Towards low-inertia power systems: An overview of monitoring technology, challenges and emerging solutions
Abstract
The interaction of hybrid energy generation resources and the nature of electrical heterogeneous demand on power systems are reshaping power system operation and its dynamic behavior. The high penetration of inverter-based resources (IBRs) is defining the features of grid operation. Low-inertia power systems (LIPS) experience faster transients and weaker system strength, making them more vulnerable to large disturbances. In this document, the IEEE Working Group (WG) on Big Data & Analytics for Transmission Systems combines their knowledge and collective efforts to provide a comprehensive, multidimensional understanding of the current challenges in LIPS. First, the system-level services based on ancillary services and the relevance of wide-area measurement system (WAMS), interoperable control and visualization platforms, as well as the structures of different IBRs are discussed. Then, the current challenges in distribution and transmission systems, as well as potential solutions related to synthetic inertia to reduce the Rate of Change of Frequency (ROCOF), the use of dynamic voltage regulators to support transient events, and WAMS technology used to control and operate on different timescales of dynamic phenomena are addressed. Finally, a future outlook is provided were the main conclusion of the WG is that harmonizing high-speed monitoring standards and developing robust, data-driven methods based on artificial intelligence (AI) and machine learning (ML) for the coordinated operation of mixed fleets of grid-following and grid-forming, as well as the integration of human operators into increasingly automated control environments, are promising avenues for achieving resilient and flexible power systems.
Fields of Study & Subjects
Power System Optimization and Stability
Microgrid Control and Optimization
Wind Turbine Control Systems
Publication details
- Journal / source
- International Journal of Electrical Power & Energy Systems
- Publisher
- Elsevier BV
- Volume
- 179
- Pages
- 112021–112021
- Publication date
- 1 June 2026
- Language
- EN