Contemporary power networks are gradually expanding incorporating new sources of electrical energy and power electronic based devices. The major stability issue in large interconnected power systems is the lightly damped interarea oscillations. In the light of growth of their incidents there are increased concerns about the effectiveness of current control devices and control systems in maintaining power system stability. This thesis presents a Wide Area Measurement System (WAMS) based control scheme to enhance power system stability. The control scheme has a hierarchical (two-level) structure comprising a Supplementary Wide-Area Controller (SWAC) built on top of existing Power System Stabilisers (PSSs). The SWAC's focus is on stabilising the critical interarea oscillations in the system while leaving local modes to be controlled entirely by local PSSs. Both control systems in the two levels work together to maintain system stability. The scheme relies on synchronised measurements supplied by Phasor Measurement Units (PMUs) through the WAMS and the only cost requirement is for the communication infrastructure which is already available, or it will be in the near future. A novel linear quadratic Gaussian (LQG) control design approach which targets the interarea modes directly is introduced in this thesis. Its features are demonstrated through a comparison with the conventional method commonly used in power system damping applications. The modal LQG approach offers simplicity and flexibility when targeting multiple interarea modes without affecting local modes and local controllers, thus making it highly suitable to hierarchical WAMS based control schemes. Applicability of the approach to large power systems is demonstrated using different scenarios of model order reduction. The design approach incorporates time delays experienced in the transmission of the SWAC's input/output signals. Issues regarding values of time delays and required level of detail in modelling time delays are thoroughly discussed. Three methods for selection of input/output signals for WAMS based damping controllers are presented and reviewed. The first method uses modal observability/controllability factors. The second method is based on the Sequential Orthogonalisation (SO) algorithm, a tool for the optimal placement of measurement devices. Its application is extended and generalised in this thesis to handle the problem of input/output signal selection. The third method combines clustering techniques and modal factor analysis. The clustering method uses advanced Principal Component Analysis (PCA) where its draw backs and limitations, in the context of power system dynamics' applications, are overcome. The methods for signal selection are compared using both small signal and transient stability analysis to determine the best optimal set of signals. Enhancement of power system stability is demonstrated by applying the proposed WAMS based control scheme on the New England test system. The multi-input multi-output (MIMO) WAMS based damping controller uses a reduced set of input/output signals and is designed using the modal LQG approach. Effectiveness of the control scheme is comprehensively assessed using both small signal and transient stability analysis for different case studies including small and large disturbances, changes in network topology and operating condition, variations in time delays, and failure of communication links.

Master of Science / Department of Electrical and Computer Engineering / Shelli Starrett / Variability in power systems is increasing due to pushing the system to limits for economic purposes, the inclusion of new energy sources like wind turbines and photovoltaic, and the introduction of new types of loads such as electric vehicle chargers. In this new environment, system monitoring and control must keep pace to insure system stability and reliability on a wide area scale. Phasor measurement unit technology implementation is growing and can be used to provide input signals to new types of control. Fuzzy logic based power system stabilizer (PSS) controllers have also been shown effective in various studies. This thesis considers several choices of input signals, composed assuming phasor measurement availability, for fuzzy logic-based controllers. The purpose of the controller is to damp power systems’ low frequency oscillations. Nonlinear transient simulation results for a 4-machine two-area system and 50 machine system are used to compare the effects of input choice and controller type on damping of system oscillations. Reactive power in the system affects voltage, which in turn affects system damping and dynamic stability. System stability and damping can be enhanced by deploying SVC controllers properly. Different types of power system variables play critical role to damp power swings using SVC controller. A fuzzy logic based static var compensator (SVC) was used near a generator to damp these electromechanical oscillations using different PMU-acquired inputs. The goal was again improve dynamic stability and damping performance of the system at local and global level. Nonlinear simulations were run to compare the damping performance of different inputs on the 50 machine system.

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Indiana University-Purdue University Indianapolis (IUPUI) / The thesis extends the work done in [1] [2] by Rovnyak, et al. where the authors have described about transient event prediction and response based one shot control using decision trees trained and tested in a 176 bus model of WECC power system network. This thesis contains results from rigorous simulations performed to measure robustness of the existing one shot control subjected to missing PMU's data ranging from 0-10%. We can divide the thesis into two parts in which the first part includes understanding of the work done in [2] using another set of one-shot control combinations labelled as CC2 and the second part includes measuring their robustness while assuming missing PMU's data. Previous work from [2] involves use of decision trees for event detection based on different indices to classify a contingency as a 'Fault' or 'No fault' and another set of decision trees that decides either to actuate 'Control' or 'No control'. The actuation of control here means application of one-shot control combination to possibly bring the system to a new equilibrium point which would otherwise attain loss of synchronism. The work done in [2] also includes assessing performance of the one shot control without event detection. The thesis is organized as follows- Chapter 1 of the thesis highlights the effect of missing PMUs' data in a power system network and the need to address them appropriately. It also provides a general idea of transient stability and response of a transient fault in a power system. Chapter 2 forms the foundation of the thesis as it describes the work done in [1] [2] in detail. It describes the power system model used, contingencies set, and different indices used for decision trees. It also describes about the one shot control combination (CC1) deduced by Rovnyak, et.al. of which performance is later tested in this thesis assuming different missing data scenarios. In addition to CC1, the chapter also describes another set of control combination (CC2) whose performance is also tested assuming the same missing data scenarios. This chapter also explains about the control methodology used in [2]. Finally the performance metrics of the DTs are explained at the end of the chapter. These are the same performance metrics used in [2] to measure the robustness of the one shot control. Chapter 2 is thus more a literature review of previous work plus inclusion of few simulation results obtained from CC2 using exactly the same model and same control methodology. Chapter 3 describes different techniques of handling missing data from PMUs most of which have been used in and referred from different previous papers. Finally Chapter 4 presents the results and analysis of the simulation. The thesis is wrapped up explaining future enhancements and room for improvements.

A variety of factors such as increasing electrical energy demand, slow expansion of transmission infrastructures, and electric energy market deregulation, are forcing utilities and system operators to operate power systems closer to their design limits. Operating under stressed regimes can have a detrimental effect on the rotor-angle stability of the system. This stability reduction is often reflected by the emergence or worsening of poorly damped low-frequency electromechanical oscillations. Without appropriate measures these can lead to costly blackouts. To guarantee system security, operators are sometimes forced to limit power transfers that are economically beneficial but that can result in poorly damped oscillations. Controllers that damp these oscillations can improve system reliability by preventing blackouts and provide long term economic gains by enabling more extensive utilization of the transmission infrastructure. Previous research in the use of artificial neural network-based intelligent controllers for power system damping control has shown promise when tested in small power system models. However, these controllers do not scale-up well enough to be deployed in realistically-sized power systems. The work in this dissertation focuses on improving the scalability of intelligent power system stabilizing controls so that they can significantly improve the rotor-angle stability of large-scale power systems. A framework for designing effective and robust intelligent controllers capable of scaling-up to large scale power systems is proposed. Extensive simulation results on a large-scale power system simulation model demonstrate the rotor-angle stability improvements attained by controllers designed using this framework.