A probability theory based price determination framework for utility companies in an oligopolistic energy market

Tiansong Cui, Yanzhi Wang, Xue Lin, Shahin Nazarian, Massoud Pedram

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

Abstract

Distributed power generation and distribution network with the dynamic pricing scheme are the major trend of the future smart grid. A smart grid is a network which contains multiple non-cooperative utility companies that offer time-of-use dependent energy prices to energy consumers and aim to maximize their own profits. Decentralized power network allows each energy consumer to have multiple choices among different utility companies. In this paper, an optimization framework is introduced to determine the energy price for utility companies in an oligopolistic energy market. At the beginning of each billing period (a day), each utility company will announce the time-of-use dependent pricing policy during the billing period, and each energy consumer will subsequently choose a utility company for energy supply to minimize the expected energy cost. The energy pricing competition among utility companies forms an n-person game because the pricing strategy of each utility company will affect the profits of others. To be realistic, the prediction error of a user's energy consumption is properly accounted for in this paper and is assumed to satisfy certain probability distribution at each time slot. We start from the most commonly-used normal distribution and extend our optimization framework to a more general case. A Nash equilibrium-based pricing policy is presented for the utility companies and the uniqueness of Nash equilibrium is proved. Experimental results show the effectiveness of our game theoretic price determination framework.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 6th Annual IEEE Green Technologies Conference, GREENTECH 2014
PublisherIEEE Computer Society
Pages106-111
Number of pages6
ISBN (Print)9781479939336
DOIs
StatePublished - Jan 1 2014
Event2014 6th Annual IEEE Green Technologies Conference, GREENTECH 2014 - Corpus Christi, TX, United States
Duration: Apr 3 2014Apr 4 2014

Publication series

NameIEEE Green Technologies Conference
ISSN (Electronic)2166-5478

Other

Other2014 6th Annual IEEE Green Technologies Conference, GREENTECH 2014
CountryUnited States
CityCorpus Christi, TX
Period4/3/144/4/14

Keywords

  • dynamic pricing
  • oligopolistic market
  • probability theory
  • smart grid

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Ecological Modeling
  • Environmental Engineering

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  • Cite this

    Cui, T., Wang, Y., Lin, X., Nazarian, S., & Pedram, M. (2014). A probability theory based price determination framework for utility companies in an oligopolistic energy market. In Proceedings - 2014 6th Annual IEEE Green Technologies Conference, GREENTECH 2014 (pp. 106-111). [6824633] (IEEE Green Technologies Conference). IEEE Computer Society. https://doi.org/10.1109/GREENTECH.2014.11