Customized Retail Pricing Scheme Design with a Hybrid Data-driven Method

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Rapid growth of smart metering data in smart grids provides great opportunities for the retailer to design customized price schemes and demand side management (DSM) programs for different customer groups. This paper proposes a hybrid data-driven method of clustering customers' daily load profiles and optimizing different electricity retail plan recommendations for electricity retailers. By combing the user-side information with the risk-aware decision-making framework, specifically using conditional value-at-risk (CVaR) modeling method, the retailer could guarantee its accumulated revenue without doing any harm to the customers' benefit, while guiding their energy consumption behavior instead. Through large-scale experiments, it is observed that a slight increase in the customers' possible payment would be compensated by their big gain in more demand response opportunities. The retailers' profit could also be increased by roughly 49%-51% and 33%-38% with or without enabling demand response programs.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE Sustainable Power and Energy Conference
Subtitle of host publicationEnergy Transition for Carbon Neutrality, iSPEC 2021
Number of pages5
ISBN (Electronic)9781665414395
Publication statusPublished - 2021
Publication typeA4 Article in conference proceedings
EventIEEE Sustainable Power and Energy Conference - Nanjing, China
Duration: 22 Dec 202124 Dec 2021


ConferenceIEEE Sustainable Power and Energy Conference


  • automatic meter reading
  • dynamic pricing
  • electricity retail market

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Energy Engineering and Power Technology


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