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Voltage instability in power systems arises due to the shortage of reactive power and may cause abnormally low bus voltages leading to a partial or complete blackout. In order to maintain the system voltages within a safe limit, voltage control techniques such as shunt capacitor banks, Static VAR Compensators (SVCs), load shedding, and transformer tap-changer blocking, are employed. In this paper, a novel receding-horizon Model Predictive Control (MPC)-based voltage controller is proposed, which, by optimally controlling generator reactive power and SVC output, maintains the voltage stability of a power system. For this, a sensitivity-based analysis is performed to design a state-space model of the power system. The frequency and voltage dependency of load and generation are considered in the system equations. The voltage control is done step-wise, and the optimal control action in each step is calculated by minimizing a cost function subject to a set of relevant constraints. Different Voltage Stability Indices (VSIs) are used as a measure of voltage stability and also used in the constraints for the optimization problem. The performance of the proposed controller is evaluated on IEEE 9-, 39- and 118-bus systems, considering different types of loads and contingencies. [ABSTRACT FROM AUTHOR]

A disturbance in a power system causes the frequency to deviate from its nominal value. The load and generation of the system are strategically adjusted to restore the synchronous frequency. This paper introduces novel shrinking-horizon model predictive control (MPC) technique, which employs a centralized controller for managing the load-frequency of a single-area power system and distributed controllers for multi-area systems. The controller optimally changes generation settings and sheds non-critical loads to make the frequency and tie-line power deviation zero. In contrast to existing approaches that use an approximate first-order transfer function model, this paper presents a structure-preserving linear state-space model for power systems. This model takes into account frequency and voltage dependencies of both load and generation, allowing for more accurate representation of power system behavior. During rescheduling, the controller minimizes additional cost associated with changes while satisfying various operational and physical constraints. The paper conducts several case studies using IEEE test systems to devise corrective action plans for both under- and over-frequency scenarios. The proposed controller’s robustness is tested against disturbances originating from renewable energy sources. Furthermore, a performance comparison is drawn between the proposed controller and existing control techniques. The comparative analysis indicates that the proposed approach consistently outperforms other controllers in terms of dynamic performance improvement, measured by parameters such as settling time, overshoot, undershoot, and error reduction. It is observed that the maximum undershoot and the settling time of the frequency is the least for centralized control. Comparative studies indicate that under different circumstances, the proposed approach outperforms other controllers in dynamic performance improvement, measured by settling time, overshoot, undershoot, and error reduction. The net rescheduling cost obtained by the proposed centralized MPC, cooperative distributed MPC, and non-cooperative distributed MPC-based controllers is 38, 25, and 24% lower than the conventional PI controller used for LFC of IEEE 39-bus system. This validates the suggested controllers’ cost-effectiveness. [ABSTRACT FROM AUTHOR]