Decentralized peer-to-peer transactive energy management and game-theoretic market operation of an integrated electrical-thermal system in networked multi-carrier microgrids under uncertainty

This study presents a novel decentralized energy management framework for Networked Multi-Carrier Microgrids (NMCMG), addressing critical gaps in privacy-preserving peer-to-peer (P2P) energy trading for multiple energy carriers, including electricity and thermal energy. Unlike conventional centralized approaches, which require extensive data sharing and compromise privacy, the proposed model leverages a two-stage optimization strategy combining the Alternating Direction Method of Multipliers (ADMM) and game theory to ensure secure, scalable, and economically fair energy exchanges among microgrids. The framework focuses on addressing limitations of prior NMCMG energy management systems, particularly in decentralized P2P markets, which often lack consideration for privacy, multiple uncertainties, and fair profit-sharing mechanisms. The first stage employs ADMM to optimize microgrid energy management while preserving operational privacy, eliminating the need for centralized data aggregation and respecting microgrid autonomy. The second stage integrates bargaining game theory to establish dynamic pricing mechanisms in the P2P market, ensuring fair profit distribution based on each microgrid’s contribution, incentivizing active engagement in energy trading. Additionally, robust optimization is applied to handle uncertainties in renewable generation and demand fluctuations, avoiding the computational complexity of probabilistic methods and enhancing real-time applicability. The proposed model not only reduces operational costs but also improves grid stability, reduces carbon emissions, minimizes load shedding, and enhances customer satisfaction. Practical results demonstrate a significant reduction in the total daily cost of microgrids, achieving approximately 13% savings through implementing the proposed innovations. Furthermore, the model exhibits robust stability, maintaining correct energy management even under critical conditions such as microgrid outages. By integrating advanced energy storage and cooperative game theory, this research provides a practical, scalable solution for real-world NMCMG deployment, bridging the gap between theoretical research and industrial implementation.

Authors

Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2026-01-01
DOI
https://doi.org/10.1016/j.ijepes.2025.111546
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Decentralized peer-to-peer transactive energy management and game-theoretic market operation of an integrated electrical-thermal system in networked multi-carrier microgrids under uncertainty

Shahram Jadid, Hamidreza Zareshahi
International Journal of Electrical Power & Energy Systems
Microgrid Control and Optimization
article

Decentralized peer-to-peer transactive energy management and game-theoretic market operation of an integrated electrical-thermal system in networked multi-carrier microgrids under uncertainty

Shahram Jadid, Hamidreza Zareshahi
article en

Abstract

This study presents a novel decentralized energy management framework for Networked Multi-Carrier Microgrids (NMCMG), addressing critical gaps in privacy-preserving peer-to-peer (P2P) energy trading for multiple energy carriers, including electricity and thermal energy. Unlike conventional centralized approaches, which require extensive data sharing and compromise privacy, the proposed model leverages a two-stage optimization strategy combining the Alternating Direction Method of Multipliers (ADMM) and game theory to ensure secure, scalable, and economically fair energy exchanges among microgrids. The framework focuses on addressing limitations of prior NMCMG energy management systems, particularly in decentralized P2P markets, which often lack consideration for privacy, multiple uncertainties, and fair profit-sharing mechanisms. The first stage employs ADMM to optimize microgrid energy management while preserving operational privacy, eliminating the need for centralized data aggregation and respecting microgrid autonomy. The second stage integrates bargaining game theory to establish dynamic pricing mechanisms in the P2P market, ensuring fair profit distribution based on each microgrid’s contribution, incentivizing active engagement in energy trading. Additionally, robust optimization is applied to handle uncertainties in renewable generation and demand fluctuations, avoiding the computational complexity of probabilistic methods and enhancing real-time applicability. The proposed model not only reduces operational costs but also improves grid stability, reduces carbon emissions, minimizes load shedding, and enhances customer satisfaction. Practical results demonstrate a significant reduction in the total daily cost of microgrids, achieving approximately 13% savings through implementing the proposed innovations. Furthermore, the model exhibits robust stability, maintaining correct energy management even under critical conditions such as microgrid outages. By integrating advanced energy storage and cooperative game theory, this research provides a practical, scalable solution for real-world NMCMG deployment, bridging the gap between theoretical research and industrial implementation.

International Journal of Electrical Power & Energy SystemsVol. 174
Affordable and clean energy
Openalex Percentile: Top 95%
Microgrid Control and Optimization
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