Fault Tolerant Kalman Filter-Based Distributed Predictive Control in Power systems Under Governor Malfunction

Power systems are disposed to frequent faults, which may occur in any of its components, such as generating units, transformers, transmission network and/or loads. Governors, depending on type, suffer from the same faults that would be expected to find in any mechanical, hydraulic or electrical device or system. Determination of governor faults effects on system behavior and system stability was of special interest in this work. Here a distributed Kalman filter (KF) algorithm along with a distributed model predictive control (MPC) is proposed to maintain system performance while governor fault takes place. Distributed KF-based MPC estimates and control. The estimation of governor state and comparing with its real value results in fault detection where two control approaches are proposed to help system keep its stability and performance. The proposed control strategy is used in a demanding two-area power network.