Frequency Stability Assessment and Synthetic Inertia in Low-Inertia Power Systems: A Comprehensive Review
Abstract
The rapid integration of inverter-based renewable energy sources (RESs), particularly solar photovoltaic (PV) and wind power, has significantly reduced the rotational inertia traditionally provided by synchronous generators, creating unprecedented challenges for frequency stability in modern power systems. Reduced system inertia results in higher rates of change of frequency (RoCoF), deeper frequency nadirs, and increased vulnerability to disturbances, necessitating advanced frequency assessment and synthetic inertia solutions. This paper presents a comprehensive review of frequency stability assessment methods and synthetic inertia techniques for low-inertia power systems. First, the fundamental principles of frequency dynamics, inertial response, and the impact of renewable energy penetration on system inertia are discussed. Subsequently, recent advances in deterministic and probabilistic frequency stability assessment methodologies are reviewed, followed by a critical evaluation of virtual synchronous machines, droop-based virtual inertia, model predictive control, battery energy storage systems, grid-forming converters, and intelligent control strategies for synthetic inertia provision. A comparative analysis of existing studies highlights their methodologies, performance metrics, advantages, and practical limitations. The review further identifies key research challenges, including uncertainty modeling, adaptive inertia allocation, converter operational constraints, computational complexity, and real-time implementation. Finally, future research directions toward uncertainty-aware frequency assessment, adaptive synthetic inertia, artificial intelligence-assisted control, and resilient converter-dominated power systems are discussed. This review provides a comprehensive reference for researchers and power system engineers developing reliable frequency stability enhancement strategies for future renewable-dominated electricity networks.