  This paper presents a carbon-energy coupling management framework for an
industrial park, where the carbon flow model accompanying multi-energy flows is
adopted to track and suppress carbon emissions on the user side. To deal with
the quadratic constraint of gas flows, a bound tightening algorithm for
constraints relaxation is adopted. The synergies among the carbon capture,
energy storage, power-to-gas further consume renewable energy and reduce carbon
emissions. Aiming at carbon emissions disparities and supply-demand imbalances,
this paper proposes a carbon trading ladder reward and punishment mechanism and
an energy trading and scheduling method based on Lyapunov optimization and
matching game to maximize the long-term benefits of each industrial cluster
without knowing the prior information of random variables. Case studies show
that our proposed trading method can reduce overall costs and carbon emissions
while relieving energy pressure, which is important for Environmental, Social
and Governance (ESG).
