An Annual Quasi-Static Time-Series Simulation Framework for Enhanced Transmission System Expansion Planning

TL;DR

This paper presents an annual quasi-static time-series simulation framework for transmission system expansion planning, capturing detailed operational dynamics and enabling more accurate, resilient grid development insights.

Contribution

It introduces a novel high-resolution simulation framework that integrates operational details into long-term planning, improving the accuracy of transmission expansion decisions.

Findings

Reveals operational constraints overlooked by static methods

Demonstrates the framework's application to Hydro-Québec's future grid scenarios

Shows the importance of aligning planning with operational realities for grid resilience

Abstract

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-Qu\'ebec'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.