Open Access

ARTICLE

Stackelberg-Nash Game Based Collaborative Optimal Low-Carbon Scheduling of Multiple Integrated Multi-Energy Systems via Peer-to-Peer Trading

Yang Liu¹, Bo Yang^2,*, Ning Yang³, Shuai Zhou⁴

1 Faculty of Science, Kunming University of Science and Technology, Kunming, China
2 Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming, China
3 Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK
4 Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland, New Zealand

* Corresponding Author: Bo Yang. Email:

(This article belongs to the Special Issue: AI in Green Energy Technologies and Their Applications)

Energy Engineering 2026, 123(11), 1 https://doi.org/10.32604/ee.2026.083523

Received 05 April 2026; Accepted 08 June 2026; Issue published 24 September 2026

Abstract

To tackle the challenges of economic operation and low-carbon transition faced by integrated multi-energy systems (IMES) in the energy transition, this paper proposes a bi-level optimization framework considering electricity, heat, hydrogen, methane and peer-to-peer (P2P) electricity trading. Specifically, the framework constructs a Stackelberg game involving IMES operator (IMESO) and load aggregators (LAs), which aims to maximize IMESO’s revenue and maximize the residual interests of LAs. Meanwhile, a Nash bargaining game is established for cooperation among multiple IMES through peer-to-peer (P2P) electricity trading, with the goals of maximizing the total revenue of the alliance and achieving a fair distribution of revenue. In the optimization process, technologies such as hydrogen blending system (HBS), water electrolysis (EL) for hydrogen production, and carbon capture system (CCS) are fully leveraged, and demand response (DR) mechanism is integrated. Simulation results demonstrate that the proposed method significantly improves the total economic revenue of the system and reduces carbon emissions. Specifically, compared with the operation mode only considering DR without cooperative game, the proposed two-level game model not only achieves 60.31% carbon emission reduction, but also achieves 133.5% increase in total system revenue; compared with the mode only considering cooperative game without DR, it reduces total carbon emissions by 8.00% and increases total revenue by 26.02%.

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Keywords

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