Low-carbon optimal scheduling of integrated energy systems incorporating V2G and ice-storage air conditioning

Abstract

With the penetration of high-proportion wind power in integrated energy systems (IESs), demand-side flexibility resources need further exploration. This paper proposes a low-carbon optimal scheduling method incorporating ice-storage air conditioning and vehicle-to-grid (V2G) interaction of electric vehicles (EVs) and hydrogen vehicles (HVs). First, the operational mechanisms of system components are analyzed, and an IES framework is established. The Monte Carlo method is employed to sample the travel behaviors of 1000 EVs and 50 HVs based on specific probability distributions, generating aggregated charge-discharge boundary profiles, and incentive costs are introduced to utilize vehicle scheduling potential. A low-carbon economic scheduling model minimizing total operating costs is then constructed with tiered carbon trading and solved using the Gurobi optimizer. Simulation results show that the proposed system effectively integrates wind power, significantly reduces carbon emissions. The reasonable operation of ice-storage air conditioning and coordinated scheduling of EVs and HVs further improve the economic performance of the system.