A Bayesian mean field game approach to supply demand analysis of the smart grid

Maryam Kamgarpour, Hamidou Tembine

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

Abstract

We explore a game theoretic framework for multiple energy producers competing in energy market. Each producer, referred to as a player, optimizes its own objective function given the demand utility. The equilibrium strategy of each player depends on the production cost, referred to as type, of the other players. We show that as the number of players increases, the mean of the types is sufficient for finding the equilibrium. For finite number of players, we design a mean field distributed learning algorithm that converges to equilibrium. We discuss extensions of our model to include several realistic aspects of the energy market.

Original languageEnglish (US)
Title of host publication2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013
Pages211-215
Number of pages5
DOIs
StatePublished - Dec 16 2013
Event2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013 - Batumi, Georgia
Duration: Jul 3 2013Jul 5 2013

Publication series

Name2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013

Other

Other2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013
CountryGeorgia
CityBatumi
Period7/3/137/5/13

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Ocean Engineering

Cite this

Kamgarpour, M., & Tembine, H. (2013). A Bayesian mean field game approach to supply demand analysis of the smart grid. In 2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013 (pp. 211-215). [6623412] (2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013). https://doi.org/10.1109/BlackSeaCom.2013.6623412