Hybrid QSS and Dynamic Extended-Term Simulation Based on Holomorphic Embedding

TL;DR

This paper introduces a novel extended-term power system simulation method combining holomorphic embedding with dynamic QSS models, enabling accurate and efficient analysis of complex, multi-timescale power system behaviors.

Contribution

It presents a new hybrid simulation approach that integrates holomorphic embedding with dynamic QSS models for improved extended-term power system analysis.

Findings

Demonstrates high accuracy in event-driven simulations.

Achieves larger, adaptive time steps for efficiency.

Successfully evaluates power system restoration plans.

Abstract

Power system simulations that extend over a time period of minutes, hours, or even longer are called extended-term simulations. As power systems evolve into complex systems with increasing interdependencies and richer dynamic behaviors across a wide range of timescales, extended-term simulation is needed for many power system analysis tasks (e.g., resilience analysis, renewable energy integration, cascading failures), and there is an urgent need for efficient and robust extended-term simulation approaches. The conventional approaches are insufficient for dealing with the extended-term simulation of multi-timescale processes. This paper proposes an extended-term simulation approach based on the holomorphic embedding (HE) methodology. Its accuracy and computational efficiency are backed by HE's high accuracy in event-driven simulation, larger and adaptive time steps, and flexible switching between full-dynamic and quasi-steady-state (QSS) models. We used this proposed extended-term simulation approach to evaluate bulk power system restoration plans, and it demonstrates satisfactory accuracy and efficiency in this complex simulation task.