The optimal scheduling of networked microgrids considering the coupled trading of energy and carbon emission allowance (CEA) has been extensively studied. Notably, the scheduling is performed on a daily basis, whereas the CEA is usually checked and determined once a year. The temporal mismatch between the daily scheduling and the yearly CEA should be addressed to realize the dynamic valuation of CEA. In this paper, the optimal scheduling of networked microgrids considering the temporal equilibrium allocation of annual CEA is investigated. Firstly, a CEA decomposition model is developed, which allocates allowance to individual microgrids and further decomposes them temporally using the entropy method. Secondly, a Lyapunov optimization-based low-carbon scheduling model is introduced to manage carbon emissions within each dispatch interval, ensuring annual CEA compliance and daily economic efficiency. Thirdly, a Stackelberg game-based energy–carbon coupling trading model is presented, which considers the uncertainties caused by fluctuations in external electricity and carbon prices to optimize trading prices and strategies of the microgrids. Finally, a test system is used to demonstrate the significant effects of emission reduction and the economic benefits of the proposed methods.