Real-time electricity pricing for demand response using online convex optimization

Seung Jun Kim, Georgios B Giannakis

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

14 Scopus citations

Abstract

Real-time electricity pricing strategies for demand response in smart grids are proposed. By accounting for individual consumers' responsiveness to prices, adjustments are made so as to induce desirable usage behavior and reduce peaks in load curves. An online convex optimization framework is adopted, which provides performance guarantees with minimal assumptions on the dynamics of load levels and consumer responsiveness. Two feedback structures are considered: a full information setup, where aggregate load levels as well as individual price elasticity parameters are directly available; and a partial information (bandit) case, where only the load levels are revealed. Fairness and sparsity constraints are also incorporated. Numerical tests verify the effectiveness of the proposed approach.

Original languageEnglish (US)
Title of host publication2014 IEEE PES Innovative Smart Grid Technologies Conference, ISGT 2014
PublisherIEEE Computer Society
ISBN (Print)9781479936526
DOIs
StatePublished - Jan 1 2014
Event2014 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2014 - Washington, DC, United States
Duration: Feb 19 2014Feb 22 2014

Other

Other2014 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2014
CountryUnited States
CityWashington, DC
Period2/19/142/22/14

Fingerprint Dive into the research topics of 'Real-time electricity pricing for demand response using online convex optimization'. Together they form a unique fingerprint.

Cite this