Online optimization for the smart (micro) grid

Balakrishnan Narayanaswamy*, Vikas K. Garg, T. S. Jayram

*Corresponding author for this work

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

39 Citations (Scopus)

Abstract

Growing environmental awareness and new government directives have set the stage for an increase in the fraction of energy supplied using renewable resources. The fast variation in renewable power, coupled with uncertainty in availability, emphasizes the need for algorithms for intelligent online generation scheduling. These algorithms should allow us to compensate for the renewable resource when it is not available and should also account for physical generator constraints. We apply and extend recent work in the field of online optimization to the scheduling of generators in smart (micro) grids and derive bounds on the performance of asymptotically good algorithms in terms of the generator parameters. We also design online algorithms that intelligently leverage available information about the future, such as predictions of wind intensity, and show that they can be used to guarantee near optimal performance under mild assumptions. This allows us to quantify the benefits of resources spent on prediction technologies and different generation sources in the smart grid. Finally, we empirically show how both classes of online algorithms, (with or without the predictions of future availability) significantly outperform certain 'natural' algorithms.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Future Energy Systems
Subtitle of host publication"Where Energy, Computing and Communication Meet", e-Energy 2012
DOIs
Publication statusPublished - 2012
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Future Energy Systems - Madrid, Spain
Duration: 9 May 201211 May 2012
Conference number: 3

Conference

ConferenceInternational Conference on Future Energy Systems
Abbreviated titlee-Energy
Country/TerritorySpain
CityMadrid
Period09/05/201211/05/2012

Keywords

  • Economic dispatch
  • Intelligent generator scheduling
  • Online convex optimization (OCO)
  • Online gradient decent
  • Regret

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