TY - GEN

T1 - A Bayesian mean field game approach to supply demand analysis of the smart grid

AU - Kamgarpour, Maryam

AU - Tembine, Hamidou

N1 - KAUST Repository Item: Exported on 2020-10-01

PY - 2013/7

Y1 - 2013/7

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10754/575814

UR - http://ieeexplore.ieee.org/document/6623412/

UR - http://www.scopus.com/inward/record.url?scp=84890072005&partnerID=8YFLogxK

U2 - 10.1109/BlackSeaCom.2013.6623412

DO - 10.1109/BlackSeaCom.2013.6623412

M3 - Conference contribution

SN - 9781479908578

SP - 211

EP - 215

BT - 2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -