The urban power grid (UPG) combines transmission and distribution networks. Past studies on UPG congestion mitigation have primarily focused on relieving local congestion while ignoring large-scale energy transfer with safety margins and load balancing. This situation is expected to worsen with the proliferation of renewable energy and electric vehicles. In this paper, a two-layer congestion mitigation framework is proposed, one which considers the congestion of the UPG with flexible topologies. In the upper-layer, the particle swarm optimization algorithm is employed to optimize the power supply distribution (PSD) of substation transformers. This is known as the upper-layer PSD. The lower-layer model recalculates the new PSD, known as the lower-layer PSD, based on the topology candidates. A candidate topology is at an optimum when the Euclidean distance mismatch between the upper-and lower-layer PSDs is the smallest. This optimum topology is tested by standard power flow to ascertain its feasibility. The optimum transitioning sequence between the initial and optimum topologies is also determined by the two-layer framework to minimize voltage deviation and line overloading of the UPG considering dynamic thermal rating. The proposed framework is tested on a 56-node test system. Results show that the proposed framework can significantly reduce congestion, maintain safety margins, and determine the optimum transitioning sequence.