Minimum Inertia Requirement Assessment Method for Renewable Energy Grid- Connected Systems With Multiple Virtual Inertia Control Units

With the high proportion of renewable energy sources being integrated into power systems, the level of system inertia continues to decline, posing severe challenges to frequency stability. Existing methods either ignore governor deadband effects or require iterative simulations, leading to excessive prediction errors or excessively long computation time. This paper proposes a method for evaluating the minimum inertia requirement of grid-connected systems with multiple virtual inertia control units. First, a multi-machine frequency response model is established, incorporating multiple virtual inertia control units such as synchronous generators, wind turbines, and photovoltaic-energy storage systems. A linear-exponential hybrid function explicitly captures deadband-induced nonlinear dynamics. Second, with minimum system inertia as the optimization objective, a minimum inertia assessment model is established that incorporates multiple constraints including system inertia level, rate of change of frequency, available adjustable capacity, and frequency extreme points. Simultaneously, the frequency response is analytically partitioned into pre- and post-primary regulation stages, enabling direct solution without iteration. Particle swarm optimization efficiently solves the model. Finally, simulation case studies are conducted to verify the effectiveness and superiority of the proposed method, achieving a frequency nadir prediction error below 2% and an 85% faster computation (