Distributed decision-making in a shared power network: a game-theoretic framework for integrated electricity and gas...

Area of Science:

• Energy Systems Engineering
• Game Theory
• Computational Economics

Background:

• Advancements in power-to-gas (P2G) and local energy markets offer new value for small-scale gas distributors (GDs).
• Limited research exists on multiple GDs collaborating within a single power network in local energy markets, risking inefficiency and imbalance.

Purpose of the Study:

• To develop a novel heterogeneous game framework for coordinating multiple GDs in integrated power and gas markets.
• To address the challenges of optimal power flow (OPF) coordination and gas pipeline flow control simultaneously.
• To ensure market fairness and operational stability among participating GDs.

Main Methods:

• Integration of a mixed-integer Nash equilibrium problem (MI-NEP) for pipeline flow control and a generalized Nash equilibrium problem (GNEP) for OPF coordination.
• Development of a collaborative computing solution using the best response (BR) method and a Korpelevich-inspired algorithm.
• Analysis of integrated power and gas networks through comprehensive case studies.

Main Results:

• The proposed algorithm converges within 10 iterations with a residual error below [Formula: see text].
• Demonstrated effective coordination for multiple GDs in a 10-node power network coupled with 7-node and 20-node gas networks.
• Achieved market fairness by eliminating cost disparities among similar agents.

Conclusions:

• The heterogeneous game framework successfully enables efficient and fair collaboration among multiple small-scale GDs in local energy markets.
• The developed computational solution provides stable and reliable Nash equilibrium solutions for integrated energy systems.
• This research bridges a critical gap in understanding multi-agent coordination within interconnected power and gas distribution systems.