Unraveling the Dynamic Characteristics of Inertia Fluctuations in Modern Power Systems

As an important index for the safe and stable operation of the power grid, inertia has traditionally been estimated and predicted. Significant progress has been made in this regard. Accurately predicting inertia is closely tied to effectively understanding and managing its dynamic characteristics. However, limited research has focused on how inertia fluctuates and the underlying principles governing these variations. Therefore, this paper employs statistical methods to unravel the seasonal, periodic, and heteroscedastic dynamic characteristics of inertia using data from the British power grid over the past five years. It integrates the principles of inertia generation and external environmental influences to demonstrate that power system inertia exhibits seasonal, heteroscedastic, and periodic fluctuation characteristics. Furthermore, this paper provides a reasonable explanation for the change mechanism of inertia by comparing and analyzing the inertia, load and renewable energy generation simultaneously. These findings provide a foundation for improving inertia forecasting and grid stability management in renewable-rich power systems.