Robust sensor fault detection and isolation scheme for interconnected smart power systems in presence of RER and EVs using unknown input observer

Correct measurement of variables used in frequency control of power system is crucial for power system operation, stability, and security. Once sensor fault is occurred in power system, the faulty sensor should be instantly isolated. To this end, a model-based fault detection and isolation (FDI) technique is adopted in this paper. The proposed sensor FDI scheme for complex power systems is built based on unknown input observer (UIO) which is robust for systems with unknown inputs. The load fluctuation and output power variation of renewable energy resources are modeled as unknown inputs of power systems. To show the effectiveness of the proposed schemes in case of future smart grids, the studied power system is developed to combine both electric vehicles (EVs) and high penetration level of renewable energy resources. The simulation scenarios are carried out for an eleven-order dynamical multi-area smart power system. The robustness of using UIO to detect and isolate sensor faults in power system is proved by several simulation scenarios. Likewise, the simulation results show that isolation of faulty sensors can be guaranteed by proper selection of the measured variables in the state space model of the studied system.