### 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 language | English (US) |
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Title of host publication | 2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013 |

Pages | 211-215 |

Number of pages | 5 |

DOIs | |

State | Published - Dec 16 2013 |

Event | 2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013 - Batumi, Georgia Duration: Jul 3 2013 → Jul 5 2013 |

### Other

Other | 2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013 |
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Country | Georgia |

City | Batumi |

Period | 7/3/13 → 7/5/13 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Networks and Communications
- Ocean Engineering

### Cite this

*2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013*(pp. 211-215). [6623412] https://doi.org/10.1109/BlackSeaCom.2013.6623412

**A Bayesian mean field game approach to supply demand analysis of the smart grid.** / Kamgarpour, Maryam; Hamidou, Tembine.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013.*, 6623412, pp. 211-215, 2013 1st International Black Sea Conference on Communications and Networking, BlackSeaCom 2013, Batumi, Georgia, 7/3/13. https://doi.org/10.1109/BlackSeaCom.2013.6623412

}

TY - GEN

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

AU - Kamgarpour, Maryam

AU - Hamidou, Tembine

PY - 2013/12/16

Y1 - 2013/12/16

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.

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.

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

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

U2 - 10.1109/BlackSeaCom.2013.6623412

DO - 10.1109/BlackSeaCom.2013.6623412

M3 - Conference contribution

AN - SCOPUS:84890072005

SN - 9781479908578

SP - 211

EP - 215

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

ER -