Proceedings of the 2017 International Conference on Manufacturing Engineering and Intelligent Materials (ICMEIM 2017)

The Analysis of Bilateral Bidding Model of Electricity Market Based on Bayesian Nash Equilibrium

Authors
Yan-hong Li
Corresponding Author
Yan-hong Li
Available Online February 2017.
DOI
10.2991/icmeim-17.2017.82How to use a DOI?
Keywords
Bayesian Nash Equilibrium; Electricity Market; Bilateral Bidding Model
Abstract

This paper, based on the incomplete information game theory, analyzes the direct bilateral bidding transactions between electric power generator and electric power consumer. Then, we analyze the existence of the Bayesian Nash equilibrium solutions. The analysis result manifests that it is of obvious benefits for the electric power producer to use game theory to guide their bidding strategies. And this article can also provide some policy guidance for China's electricity market reforms.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Manufacturing Engineering and Intelligent Materials (ICMEIM 2017)
Series
Advances in Engineering Research
Publication Date
February 2017
ISBN
10.2991/icmeim-17.2017.82
ISSN
2352-5401
DOI
10.2991/icmeim-17.2017.82How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yan-hong Li
PY  - 2017/02
DA  - 2017/02
TI  - The Analysis of Bilateral Bidding Model of Electricity Market Based on Bayesian Nash Equilibrium
BT  - Proceedings of the 2017 International Conference on Manufacturing Engineering and Intelligent Materials (ICMEIM 2017)
PB  - Atlantis Press
SP  - 482
EP  - 486
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmeim-17.2017.82
DO  - 10.2991/icmeim-17.2017.82
ID  - Li2017/02
ER  -