Adaptive control of distributed energy management: A comparative study

Astrid Zeman*, Mikhail Prokopenko, Ying Guo, Rongxin Li

*Corresponding author for this work

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

11 Citations (Scopus)

Abstract

Demand-side management is a technology for managing electricity demand at the point of use. Enabling devices to plan, manage and reduce their electricity consumption can relieve the network during peak demand periods. We look at a reinforcement learning approach to set a quota of electricity consumption for a network of devices. This strategy is compared with homeotaxis - a method which achieves coordination through minimising the persistent time-loop error. These policies are analysed with increasing levels of noise to represent loss of communication or interruption of device operability. Whilst the policy trained using reinforcement learning proves to be most successful in reducing cost, the homeotaxis method is more successful in reducing stress on devices and increasing stability.

Original languageEnglish
Title of host publicationProceedings - 2nd IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2008
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages84-93
Number of pages10
ISBN (Print)9780769534046
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2nd IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2008 - Venice, Italy
Duration: 20 Oct 200824 Oct 2008

Other

Other2nd IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2008
CountryItaly
CityVenice
Period20/10/0824/10/08

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