Coordinated Optimal Scheduling of Transmission Grid and Multi-Parks Considering Source-Load Uncertainties with Multi-Spatial–Temporal Scales

With the ongoing transformation of energy systems and the expanding scale of multi-park integrated energy systems, this paper proposes a novel multi-spatiotemporal scale scheduling framework that integrates robust optimization with distributed coordination to address the challenges of complex spatiotemporal coupling and significant uncertainties in the coordinated operation of transmission grids and multi-park integrated energy systems under high renewable energy penetration. The proposed framework establishes a hierarchical optimization model encompassing day-ahead, intra-day rolling, and real-time scheduling stages, incorporating multi-energy coupling constraints and accounting for load uncertainty. Robust optimization is employed to effectively manage source-load fluctuations arising from renewable intermittency. For solution implementation, the analytical target cascading (ATC) method is adopted to enable distributed collaborative optimization between the transmission system and individual park-level systems. Simulation results demonstrate that the proposed approach significantly enhances both the economic efficiency and operational reliability of the integrated energy system.