发表机构
University of Zagreb Faculty of Electrical Engineering and Computing（萨格勒布大学电气工程和计算学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文综述了换流器主导电力系统稳定性研究中的模型降阶方法，重点分析关键方程及各类策略的优缺点，并指出谐波交互等挑战与未来发展方向。
AI 中文摘要
可再生能源的快速集成正在将现代电力系统转变为换流器主导的网络，其特征是复杂的多时间尺度动力学以及宽频率范围内新的稳定性交互作用。对这些现象的准确分析需要输电网和电力电子换流器的高保真模型，这通常会导致大规模微分代数系统，带来显著的计算负担。本文对富含换流器的电力系统的模型降阶技术进行了分析性综述，特别强调了降阶过程中使用的关键方程。讨论了常用策略的优点和局限性，包括基于时间尺度的奇异摄动、基于投影、基于算子、数据驱动和基于机器学习的方法。综述强调了与谐波交互和多频动力学相关的关键挑战，并为未来电力系统开发计算高效且动态准确的降阶模型指明了方向。
英文摘要
The rapid integration of renewable energy sources is transforming modern electric power systems into converter-dominated networks characterized by complex multi-timescale dynamics and new stability interactions over a wide frequency range. Accurate analysis of these phenomena requires high-fidelity models of transmission networks and power electronic converters, which often result in large-scale differential-algebraic systems with significant computational burden. This paper provides an analytical review of model order reduction techniques for converter-rich power systems, with particular emphasis on the key equations employed in the reduction process. Advantages and limitations of commonly used strategies, including timescale-based singular perturbation, projection-based, operator-based, data-driven, and machine-learning based methods, are discussed. The synthesis highlights key challenges related to harmonic interactions and multi-frequency dynamics, and outlines directions for the development of computationally efficient yet dynamically accurate reduced-order models for future power systems.
Comments53 pages, 4 figures
