Temporal Regulation Domain for New-Type Power Systems: Concept and Methodology
The rapid proliferation of inverter-based renewables in new-type power systems has exposed the inadequacy of conventional point-based regulation capability assessments, which evaluate a single operating point and fail to capture the temporally coupled feasible space required for scheduling and resource allocation. This paper introduces the temporal regulation domain (TRD) as a global construct that maps all feasible system states satisfying intertemporal constraints into an observation space. A compact TRD model is formulated incorporating ramping, state-of-charge, power balance, security, and regulation cost budget constraints. Topological analysis establishes that the TRD is bounded, closed, and monotonically non-decreasing with respect to the cost budget. To overcome the curse of dimensionality in boundary characterization, a prior-constraint-guided deep neural network is developed, embedding monotonicity priors into the loss function. Simulations on a modified IEEE 118-bus system demonstrate that the proposed method efficiently and accurately delineates high-dimensional TRD boundaries. The TRD expands in a stepwise manner with regulation cost investment, exhibiting diminishing marginal returns; identifying the stepwise growth point provides a reliable reference for cost optimization. As renewable penetration increases, the TRD follows a steep-rise, plateau, and sharp-drop pattern, enabling identification of critical penetration thresholds to guide renewable deployment without violating security boundaries.