Hybrid QSS and Dynamic Extended-Term Simulation Based on Holomorphic Embedding
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.
Cite
@article{arxiv.2104.02877,
title = {Hybrid QSS and Dynamic Extended-Term Simulation Based on Holomorphic Embedding},
author = {Rui Yao and Feng Qiu},
journal= {arXiv preprint arXiv:2104.02877},
year = {2021}
}