Optimal Load Frequency and Voltage Control in Interconnected Power Systems: A Model Predictive Control Approach

Abstract

Modern electric power systems are exceptionally complex human engineered system, constantly evolving in scale and complexity. This growth stems from the integration of renewable energy sources, sophisticated power electronics, and other cutting-edge electrical equipment. However, ensuring the smooth flow of electricity to consumers remains paramount. To achieve this, the power-system system must maintain a state of continuous stability. This dissertation explores into the intricate dynamics of power system stability, focusing primarily on two crucial aspects: frequency stability and voltage stability. It explores the complexities of frequency and voltage stability, their impact on power systems, and the measures taken to preserve them. The work introduces innovative control methods employed to keep the power grid steady, guaranteeing a continuous supply of dependable electricity to users. 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 work 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 work 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 increasing penetration of Renewable Energy Sources (RESs) in a power system makes the conventional LFC more challenging, since the power output from RESs is unpredictable or stochastic. In this thesis, a novel MPC based Stochastic Load Frequency Control (SLFC) technique is proposed, that enables high amounts of RESs to be integrated while maintaining reliable and stable operation. A structure-preserving linear state-space model for power systems is derived which more precisely represents a practical power system behavior. The proposed controller calculates optimal generation settings by minimizing an optimization problem subject to a set of constraints. To model the stochastic nature of RES power outputs, frequency deviation is added as a chance constraint in the optimization problem, transforming it to a chance constrained optimization problem. This ensures that the probability of frequency deviation at the end of prediction horizon, lying outside a specific range, is always less than some predefined confidence level. 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, transformer tap-changer blocking, etc., are employed. In this dissertation, a novel receding-horizon 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 the standard IEEE 9, 39 and 118 bus test systems to prove the efficacy of the proposed control techniques, under different operating conditions and in the presence of different contingencies.