Disaggregated bundle methods for distributed market clearing in power networks

Yu Zhang, Nikolaos Gatsis, Georgios B. Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

A fast distributed approach is developed for the market clearing with large-scale demand response in electric power networks. In addition to conventional supply bids, demand offers from aggregators serving large numbers of residential smart appliances with different energy constraints are incorporated. Leveraging the Lagrangian relaxation based dual decomposition, the resulting optimization problem is decomposed into separate subproblems, and then solved in a distributed fashion by the market operator and each aggregator aided by the end-user smart meters. A disaggregated bundle method is adapted for solving the dual problem with a separable structure. Compared with the conventional dual update algorithms, the proposed approach exhibits faster convergence speed, which results in reduced communication overhead. Numerical results corroborate the effectiveness of the novel approach.

Original languageEnglish (US)
Title of host publication2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
Pages835-838
Number of pages4
DOIs
StatePublished - 2013
Event2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Austin, TX, United States
Duration: Dec 3 2013Dec 5 2013

Publication series

Name2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings

Other

Other2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013
CountryUnited States
CityAustin, TX
Period12/3/1312/5/13

Keywords

  • Aggregators
  • Decomposition algorithms
  • Demand response
  • Disaggregated bundle method
  • Market clearing

Fingerprint Dive into the research topics of 'Disaggregated bundle methods for distributed market clearing in power networks'. Together they form a unique fingerprint.

Cite this