VELARDE RUEDA, PABLO ANIBAL, Hernandez-Rivera A. , Zafra-Cabeza A. , Bordons C.
No
European Control Conference
Conference Paper
Científica
0
0
Internacional
01/01/2026
2-s2.0-105047338721
This paper presents a detailed formulation of Probabilistic-Robust (Probust) MPC and its application to a real microgrid, focusing on its capability to detect faults in real-time and apply adaptive mitigation strategies. Unlike classical residual-based methods for Fault Detection and Isolation (FDI), Probust MPC integrates probabilistic constraints and robust optimization techniques to enhance resilience against uncertainties in power generation and demand. The proposed method dynamically adjusts control actions in response to stochastic disturbances, ensuring effective fault detection and mitigation. By incorporating robust probabilistic constraints, this approach systematically identifies faults before they develop into critical failures, allowing for timely corrective actions. Simulation results demonstrate that the proposed approach enhances system reliability, optimizes energy management, and improves operational robustness under various conditions. These findings highlight the potential of Probust MPC as a scalable and effective solution for operating resilient microgrids, as demonstrated through its application to data from a real energy community on the Culatra Island, Portugal. © 2026 EUCA.
Microgrids; Model predictive control; Optimization; Predictive control systems; Robust control; Stochastic control systems; Stochastic models; Energy; Faults detection; ITS applications; Microgrid; Model-predictive control; Probabilistic constraints; Probabilistic-robust MPC; Probabilistics; Robust optimization; Stochastics; Fault detection; Stochastic systems