<p>An on-line identifier using Functional Link Network (FLN) and Pole-shift (PS) controller for power system stabilizer (PSS) application are presented in this thesis. To have the satisfactory performance of the PSS controller, over a wide range of operating conditions, it is desirable to adapt PSS parameters in real time. Artificial Neural Networks (ANNs) transform the inputs in a low-dimensional space to high-dimensional nonlinear hidden unit space and they have the ability to model the nonlinear characteristics of the power system. The ability of ANNs to learn makes them more suitable for use in adaptive control techniques.</p> <p>On-line identification obtains a mathematical model at each sampling period to track the dynamic behavior of the plant. The ANN identifier consisting of a Functional link Network (FLN) is used for identifying the model parameters. A FLN model eliminates the need of hidden layer while retaining the nonlinear mapping capability of the neural network by using enhanced inputs. This network may be conveniently used for function approximation with faster convergence rate and lesser computational load.</p> <p>The most commonly used Pole Assignment (PA) algorithm for adaptive control purposes assign the pole locations to fixed locations within the unit circle in the z-plane. It may not be optimum for different operating conditions. In this thesis, PS type of adaptive control algorithm is used. This algorithm, instead of assigning the closed-loop poles to fixed locations within the unit circle in the z-plane, this algorithm assumes that the pole characteristic polynomial of the closed-loop system has the same form as the pole characteristic of the open-loop system and shifts the open-loop poles radially towards the centre of the unit circle in the z-plane by a shifting factor &alpha; according to some rules. In this control algorithm, no coefficients need to be tuned manually, so manual parameter tuning (which is a drawback in conventional power system stabilizer) is minimized. The PS control algorithm uses the on-line updated ARMA parameters to calculate the new closed-loop poles of the system that are always inside the unit circle in the z-plane.</p> <p>Simulation studies on a single-machine infinite bus and on a multi-machine power system for various operating condition changes, verify the effectiveness of the combined model of FLN identifier and PS control in damping the local and multi-mode oscillations occurring in the system. Simulation studies prove that the APSSs have significant benefits over conventional PSSs: performance improvement and no requirement for parameter tuning.</p>

<p>An on-line identifier using Functional Link Network (FLN) and Pole-shift (PS) controller for power system stabilizer (PSS) application are presented in this thesis. To have the satisfactory performance of the PSS controller, over a wide range of operating conditions, it is desirable to adapt PSS parameters in real time. Artificial Neural Networks (ANNs) transform the inputs in a low-dimensional space to high-dimensional nonlinear hidden unit space and they have the ability to model the nonlinear characteristics of the power system. The ability of ANNs to learn makes them more suitable for use in adaptive control techniques.</p> <p>On-line identification obtains a mathematical model at each sampling period to track the dynamic behavior of the plant. The ANN identifier consisting of a Functional link Network (FLN) is used for identifying the model parameters. A FLN model eliminates the need of hidden layer while retaining the nonlinear mapping capability of the neural network by using enhanced inputs. This network may be conveniently used for function approximation with faster convergence rate and lesser computational load.</p> <p>The most commonly used Pole Assignment (PA) algorithm for adaptive control purposes assign the pole locations to fixed locations within the unit circle in the z-plane. It may not be optimum for different operating conditions. In this thesis, PS type of adaptive control algorithm is used. This algorithm, instead of assigning the closed-loop poles to fixed locations within the unit circle in the z-plane, this algorithm assumes that the pole characteristic polynomial of the closed-loop system has the same form as the pole characteristic of the open-loop system and shifts the open-loop poles radially towards the centre of the unit circle in the z-plane by a shifting factor &alpha; according to some rules. In this control algorithm, no coefficients need to be tuned manually, so manual parameter tuning (which is a drawback in conventional power system stabilizer) is minimized. The PS control algorithm uses the on-line updated ARMA parameters to calculate the new closed-loop poles of the system that are always inside the unit circle in the z-plane.</p> <p>Simulation studies on a single-machine infinite bus and on a multi-machine power system for various operating condition changes, verify the effectiveness of the combined model of FLN identifier and PS control in damping the local and multi-mode oscillations occurring in the system. Simulation studies prove that the APSSs have significant benefits over conventional PSSs: performance improvement and no requirement for parameter tuning.</p>

This thesis presents novel series compensation schemes and adaptive control techniques to enhance power system dynamics through damping Subsynchronous Resonance (SSR) and low-frequency power oscillations: local and inter-area oscillations. Series capacitive compensation of transmission lines is used to improve power transfer capability of the transmission line and is economical compared to the addition of new lines. However, one of the impeding factors for the increased utilization of series capacitive compensation is the potential risk of SSR, where electrical energy is exchanged with turbine-generator shaft systems in a growing manner which can result in shaft damage. Furthermore, the fixed capacitor does not provide controllable reactance and does not aid in the low-frequency oscillations damping. The Flexible AC Transmission System (FACTS) controllers have the flexibility of controlling both real and reactive power which could provide an excellent capability for improving power system dynamics. Several studies have investigated the potential of using this capability in mitigating the low-frequency (electromechanical) as well as the subsynchronous resonance (SSR) oscillations. However, the practical implementations of FACTS devices are very limited due to their high cost. To address this issue, this thesis proposes a new series capacitive compensation concept capable of enhancing power system dynamics. The idea behind the concept is a series capacitive compensation which provides balanced compensation at the power frequency while it provides phase unbalance at other frequencies of oscillations. The compensation scheme is a combination of a single-phase Thyristor Controlled Series Capacitor (TCSC) or Static Synchronous Series Compensator (SSSC) and a fixed series capacitors in series in one phase of the compensated transmission line and fixed capacitors on the other two phases. The proposed scheme is economical compared to a full three-phase FACTS counterpart and improves reliability of the device by reducing number of switching components. The phase unbalance during transients reduces the coupling strength between the mechanical and the electrical system at asynchronous oscillations, thus suppressing the build-up of torsional stresses on the generator shaft systems. The SSR oscillations damping capability of the schemes is validated through detailed time-domain electromagnetic transient simulation studies on the IEEE first and second benchmark models. Furthermore, as the proposed schemes provide controllable reactance through TCSC or SSSC, the supplementary controllers can be implemented to damp low-frequency power oscillations as well. The low-frequency damping capability of the schemes is validated through detail time-domain electromagnetic transient simulation studies on two machines systems connected to a very large system and a three-area, six-machine power system. The simulation studies are carried out using commercially available electromagnetic transient simulation tools (EMTP-RV and PSCAD/EMTDC). An adaptive controller consisting of a robust on-line identifier, namely a robust Recursive Least Square (RLS), and a Pole-Shift (PS) controller is also proposed to provide optimal damping over a wide range of power system operations. The proposed identifier penalizes large estimated errors and smooth-out the change in parameters during large power system disturbances. The PS control is ideal for its robustness and stability conditions. The combination results in a computationally efficient estimator and a controller suitable for optimal control over wider range of operations of a non-linear system such as power system. The most important aspect of the controller is that it can be designed with an approximate linearized model of the complete power system, and does not need to be re-tuned after it is commissioned. The damping capability of such controller is demonstrated through detail studies on a three-area test system and on an IEEE 12-bus test system. Finally, the adaptive control algorithm is developed on a Digital Signal Processing Board, and the performance is experimentally tested using hardware-in-the-loop studies. For this purpose, a Real Time Digital Simulator (RTDS) is used, which is capable of simulating power system in real-time at 50 µs simulation time step. The RTDS facilitates the performance evaluation of a controller just like testing on a real power system. The experimental results match closely with the simulation results; which demonstrated the practical applicability of the adaptive controller in power systems. The proposed controller is computationally efficient and simple to implement in DSP hardware.