Energy efficiency via incentive design and utility learning

Lillian Ratliff, Roy Dong, Henrik Ohlsson, S. Shankar Sastry

Research output: Contribution to conferencePaperpeer-review

Abstract

Utility companies have many motivations for modifying energy consumption patterns of consumers such as revenue decoupling and demand response programs. We model the utility company-consumer interaction as a principal-agent problem and present an iterative algorithm for designing incentives while estimating the consumer's utility function. Copyright is held by the author/owner(s).

Original languageEnglish (US)
Pages57-58
Number of pages2
DOIs
StatePublished - 2014
Externally publishedYes
Event2014 3rd ACM International Conference on High Confidence Networked Systems, HiCoNS 2014, Part of CPSWeek 2014 - Berlin, Germany
Duration: Apr 15 2014Apr 17 2014

Other

Other2014 3rd ACM International Conference on High Confidence Networked Systems, HiCoNS 2014, Part of CPSWeek 2014
CountryGermany
CityBerlin
Period4/15/144/17/14

Keywords

  • Energy disaggregation
  • Game theory
  • Incentive design
  • Utility learning

ASJC Scopus subject areas

  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Energy efficiency via incentive design and utility learning'. Together they form a unique fingerprint.

Cite this