Tri‐layer low‐carbon distributed optimization of integrated energy systems based on hybrid games under stochastic scenarios

Abstract

The low‐carbon development of integrated energy systems is achieved via the sharing of multiple energy interactions by park‐level IES (PIES).However, coordinating profit distribution conflicts among complex interactive stakeholders in stochastic scenarios is challenging. Accordingly, this study proposes a novel tri‐layer framework that aggregates different game mechanisms to investigate the interactions between PIESs and coupled energy markets. First, a linkage trading mechanism is proposed by integrating carbon emissions trading and green certificate trading, which establishes a coupled electricity‐carbon‐green certificate market. Consequently, a park aggregation operator acts as an intermediary between PIESs and the coupled market, setting upper‐level purchase and sale prices to guide unit generation in each PIES using the Stackelberg game theory. Subsequently, the Nash game theory is applied to realize cooperative bargaining among PIESs for a fair revenue distribution. Further, the impact of uncertain environments is considered by utilizing stochastic scenario methods and the conditional value‐at‐risk theory. To protect the privacy of each participating agent while improving the convergence speed, a differential evolutionary method is combined with analysis target cascading to solve the framework. Finally, the proposed scheduling method is validated by utilizing a typical case to optimize conflicting PIES interests in multiple scenarios and realize decarbonisation.