Collaborative optimization of flexible resources for power system resilience based on feasibility-guided deep Q-networks

A feasibility-guided deep Q-network (FG-DQN) framework for the collaborative optimization of flexible resources is proposed in this paper to enhance power system resilience under extreme events. Targeting the coordinated siting, sizing, and switching of mobile generators, energy storage systems, reactive compensation devices, and reserve interconnections, the resilience enhancement task is formulated as a constrained sequential decision problem under multiple concurrent contingencies. AC power-flow equations, operational-safety limits, and budget constraints are embedded into the environment, and a normalized incremental-potential reward aligned with a composite resilience score is introduced. A width-limited search mechanism for reserve-interconnection selection is further developed to improve computational tractability and execution quality. Simulation results on the IEEE-30 and IEEE-57 systems confirm that more balanced resilience improvements and better overall solution quality can be achieved under unified feasibility checks.