Och, Alexander (RWTH Aachen University), Ulbig, Andreas (RWTH Aachen University)

Stochastic Model Predictive Control for Robust Grid Frequency Regulation

Scheduled for presentation during the Regular Session "Estimation and control techniques for power systems" (FriS1T4), Friday, July 12, 2024, 10:40−11:00, Session room 4

12th IFAC Symposium on Control of Power & Energy Systems, July 10-12, 2024, Rabat, Morocco

This information is tentative and subject to change. Compiled on March 6, 2025

Abstract

This paper delves into the application of Stochastic Model Predictive Controls (SMPC) for power grids driven by inverter-interfaced generators, focusing on enhancing grid stability amidst decreasing inertia. By employing SMPC, uncertainties in energy systems are anticipated and plant-model mismatch is mitigated. Improvement in grid robustness concerning frequency limits is demonstrated via a Monte Carlo approach. The integration of data-driven model augmentation and stochastic constraint tightening significantly enhances the precision and robustness of frequency control. This study highlights the potential of SMPC in navigating uncertainties in energy systems and offering a robust framework for maintaining grid stability.