Decentralized Synergetic Control of Power Systems

The objective of this dissertation is to design decentralized controllers to enhance the transient stability of power systems. Due to the nonlinearities and complexities of the system, nonlinear control design techniques are required to improve its dynamic performance. In this dissertation a synergetic control technique is being proposed to design supplementary controller that is added to the exciter of the generation unit of the system. Although this method has been previously applied to a Single Infinite Machine Bus (SMIB) system with high degree of success, it has not been employed to systems with multi machine. Also, the method has good robust characteristic like that of the popular Sliding Mode Control (SMC) technique. But the latter technique introduces steady state chattering effect which can cause wear and tear in actuating system. This gives the proposed technique a major advantage over the SMC. In this work, the method is employed for systems with multi machine. Each of the machines is considered to be a subsystem and decentralized controller is designed for each subsystem. The interconnection term of each subsystem with the rest of the system is estimated by a polynomial function of the active power generated by the subsystem. Particle Swarm Optimization (PSO) technique is employed for optimum tuning of the controller\u27s parameters. To further enhance the performance of the system by widening its range of operation, Reinforcement Learning (RL) technique is used to vary the gains of the decentralized synergetic supplementary controller in real time. The approach is illustrated with several case studies including a SMIB system with or without a Static Var Compensator (SVC), a Two Area System (TAS) with or without an SVC, a three --machines-nine-bus system and a fifty machine system. Results show that the proposed control technique provides better damping than the conventional power system stabilizers and synergetic controllers with fixed gains

Feedback linearizing model predictive excitation controller design for multimachine power systems

In this paper, a nonlinear excitation controller is designed for multimachine power systems in order to enhance the transient stability under different operating conditions. The two-axis models of synchronous generators in multimachine power systems along with the dynamics of IEEE Type & #x2013;II excitation systems, are considered to design the proposed controller. The partial feedback linearization scheme is used to simplify the multimachine power system as it allows to decouple a multimachine power system based on the excitation control inputs of synchronous generators. A receding horizon-based continuous-time model predictive control scheme is used for partially linearized power systems to obtain linear control inputs. Finally, the nonlinear control laws, which also include receding horizon-based control inputs, are implemented on an IEEE 10-machine, 39-bus New England power system. The superiority of the proposed scheme is evaluated by providing comparisons with a similar existing nonlinear excitation controller where the control input for the feedback linearized model is obtained using the linear quadratic regulator (LQR) approach. The simulation results demonstrate that the proposed scheme performs better as compared to the LQR-based partial feedback linearizing excitation controller in terms of enhancing the stability margin

Power system damping controllers design using a backstepping control technique

The objective of this dissertation is to design and coordinate controllers that will enhance transient stability of power systems subject to large disturbances. Two specific classes of controllers have been investigated, the first one is a type of supplementary signals added to the excitation systems of the generating units, and the second is a type of damping signal added to a device called a Static Var Compensator that can be placed at any node in the system. To address a wide range of operating conditions, a nonlinear control design technique, called backstepping control, is used. While these two types of controllers improve the dynamic performance significantly, a coordination of these controllers is even more promising. Control coordination is presented in two parts. First part concerns simultaneous optimization of selected control gains of exciter and SVC in coping with the complex nature of power systems. Second part proposes a combination of reinforcement learning and a backstepping control technique for excitation control system. The reinforcement learning progressively learns and adapts the backstepping control gains to handle a wide range of operating conditions. Results show that the proposed control technique provides better damping than conventional power system stabilizers and backstepping fixed gain controllers

DEVELOPMENT OF NONLINEAR CONTROL SCHEMES FOR ELECTRIC POWER SYSTEM STABILIZATION

Power system stabilizers and other controllers are employed to damp oscillations in power systems, thereby guaranteeing satisfactory dynamic performance following major network disturbances. However, the parameters of these controllers are often tuned based on the power system linearized model which generally is a function of the system operating point or state. These controllers suffer from poor performance when the system state changes. The aim of the research work reported in this Thesis is to develop nonlinear synchronous generator excitation control schemes with control laws for providing improved transient stability when the system is subjected to wide parameter variations due to network disturbances. The study employed fourth-and third-order models of a single-machine-connected-to-an-infinite-bus system to design two nonlinear sliding mode control laws (CLs) and one finite-time homogeneous control law (CL), which were constructed based on a well-chosen output function of the system. The parameters of the control laws were properly selected and/or tuned to give desirable dynamic characteristics using well established linear control methods. Justifications for the selection of the fourth-and third-order synchronous generator models to design the aforesaid controllers are presented. Dynamic simulations of the system under the action of the control laws were carried out using MATLAB®/SIMULINK. In order to test the performance of the laws, several simulation studies were performed when the voltage magnitude (V) of the infinite bus and the transmission line reactance (XE) of the system changed due to an applied three-phase symmetrical fault at the infinite bus and generator terminals. Results obtained from these studies show that the dynamic characteristics of the system being investigated have improved significantly, in terms of the rotor angle and rotor speed first peak, damping of low-frequency mechanical oscillations in rotor angle following fault clearance, and settling times of key stability indicators (rotor angle and rotor speed). For instance, for application of each of 5-cycle, 7-cycle, and 9-cycle fault at the infinite bus, the system rotor angle settled to its stable steady values within 1 - 2.2s with minimal control effort that varied between -5pu and 5pu before settling at the prefault value of 1.5603pu in 4.32s (CL1), in 1.92s (CL2), and in 3.32s (CL3). Whereas, CL3, which is a contribution to the improvement of the existing general higher-order sliding mode control structure for synchronous excitation control, was able to make the system withstand greater fault duration than CL1, CL2, which has a new positive parameter (called the dilation gain) incorporated into it, furnished the system with the greatest fault-retaining capability. In practice, the implementation of the three control laws can be carried out in a static exciter configuration with a very fast response