[Objective] After multiple line failures， a distribution network can maintain load supply by forming multiple microgrids. The initial formation and subsequent dynamic interconnection of microgrids require consideration of frequency-voltage control and sequential coordinated output of various types of resources. Hence， this paper proposes a multi-source sequential coordinated power-supply recovery method for post-disaster distribution networks， incorporating droop-control-based dynamic networked microgrid technology and network reconfiguration methods. [Methods] First， a pre-disaster electric vehicle dispatch model is established， considering the impact of impending extreme events on user travel intentions. Subsequently， a sequential power-supply recovery model is established that comprehensively considers the output of distributed resources， reverse charging of electric vehicles， repair crew dispatch， and flexible load management with the integration of frequency-voltage control constraints. Finally， multiple sets of examples are designed to validate the proposed method. [Results] The dynamic networked microgrid technology incorporating droop control can reduce the load-shedding ratio during faults to 30% of that without considering dynamic interconnections. [Conclusions] This effectively lowers the amount of load shedding while ensuring the safety of load restoration， providing an important reference for power-supply recovery of distribution networks under extreme events.

[Objective] In the context of high-percentage renewable energy integration， to satisfy the system flexibility and low-carbon demand， we propose an optimization method for the carbon capture reformation of thermal power plants considering the flexible power ramping demand. [Methods] First， a calculation model for the power system flexibility demand is established to address the ramping demand surge caused by large-scale wind and photovoltaic power integration. Second， a flexible operation model of thermal power units considering carbon capture reformation is established， and the flexible ramping supply capacity is quantified. Subsequently， considering the uncertainty of the load and renewable energy， a flexible ramping demand constraint and a fuzzy opportunity-constrained model are introduced to establish a carbon capture reformation planning model for thermal power plants. This model jointly solves the carbon capture reformation planning and operation optimization problems of thermal power units to obtain an optimal carbon capture reformation solution. Finally， the effectiveness of the planning model is verified using examples， and the impacts of different unit carbon penalties， renewable energy integration ratios， and confidence levels on the carbon capture reformation results are analyzed. [Results] Simulation results showed that after the optimal carbon capture reformation of thermal power plants， the carbon emissions of the power system were significantly reduced， the renewable energy curtailment rate was significantly reduced， and the total operating cost of the system was reduced by 9.44%. [Conclusions] Through optimal carbon capture reformation of thermal power plants， the output downward regulation space and ramping capability of thermal power plants can be improved， which can promote the accommodation of renewable energy while reducing the carbon emissions of the power system， thus enhancing the economic efficiency of system operation.