An Annual Quasi-Static Time-Series Simulation Framework for Enhanced Transmission System Expansion Planning
For transmission planners, this framework addresses the inadequacy of traditional snapshot-based methods by enabling high-resolution, year-round modeling to align planning with operational realities.
The paper introduces an annual quasi-static time-series simulation framework for transmission system expansion planning that captures temporal dynamics and operational constraints, applied to Hydro-Québec's 2035/2036 grid. The framework reveals critical insights under high renewable penetration and integrates energy storage control to mitigate wind variability.
The increasing integration of distributed energy resources (DERs), variable renewable energy sources, and emerging technologies presents new challenges for transmission system expansion planning (TSEP). Traditional snapshot-based and deterministic approaches are inadequate for capturing the temporal dynamics and operational constraints of modern power systems. This paper introduces an annual quasi-static time-series simulation (AQSTSS) framework that enables high-resolution, year-round modeling of transmission systems, incorporating detailed equipment behavior, control strategies, and DER interactions. By simulating system performance across all seasons and operating conditions, AQSTSS uncovers flexibility opportunities and operational constraints that static methods overlook. Applied to Hydro-Québec's projected 2035/2036 grid, the framework reveals critical insights under high wind and electric vehicle penetration. It also integrates an energy storage control strategy designed to mitigate wind variability and support grid reliability. Furthermore, AQSTSS facilitates the assessment of system resilience under diverse scenarios, including extreme weather and load variability. The simulation results underscore the importance of aligning planning with operational realities to ensure secure, efficient, and future-ready grid development. Overall, the proposed framework enhances the robustness of TSEP by bridging the gap between long-term planning and real-time operational needs.