Two-Stage Optimization Scheduling of Multi-Microgrids with Hydrogen-Infused Gas in an Uncertain Environment using Nash Bargaining

In pursuit of carbon peak and carbon neutrality goals, the energy industry is advancing its green and low-carbon transformation through integrated energy systems, forming multi-microgrid systems. These systems facilitate economic viability and electricity exchange among microgrids. However, complexities in stakeholder interactions and multi-energy flows challenge traditional scheduling methods. To address these challenges, this paper presents three key contributions: Integration of Hydrogen-doped Gas Technology: We integrate hydrogen doping technology with carbon capture and power-to-gas technologies in multi-microgrid systems to enhance flexibility and reduce carbon emissions. Conditional Value-at-Risk (CVaR) for Uncertainty Measurement: We introduce a simplified yet accurate approach using net interaction costs to calculate conditional value-at-risk, streamlining uncertainty assessment. Improved ADMM Algorithm for Solving Non-Convex Models: We propose an enhanced Alternating Direction Method of Multipliers (ADMM) algorithm with dynamic adaptive penalty factors to solve the complex Nash negotiation model, improving computational efficiency and solution stability. Through case studies, we validate the effectiveness of these contributions, advancing the optimization of integrated energy multi-microgrids in uncertain and low-carbon conditions.