Valuing demand response controllability via chance constrained programming

Kenneth Bruninx, Yury Dvorkin, Erik Delarue, William D'haeseleer, Daniel S. Kirschen

Research output: Contribution to journalArticlepeer-review


Controllable loads can modify their electricity consumption in response to signals from a system operator, providing some of the flexibility needed to compensate for the stochasticity of electricity generated from renewable energy sources (RES) and other loads. However, unlike traditional flexibility providers, e.g., conventional generators and energy storage systems, demand response (DR) resources are not fully controlled by the system operator and their availability is limited by user-defined comfort constraints. This paper describes a deterministic unit commitment model with probabilistic reserve constraints that optimizes day-ahead power plant scheduling in the presence of stochastic RES-based electricity generation and DR resources that are only partially controllable, in this case residential electric heating systems. This model is used to evaluate the operating cost savings that can be attained with these DR resources on amodel inspired by the Belgian power system.

Original languageEnglish (US)
Pages (from-to)178-187
Number of pages10
JournalIEEE Transactions on Sustainable Energy
Issue number1
StatePublished - Jan 2018


  • Demand response (DR)
  • Limited controllability
  • Uncertainty
  • Unit commitment

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment


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