Cascaded column generation for scalable predictive demand side management

Hermen Toersche, Albert Molderink, Johann L. Hurink, Gerardus Johannes Maria Smit

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)
53 Downloads (Pure)


We propose a nested Dantzig-Wolfe decomposition, combined with dynamic programming, for the distributed scheduling of a large heterogeneous fleet of residential appliances with nonlinear behavior. A cascaded column generation approach gives a scalable optimization strategy, provided that the problem has a suitable structure. The presented approach extends the TRIANA smart grid framework for predictive demand side management; the main goal of this framework is peak shaving. Simulations validate that the approach is effective, but also show that the performance degrades for smaller group sizes.
Original languageUndefined
Title of host publicationProceedings of the 2014 IEEE International Energy Conference (ENERGYCON)
Place of PublicationUSA
Number of pages8
ISBN (Print)978-1-4799-2449-3
Publication statusPublished - 16 May 2014
Event2014 IEEE International Energy Conference, ENERGYCON 2014 - Hotel Croatia, Cavtat, Croatia
Duration: 13 May 201416 May 2014

Publication series

PublisherIEEE Power & Energy Society


Conference2014 IEEE International Energy Conference, ENERGYCON 2014
Abbreviated titleENERGYCON


  • Smart Grids
  • Power system management
  • Optimization
  • EWI-24897
  • Home appliances
  • Energy management
  • METIS-305939
  • Vectors
  • Electricity
  • IR-91537
  • Context
  • Mathematical Programming
  • Equations

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