Biblio

As more non-synchronous renewable energy sources (RES) participate in power systems, the system's inertia decreases and becomes time dependent, challenging the ability of existing control schemes to maintain frequency stability. System operators, research laboratories, and academic institutes have expressed the importance to adapt to this new power system paradigm. As one of the potential solutions, virtual inertia has become an active research area. However, power dynamics have been modeled as time-invariant, by not modeling the variability in the system's inertia. To address this, we propose a new modeling framework for power system dynamics to simulate a time-varying evolution of rotational inertia coefficients in a network. We model power dynamics as a hybrid system with discrete modes representing different rotational inertia regimes of the network. We test the performance of two classical controllers from the literature in this new hybrid modeling framework: optimal closed-loop Model Predictive Control (MPC) and virtual inertia placement. Results show that the optimal closed-loop MPC controller (Linear MPC) performs the best in terms of cost; it is 82 percent less expensive than virtual inertia placement. It is also more efficient in terms of energy injected/absorbed to control frequency. To address the lower performance of virtual inertia placement, we then propose a new Dynamic Inertia Placement scheme and we find that it is more efficient in terms of cost (74 percent cheaper) and energy usage, compared to classical inertia placement schemes from the literature.