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

Handle URI:
http://hdl.handle.net/10754/575814
Title:
A Bayesian mean field game approach to supply demand analysis of the smart grid
Authors:
Kamgarpour, Maryam; Tembine, Hamidou
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. © 2013 IEEE.
KAUST Department:
Center for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom)
Conference/Event name:
2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013
Issue Date:
Jul-2013
DOI:
10.1109/BlackSeaCom.2013.6623412
Type:
Conference Paper
ISBN:
9781479908578
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorKamgarpour, Maryamen
dc.contributor.authorTembine, Hamidouen
dc.date.accessioned2015-08-24T09:26:56Zen
dc.date.available2015-08-24T09:26:56Zen
dc.date.issued2013-07en
dc.identifier.isbn9781479908578en
dc.identifier.doi10.1109/BlackSeaCom.2013.6623412en
dc.identifier.urihttp://hdl.handle.net/10754/575814en
dc.description.abstractWe 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. © 2013 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleA Bayesian mean field game approach to supply demand analysis of the smart griden
dc.typeConference Paperen
dc.contributor.departmentCenter for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom)en
dc.conference.date3 July 2013 through 5 July 2013en
dc.conference.name2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013en
dc.conference.locationBatumien
dc.contributor.institutionAutomatic Control Laboratory, Swiss Federal Institute of Technology, Switzerlanden
kaust.authorTembine, Hamidouen
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