Robust-Nash Optimization Method for Multi-Energy Sharing in Wide-Area Integrated Energy Systems Based on Asymmetric Bargaining

• • The WAIES cooperative operation reduced total system cost by 6.58% and carbon trading cost by 1.64% compared to independent operation, while achieving 100% renewable energy consumption. This demonstrates that cross-regional multi-energy sharing can simultaneously improve economic and environmental performance, a critical finding for scaling low-carbon energy networks. • • The asymmetric Nash bargaining model allocates profits proportional to each entity's contribution, with a deliberate bias toward energy suppliers. This design addresses fairness concerns in cooperative games, potentially increasing participation incentives and long-term stability of multi-energy sharing alliances. • • The two-stage robust-Nash optimization method, solved via ADMM and C&CG, ensures reliable decision-making under source-load uncertainty. Out-of-sample validation confirms its strategy adaptability, making it suitable for real-world deployment where renewable generation and demand forecasts are imperfect. • • The framework's scalability to large-scale interconnected energy systems is constrained by potential non-convexity in the bargaining function as the number of members increases, which could lead to negotiation infeasibility. This identifies a key research gap for extending the approach to urban or industrial-scale applications.