Stackelberg game-based optimal scheduling for multi-community integrated energy systems considering energy interaction and carbon trading

The multi-community integrated energy system (MCIES) has become a practical approach to improve energy efficiency and reduce carbon emissions with the promotion of urbanization. However, the current optimal scheduling of MCIES neither balances the total operation cost of the MCIES and the individual benefits of community microgrids effectively nor considers the carbon emission accounting and carbon trading of terminal integrated energy systems adequately. In this study, a bi-level optimal scheduling framework dominated by the regional dispatching center (RDC) and fully participated by the community integrated energy systems (CIESs) is developed for the scheduling of MCIES, which considers the energy interaction and carbon trading between CIESs. Firstly, a refined carbon emission accounting model considering direct and indirect carbon emissions is proposed, which can calculate the carbon emissions of each CIES in detail from the energy flow perspective based on the definition of virtual and actual carbon flow. Then, a one-master-multi-slave game model is established, where the RDC acts as the leader pursuing the minimum operation cost of the region by formulating energy interaction and carbon trading schemes between CIESs, while the CIESs are regarded as the followers that adjust the energy consumptions to minimize their operation costs. Finally, the effectiveness of the proposed optimization model is validated through the case studies, which are tested in a specific urban area. The simulation results demonstrate that the proposed optimal scheduling model can not only effectively coordinate the benefits between RDC and CIESs, but also reduce the overall operational cost and carbon emission of the MCIES.