State estimation is an important tool for power system monitoring and the present study involves integrating phasor measurement units in the state estimation process. Based on measurements taken throughout the network, the role of a state estimator is to estimate the state variables of the power system while checking that these estimates are consistent with the measurement set. In the case of power system state estimation, the state variables are the voltage phasors at each network bus.\ The classical state estimator currently used is based on SCADA (Supervisory Control and Data Acquisition) measurements. Weaknesses of the SCADA measurement system are the asynchronicity of the measurements, which introduce errors in the state estimation results during dynamic events on the electrical network.\ Wide-area monitoring systems, consisting of a network of Phasor Measurement Units (PMU) provide synchronized phasor measurements, which give an accurate snapshot of the monitored part of the network at a given time. The objective of this thesis is to integrate PMU measurements in the state estimator. The proposed state estimators use PMU measurements exclusively, or both classical and PMU measurements.\ State estimation is particularly useful to filter out measurement noise, detect and eliminate bad data. A sensitivity analysis to measurement errors is carried out for a state estimator using only PMU measurements and a classical state estimator. Measurement errors considered are Gaussian noise, systematic errors and asynchronicity errors. Constraints such as zero injection buses are also integrated in the state estimator. Bad data detection and elimination can be done before the state estimation, as in pre-estimation methods, or after, as in post-estimation methods. For pre-estimation methods, consistency tests are used. Another proposed method is validation of classical measurements by PMU measurements. Post-estimation is applied to a measurement set which has asynchronicity errors. Detection of a systematic error on one measurement in the presence of Gaussian noise is also analysed. \ The state estimation problem can only be solved if the measurements are well distributed over the network and make the network observable. Observability is crucial when trying to solve the state estimation problem. A PMU placement method based on metaheuristics is proposed and compared to an integer programming method. The PMU placement depends on the chosen objective. A given PMU placement can provide full observability or redundancy. The PMU configuration can also take into account the zero injection nodes which further reduce the number of PMUs needed to observe the network. Finally, a method is proposed to determine the order of the PMU placement to gradually extend the observable island. \ State estimation errors can be caused by erroneous line parameter or bad calibration of the measurement transformers. The problem in both cases is to filter out the measurement noise when estimating the line parameters or calibration coefficients and state variables. The proposed method uses many measurement samples which are all integrated in an augmented state estimator which estimates the voltage phasors and the additional parameters or calibration coefficients.

With the development of the power grid into an automated system, phasor measurement units and phasor data concentrators are essential for real time control of the system. PMUs are time synchronized throughout the power system and take sample measurements in very small windows of time. Phasor Data Concentrators accept PMU data and time align the data so that a snapshot of the power system can be viewed in real time. It is unfeasible to possess enough real PMUs to thoroughly test PDCs, thus a Real Time PMU Simulator is desired. It is possible to implement a UNIX based PMU simulator that can emulate the behavior of real PMUs, while also allowing the user to alter the Synchrophasor data to test the response of a PDC. GPS is used to synchronize a UNIX machine to UTC time to match that of a real PMU. In this way, the PMU simulator will accurately behave as a PMU. This PMU data can be sent to PDCs to test the response of the device. To test extremes of the PDC, alterations were made to the PMU software to send irregular data to a PDC. The results conclude that the open source iPDC software is capable of being used for latency testing, sending late data frames, as well as sending corrupted data. The PMU simulator proved to be successful in the area of PDC testing. The purpose of this thesis is to demonstrate how the iPDC software can be implemented to test PDC's. / Master of Science

Synchrophasor Measurement Units (PMUs) are devices that can not only measure but also time stamp voltage, current, frequency, among others. PMUs take these synchronized measurements as fast as 60 times per second; compared with the traditional 2-4 second SCADA measurements, PMUs bring a much clear and real-time picture of what is happening in the power system. PMUs have been increasingly deployed across transmission power grids worldwide. In the USA this is primarily done by utilities through projects sponsored mainly by SIGS and Smart Grid grants. There are different applications that synchrophasors can provide, including off-line and real-time applications. However, due to budget constraints, technology development and characteristics specific to each system, not all applications are equally suitable and essential for all electric power systems. This thesis provides a method for PMU applications prioritization based on the analysis and results of wide area disturbance events. / Master of Science

Esta trabalho apresenta a análise e implementação de uma técnica inteligente, o algoritmo genético (AG), para implementação de unidades de medição fasoriais, denominadas PMUs (Phasor Measurement Units). A disponibilidade dos fasores em diversos pontos de um sistema elétrico de potência (SEP) é importante, tanto para monitoramento quanto para controle, proteção e estudo do sistema. Entretanto, a obtenção de tais fasores só têm sentido se os mesmos possuírem o mesmo referencial no tempo. Este referencial é conseguido através de sinais de satélites GPS (Global Positioning System) que sincronizam as PMUs instaladas nos pontos de interesse. Existe uma vasta quantidade de m´métodos que podem ser utilizados para que, de posse das formas de onda discretizadas de tensão e corrente, estime-se os fasores correspondentes e as frequências locais. Este projeto apresenta os AGs como ferramenta de estimação para a obtenção de uma PMU com todas as vantagens relativas a tais algoritmos. Além disso, uma versão do AG que utiliza menos recursos computacionais , o algoritmo genético compacto (AGc) também será estudado. Um estudo norteado pela norma internacional C37.118 compara o desempenho dos AGs com dois métodos tradicionais de medição fasorial, um baseado na transformada discreta de Fourier e outro baseado em um filtro phase-locked loop. Dados sintéticos e provenientes de simulações são utilizados para avaliar o desempenho dos algoritmos desenvolvidos. Para tirar vantagem da natureza paralela dos algoritmos genéticos, um estudo da implementação do AGc em FPGA (field programmable gate array) utilizando a linguagem VHDL e realizado a fim de estudar a implementação embarcada em PMUs. / This work presents the implementation and analysis of an intelligent technique, the genetic algorithm (GA), for the implementation of phasor measurement units (PMUs). The estimation of phasors in several spots in an electrical power system is important for the monitoring, control, protection and study of this system. However, these phasors must be in a common time reference in order to be usefull. This reference is achieved by using signals provided by the Global Positioning System (GPS) that synchronize the PMUs installed in the system. There are several techniques that can be used to estimate the phasors and local frequency using current and voltage wave signals. This project introduces the GAs as a phasor estimation tool applied to PMUs. Besides that, a version of the GA that demands less computational resources, the compact Genetic Algorithm is studied and implemented. A detailed study is performed using the international standard C37.118 as a guide comparing the GAs with two traditional techniques. The two traditional techniques are based on the DFT (Discrete Fourier transform) and a phaselocked loop filter (PLL). Synthetic and simulated data is used to evaluate the performance of the implemented algorithms. In order to take advantage of the parallel behavior of the genetic algorithms, a study of its implementation in FPGA (field programmable gate array) using the VHDL language is performed to make the genetic algorithms useful in real PMUs.

Esta trabalho apresenta a análise e implementação de uma técnica inteligente, o algoritmo genético (AG), para implementação de unidades de medição fasoriais, denominadas PMUs (Phasor Measurement Units). A disponibilidade dos fasores em diversos pontos de um sistema elétrico de potência (SEP) é importante, tanto para monitoramento quanto para controle, proteção e estudo do sistema. Entretanto, a obtenção de tais fasores só têm sentido se os mesmos possuírem o mesmo referencial no tempo. Este referencial é conseguido através de sinais de satélites GPS (Global Positioning System) que sincronizam as PMUs instaladas nos pontos de interesse. Existe uma vasta quantidade de m´métodos que podem ser utilizados para que, de posse das formas de onda discretizadas de tensão e corrente, estime-se os fasores correspondentes e as frequências locais. Este projeto apresenta os AGs como ferramenta de estimação para a obtenção de uma PMU com todas as vantagens relativas a tais algoritmos. Além disso, uma versão do AG que utiliza menos recursos computacionais , o algoritmo genético compacto (AGc) também será estudado. Um estudo norteado pela norma internacional C37.118 compara o desempenho dos AGs com dois métodos tradicionais de medição fasorial, um baseado na transformada discreta de Fourier e outro baseado em um filtro phase-locked loop. Dados sintéticos e provenientes de simulações são utilizados para avaliar o desempenho dos algoritmos desenvolvidos. Para tirar vantagem da natureza paralela dos algoritmos genéticos, um estudo da implementação do AGc em FPGA (field programmable gate array) utilizando a linguagem VHDL e realizado a fim de estudar a implementação embarcada em PMUs. / This work presents the implementation and analysis of an intelligent technique, the genetic algorithm (GA), for the implementation of phasor measurement units (PMUs). The estimation of phasors in several spots in an electrical power system is important for the monitoring, control, protection and study of this system. However, these phasors must be in a common time reference in order to be usefull. This reference is achieved by using signals provided by the Global Positioning System (GPS) that synchronize the PMUs installed in the system. There are several techniques that can be used to estimate the phasors and local frequency using current and voltage wave signals. This project introduces the GAs as a phasor estimation tool applied to PMUs. Besides that, a version of the GA that demands less computational resources, the compact Genetic Algorithm is studied and implemented. A detailed study is performed using the international standard C37.118 as a guide comparing the GAs with two traditional techniques. The two traditional techniques are based on the DFT (Discrete Fourier transform) and a phaselocked loop filter (PLL). Synthetic and simulated data is used to evaluate the performance of the implemented algorithms. In order to take advantage of the parallel behavior of the genetic algorithms, a study of its implementation in FPGA (field programmable gate array) using the VHDL language is performed to make the genetic algorithms useful in real PMUs.

Previously, conventional state estimation techniques have been used for state estimation in power systems. These conventional methods are based on steady state models. As a result of this, power system dynamics during disturbances or transient conditions are not adequately captured. This makes it challenging for operators in control centers to perform visual tracking of the system, proper fault diagnosis and even take adequate preemtive control measures to ensure system stability during voltage dips. Another challenge is that power systems are nonlinear in nature. There are multiple power components in operation at any given time making the system highly dynamic in nature. Consequently, the need to study and implement better dynamic estimation tools that capture system dynamics during disturbances and transient conditions is necessary. For this thesis work, we present the Unscented Kalman Filter (UKF) which integrates Unscented Transformation (UT) to Kalman Filtering. Our algorithm takes as input the output of a synchronous machine modeled in MATLAB/Simulink as well as data from a PMU device assumed to be installed at the terminal bus of the synchronous machine, and estimate the dynamic states of the system using a Kalman Filter. We have presented a detailed and analytical study of our proposed algorithm in estimating two dynamic states of the synchronous machine, rotor angle and rotor speed. Our study and result shows that our proposed methodology has better efficiency when compared to the results of the Extended Kalman Filter (EKF) algorithm in estimating dynamic states of a power system.  Our results are presented and analyzed on the basis of how accurately the algorithm estimates the system states following various simulated transient and small-signal disturbances.

The penetration of renewable energy sources has increased significantly in recent years due to the ongoing depletion of conventional resources and the transition to a low carbon energy system. Renewable energy sources such as wind energy are highly intermittent and unpredictable in nature, which makes the operation of the power grid more dynamic and therefore more complex. In order to operate the power system reliably under such conditions, Phasor Measurement Units (PMUs) through the use of satellite technology can offer a state-of-the-art Wide Area Monitoring System (WAMS) for improving power system monitoring, control and protection. They can improve the operation by providing highly precise and synchronised measurements near to real-time with higher frequency and accuracy. In order to achieve such objectives, a high-speed and reliable communications infrastructure is required to transfer time-critical PMU data from remote locations to the control centre. The signals measured by PMUs are transmitted across Local and Wide Area Networks, where they may encounter excessive delays. Signal delays can have a disruptive effect and make applications at best inefficient and at worse ineffective. The main research contribution of this thesis is the performance evaluation of communication infrastructures for WAMS. The evaluation begins from inside substations and continues over wide areas from substations to control centre. Through laboratory-based investigations and simulations, the performance of communications infrastructure in a typical power system substation has been analysed. In addition, the performance evaluation of WAMS communications infrastructure has been presented. In the modelling and analysis, an existing WAMS as installed on the GB transmission system has been considered. The actual PMU packets as received at the Phasor Data Concentrator (PDC) were captured for latency analysis. A novel algorithmic procedure has been developed and implemented to automate the large-scale latency calculations. Furthermore, the internal delays of PMUs have been investigated, determined and analysed. Subsequently, the WAMS has been simulated and detailed comparisons have been performed between the simulated model results and WAMS performance data captured from the actual WAMS. The validated WAMS model has been used for analysing possible future developments as well as to test newly proposed mechanisms, protocols, etc. in order to improve the communications infrastructure performance.

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.

Wide-area monitoring for the power system is a key tool for preventing the power system from system wide failure. State Estimation (SE) is an essential and practical monitoring tool that has been widely used to provide estimated values for each quantity within energy management systems (EMS) in the control center. However, monitoring larger power systems coordinated by regional transmission operators has placed an enormous operational burden on current SE techniques. A distributed state estimation (DSE) algorithm with a hierarchical structure designed for the power system industry is much more computationally efficient and robust especially for monitoring a wide-area power system. Moreover, considering the deregulation of the power system industry, this method does not require sensitive data exchange between smaller areas that may be competing entities. The use of phasor measurement units (PMUs) in the SE algorithm has proven to improve the performance in terms of accuracy and converging speed. Being able to synchronize the measurements between different areas, PMUs are perfectly suited for distributed state estimation. This dissertation investigates the benefits of the DSE using PMU over a serial state estimator in wide area monitoring. A new method has been developed using available PMU data to calculate the reference angle differences between decomposed power systems in various situations, such as when the specific PMU data of the global slack bus cannot be obtained. The algorithms were tested on six bus, I standard 30 bus and I 118-bus test cases. The proposed distributed state estimator has also been implemented in a test bed to work with a power system real-time digital simulator (RTDS) that simulates the physical power system. PMUs made by SEL and GE are used to provide real-time inputs to the distributed state estimator. Simulation results demonstrated the benefits of the PMU and distributed SE techniques. Additionally a constructed test bed verified and validated the proposed algorithms and can be used for different smart grid tests.

In a typical utility control center, there could be hundreds of applications running to take care of day-to-day functionality. In many cases, these applications are custom-built by different vendors. With the expectation for high reliability of the electric power grid, many utilities are increasingly moving towards sharing data with each other and with security coordinators. But this data exchange is hampered by incompatible electrical applications built on proprietary data formats and file systems. Electric Power Research Institute's (EPRI‟s) Common Information Model (CIM) was envisioned as a one-sizeits-all data model to remove incompatibility between applications. This research work utilizes the CIM models to exchange power system models and measurements between a state estimator application and sensor web application. The CIM was further extended to include few unique devices from the shipboard medium voltage DC power system. Finally, a wide-area monitoring test bed was set up at MSU to perform wide-area monitoring using phasor measurement units (PMU). The outputs from the Phasor Data Concentrator (PDC) were then converted into CIM/XML documents to make them compatible with the sensor web application. These applications have created advancements in power system monitoring and interoperability