Energy and reserve dispatch with distributionally robust joint chance constraints

Christos Ordoudis*, Viet Anh Nguyen, Daniel Kuhn, Pierre Pinson

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

We develop a two-stage stochastic program for energy and reserve dispatch of a joint power and gas system with a high penetration of renewables. Data-driven distributionally robust chance constraints ensure that there is no load shedding and renewable spillage with high probability. We solve this problem efficiently using conditional value-at-risk approximations and linear decision rules. Out-of-sample experiments show that this model dominates the corresponding stochastic program without chance constraints that models the effects of load shedding and renewable spillage explicitly.
Original languageEnglish
JournalOperations Research Letters
Volume49
Issue number3
Pages (from-to)291-299
Number of pages9
ISSN0167-6377
DOIs
Publication statusPublished - 2021

Keywords

  • Distributionally robust optimization
  • Energy and reserve dispatch
  • Joint chance constraints
  • Wasserstein metric

Fingerprint Dive into the research topics of 'Energy and reserve dispatch with distributionally robust joint chance constraints'. Together they form a unique fingerprint.

Cite this