Abstract: To address the difficulty of conventional static active-reactive power coordinated optimization in wind-PV-energy storage renewable energy bases in ensuring the executability of dynamic support following disturbances, a day-ahead active-reactive power co-optimization method considering the dynamic feasible region of energy storage is proposed. First, the multidimensional coupling relationships among the active-power frequency support capability, reactive-power voltage support capability, energy sustainment capability, and apparent-power capacity of the energy storage converter are systematically characterized. On this basis, a time-varying dynamic feasible region is constructed by jointly considering the current state of charge (SOC), operating setpoint, and the utilization of active- and reactive-power capacities. Furthermore, comprehensive and component-wise margin indices are established, and the dynamic support boundaries of energy storage are explicitly embedded into the day-ahead coordinated optimization framework. A multi-objective scheduling model is then formulated to simultaneously account for renewable energy curtailment, voltage deviation, network losses, and the executability of dynamic support, and is solved using the NSGA-III algorithm. Case studies demonstrate that, compared with conventional static methods, which are prone to insufficient support during high-risk periods, and fixed-reserve methods, which tend to result in excessive reserve allocation during low-risk periods, the proposed method can adaptively adjust the multidimensional reserve space of energy storage according to the system operating state and disturbance requirements. While maintaining acceptable static operating performance, the proposed method significantly improves the executability of dynamic support and enables the system operating point to better conform to the dynamic feasible region. The proposed approach provides an effective reference for refined energy storage allocation and coordinated static-dynamic scheduling of renewable energy bases.