Stochastic scheduling of generating units with weekly energy storage: A hybrid decomposition approach

Gonzalo E. Constante-Flores, Antonio J. Conejo, Ricardo Lima

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


We propose a solution method for the large-scale stochastic unit commitment (SUC) problem with weekly-dispatched energy storage and significant weather-dependent stochastic generating capacity. Weekly storage facilities that mostly charge during weekends and discharge during weekdays require a weekly scheduling of generating units, which result in a large-scale optimization problem. This SUC problem is formulated as a two-stage stochastic model and we use the conditional value-at-risk as a risk measure. Using a Benders framework, the proposed solution method decomposes the problem into a mixed-integer linear master problem and linear and continuous subproblems. The master problem corresponds to the first-stage decisions throughout the week and includes all the commitment (binary) variables and their corresponding constraints. The subproblems correspond to the actual dispatch of the generating units on a weekly basis. Based on the success of column-and-constraint generation algorithms to solve robust optimization problems, we improve the low communication between the master problem and the subproblems in the standard Benders decomposition by adding primal variables and constraints from the subproblems to the master problem, which provides a better approximation of the recourse function. Our computational experiments demonstrate the effectiveness of the proposed decomposition method using an instance of the South Carolina synthetic system with 90 generating units under 40 scenarios.
Original languageEnglish (US)
Pages (from-to)108613
JournalInternational Journal of Electrical Power and Energy Systems
StatePublished - Oct 18 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-10-31
Acknowledged KAUST grant number(s): KI-ORA-2021-4926
Acknowledgements: The work reported in this paper has been partly supported by the Advanced Research Projects Agency-Energy (ARPA-E), USA, U.S. Department of Energy, under Award 2171-1618 (first and second coauthors). This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) under Award No. KI-ORA-2021-4926 (third coauthor).

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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