The internal voltage angle of a generator is an important parameter that indicates the stability, both transient and steady-state, of the generator. This paper proposes a method of measuring and synchronizing the internal angle using a microprocessor and an optical encoder installed on the shaft of a generator. With a synchronized angle measurement, accurate stability studies and wide-area controls can be implemented. The experimental setup for measuring the rotor angle of a generator is explained in this work. A wide-area power system stabilizer implementing the synchronized angle measurement is then investigated using a four machine, two-area system. A synchronized remote feedback rotor angle signal is included in a traditional stabilizer design. It is shown that this remote signal helps increase the stability of the system while also having the benefit of being able to be predicted accurately. This capability makes bad data detection and communication delay compensation possible. / Master of Science

Syftet med examensarbetet är att digitalt tillämpa en stabilisering av pendlingar i den aktiva effekten hos en synkrongenerator för vattenkraft kopplad till ett distributionsnät. Implementeringen är tänkt att ske i en PLC som redan hanterar andra delar av magnetiseringen. Effektstabiliseringen görs genom att en motverkande styrsignal skickas till magnetiseringsutrustningen vilken i sin tur påverkar generatorns uteffekt. Denna motverkande styrsignal kan tas fram på olika sätt. Två modeller, av IEEE standardiserade, för effektstabilisering undersöks, PSS1A och PSS2B. En Simulink-modell över ett distributionsnät med generator byggs upp för att testa effektstabiliseringen. Diskretisering av den ena standarden utförs för att digital implementering ska kunna ske. Tester utförs även på denna modell för att kunna validera dess funktion i jämförelse med den kontinuerliga. Den tidsdiskreta modellen görs om till ett matematiskt uttryck tillämpbart i PLC:n. Jämförelse sker mellan simuleringarna och den tillämpade modellen genom mätningar. / The purpose of the degree project is to make a digital realization of a stabilizer for oscillations in the active power from a hydropower synchronous generator, connected to a power network. The implementation is supposed to be done in a PLC which already handles part of the excitation system. The power stabilization is achieved by sending a counteracting reference signal to the excitation system which controls the generator’s output power. This counteracting signal can be achieved in several ways. Two existing models, standardized by IEEE, for power system stabilizing will be examined, PSS1A and PSS2B. A Simulink-model of a distribution net with a generator is constructed to test the stabilizers. To perform a digital implementation a discrete transformation of one continuous model is done. This discrete model is also tested to verify the function in comparison to the continuous one. The discrete model is reorganized in a form possible to implement in the PLC. Comparison between the simulated and the implemented model is made by measurement.

<p>Syftet med examensarbetet är att digitalt tillämpa en stabilisering av pendlingar i den aktiva effekten hos en synkrongenerator för vattenkraft kopplad till ett distributionsnät.</p><p>Implementeringen är tänkt att ske i en PLC som redan hanterar andra delar av magnetiseringen.</p><p>Effektstabiliseringen görs genom att en motverkande styrsignal skickas till magnetiseringsutrustningen vilken i sin tur påverkar generatorns uteffekt. Denna motverkande styrsignal kan tas fram på olika sätt.</p><p>Två modeller, av IEEE standardiserade, för effektstabilisering undersöks, PSS1A och PSS2B.</p><p>En Simulink-modell över ett distributionsnät med generator byggs upp för att testa effektstabiliseringen.</p><p>Diskretisering av den ena standarden utförs för att digital implementering ska kunna ske. Tester utförs även på denna modell för att kunna validera dess funktion i jämförelse med den kontinuerliga.</p><p>Den tidsdiskreta modellen görs om till ett matematiskt uttryck tillämpbart i PLC:n.</p><p>Jämförelse sker mellan simuleringarna och den tillämpade modellen genom mätningar.</p> / <p>The purpose of the degree project is to make a digital realization of a stabilizer for oscillations in the active power from a hydropower synchronous generator, connected to a power network.</p><p>The implementation is supposed to be done in a PLC which already handles part of the excitation system.</p><p>The power stabilization is achieved by sending a counteracting reference signal to the excitation system which controls the generator’s output power. This counteracting signal can be achieved in several ways.</p><p>Two existing models, standardized by IEEE, for power system stabilizing will be examined, PSS1A and PSS2B.</p><p>A Simulink-model of a distribution net with a generator is constructed to test the stabilizers.</p><p>To perform a digital implementation a discrete transformation of one continuous model is done. This discrete model is also tested to verify the function in comparison to the continuous one.</p><p>The discrete model is reorganized in a form possible to implement in the PLC.</p><p>Comparison between the simulated and the implemented model is made by measurement.</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>

<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>

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed. / May 2007

The problem of dynamic stability of power system has challenged power system engineers since over three decades now. In a generator, the electromechanical coupling between the rotor and the rest of the system causes it to behave in a manner similar to a spring mass damper system, which exhibits an oscillatory behaviour around the equilibrium state, following any disturbance, such as sudden change in loads, change in transmission line parameters, fluctuations in the output of turbine and faults etc. The use of fast acting high gain AVRs and evolution of large interconnected power systems with transfer of bulk power across weak transmission links have further aggravated the problem of low frequency oscillations. The oscillations, which are typically in the frequency range of 0.2 to 3.0 Hz, might be excited by the disturbances in the system or, in some cases, might even build up spontaneously. These oscillations limit the power transmission capability of a network and, sometimes, even cause a loss of synchronism and an eventual breakdown of the entire system. The application of Power System Stabilizer (PSS) can help in damping out these oscillations and improve the system stability. The traditional and till date the most popular solution to this problem is application of conventional power system stabilizer (CPSS). However, continual changes in the operating condition and network parameters result in corresponding change in system dynamics. This constantly changing nature of power system makes the design of CPSS a difficult task. Adaptive control methods have been applied to overcome this problem with some degree of success. However, the complications involved in implementing such controllers have restricted their practical usage. In recent years there has been a growing interest in robust stabilization and disturbance attenuation problem. H∞ control theory provides a powerful tool to deal with robust stabilization and disturbance attenuation problem. However the standard H∞ control theory does not guarantee robust performance under the presence of all the uncertainties in the power plants. This thesis provides a method for designing fixed parameter controller for system to ensure robustness under model uncertainties. Minimum performance required of PSS is decided a priori and achieved over the entire range of operating conditions. A new method has been proposed for tuning the parameters of a fixed gain power system stabilizer. The stabilizer places the troublesome system modes in an acceptable region in the complex plane and guarantees a robust performance over a wide range of operating conditions. Robust D-stability is taken as primary specification for design. Conventional lead/lag PSS structure is retained but its parameters are re-tuned using genetic algorithm (GA) to obtain enhanced performance. The advantage of GA technique for tuning the PSS parameters is that it is independent of the complexity of the performance index considered. It suffices to specify an appropriate objective function and to place finite bounds on the optimized parameters. The efficacy of the proposed method has been tested on single machine as well as multimachine systems. The proposed method of tuning the PSS is an attractive alternative to conventional fixed gain stabilizer design as it retains the simplicity of the conventional PSS and still guarantees a robust acceptable performance over a wide range of operating and system condition. The method suggested in this thesis can be used for designing robust power system stabilizers for guaranteeing the required closed loop performance over a prespecified range of operating and system conditions. The simplicity in design and implementation of the proposed stabilizers makes them better suited for practical applications in real plants.

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed.

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed.

abstract: An important operating aspect of all transmission systems is power system stability and satisfactory dynamic performance. The integration of renewable resources in general, and photovoltaic resources in particular into the grid has created new engineering issues. A particularly problematic operating scenario occurs when conventional generation is operated at a low level but photovoltaic solar generation is at a high level. Significant solar photovoltaic penetration as a renewable resource is becoming a reality in some electric power systems. In this thesis, special attention is given to photovoltaic generation in an actual electric power system: increased solar penetration has resulted in significant strides towards meeting renewable portfolio standards. The impact of solar generation integration on power system dynamics is studied and evaluated. This thesis presents the impact of high solar penetration resulting in potentially problematic low system damping operating conditions. This is the case because the power system damping provided by conventional generation may be insufficient due to reduced system inertia and change in power flow patterns affecting synchronizing and damping capability in the AC system. This typically occurs because conventional generators are rescheduled or shut down to allow for the increased solar production. This problematic case may occur at any time of the year but during the springtime months of March-May, when the system load is low and the ambient temperature is relatively low, there is the potential that over voltages may occur in the high voltage transmission system. Also, reduced damping in system response to disturbances may occur. An actual case study is considered in which real operating system data are used. Solutions to low damping cases are discussed and a solution based on the retuning of a conventional power system stabilizer is given in the thesis. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2015