-step search method for identifying optimal hyper-parameters for balancing cost and control accuracy. We showcase how the proposed approach constructs security proxies that cover multiple contingencies while facing high-dimensional uncertainty with respect to operating conditions with the use of a case study on the IEEE 39-bus system. The method is shown to achieve efficient system control at a marginal increase in system price compared to an oracle model.

Original languageEnglish
Title of host publication2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018
Subtitle of host publicationConference Proceedings
Place of PublicationPiscataway, NJ
Number of pages6
ISBN (Electronic)978-1-5386-3596-4
Publication statusPublished - 2018
EventPMAPS 2018: International Conference on Probabilistic Methods Applied to Power Systems - Boise, ID, United States
Duration: 24 Jun 201828 Jun 2018


ConferencePMAPS 2018
Abbreviated titlePMAPS
Country/TerritoryUnited States
CityBoise, ID

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Decision Tree
  • Disjunctive Rules
  • Power Systems Operation
  • Stability


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