Clustering distributed energy resources for large-scale demand management

Elth Ogston*, Astrid Zeman, Mikhail Prokopenko, Geoff James

*Corresponding author for this work

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

13 Citations (Scopus)

Abstract

Managing demand for electrical energy allows generation facilities to be run more efficiently. Current systems allow for management between large industrial consumers. There is, however, an increasing trend to decentralize energy resource management and push it to the level of individual households, or even appliances. In this work we investigate the suitability of using adaptive clustering to improve the scalability of decentralized energy resource management systems by appropriately partitioning resources. We review the area of distributed energy resource management and propose a simple yet realistic model to study the problem. Simulations using this model show that straightforward clustering and distributed planning methods allow systems to scale, but may be limited to only a few hundred-thousand appliances. Results indicate that there is an opportunity to apply adaptive clustering techniques in order to discover more advanced grouping criteria that would enable groups to change as appliances' behavior changes. The simulations further suggest that even an extremely limited exchange of information between clusters can greatly improve management solutions.

Original languageEnglish
Title of host publicationFirst International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2007
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages97-106
Number of pages10
ISBN (Print)0769529062, 9780769529066
DOIs
Publication statusPublished - 2007
Externally publishedYes
EventFirst International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2007 - Cambridge, MA, United States
Duration: 9 Jul 200711 Jul 2007

Other

OtherFirst International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2007
CountryUnited States
CityCambridge, MA
Period9/07/0711/07/07

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