The vision of the smart grid is predicated upon pervasive use of modern digital communication techniques in today's power system. As wide area measurements and control techniques are being developed and deployed for a more resilient power system, the role of communication networks is becoming prominent. Advanced communication infrastructure provides much wider system observability and enables globally optimal control schemes. Wide area measurement and monitoring with Phasor Measurement Units (PMUs) or Intelligent Electronic Devices (IED) is a growing trend in this context. However, the large amount of data collected by PMUs or IEDs needs to be transferred over the data network to control centers where real-time state estimation, protection, and control decisions are made. The volume and frequency of such data transfers, and real-time delivery requirements mandate that sufficient bandwidth and proper delay characteristics must be ensured for the correct operations. Power system dynamics get influenced by the underlying communication infrastructure. Therefore, extensive integration of power system and communication infrastructure mandates that the two systems be studied as a single distributed cyber-physical system. This dissertation proposes a global event-driven co-simulation framework, which is termed as GECO, for interconnected power system and communication network. GECO can be used as a design pattern for hybrid system simulation with continuous/discrete sub-components. An implementation of GECO is achieved by integrating two software packages: PSLF and NS2 into the framework. Besides, this dissertation proposes and studies a set of power system applications which can be only properly evaluated on a co-simulation framework like GECO, namely communication-based distance relay protection, all-PMU state estimation and PMU-based out-of-step protection. All of them take advantage of interplays between the power grid and the communication infrastructure. The GECO experiments described in this dissertation not only show the efficacy of the GECO framework, but also provide experience on how to go about using GECO in smart grid planning activities. / Ph. D.

This dissertation aims to develop decision-making tools that aid power grid operators in mitigating extreme events. Two distinct areas are focused on: a) improving grid performance after a severe disturbance, and b) enhancing grid monitoring to facilitate timely preventive actions. The first part of the dissertation presents a proactive islanding strategy to split the bulk power transmission system into smaller self-adequate islands in order to arrest the propagation of cascading failures after an event. Heuristic methods are proposed to determine in what sequence should the island boundary lines be disconnected such that there are no operation constraint violations. The idea of optimal partitioning is further extended to the distribution network. A planning problem for determining which parts of the existing distribution grid can be converted to microgrids is formulated. This partitioning formulation addresses safety limits, uncertainties in load and generation, availability of grid-forming units, and topology constraints such as maintaining network radiality. Microgrids help maintain energy supply to critical loads during grid outages, thereby improving resilience. The second part of the dissertation focuses on wide-area monitoring using Phasor Measurement Unit (PMU) data. Strategies for data imputation and prediction exploiting the spatio-temporal correlation in PMU measurements are outlined. A deep-learning-based methodology for identifying the location of temporary power systems faults is also illustrated. As severe weather events become more frequent, and the threats from coordinated cyber intrusions increase, formulating strategies to reduce the impact of such events on the power grid becomes important; and the approaches outlined in this work can find application in this context. / Doctor of Philosophy / The modern power grid faces multiple threats, including extreme-weather events, solar storms, and potential cyber-physical attacks. Towards the larger goal of enhancing power systems resilience, this dissertation develops strategies to mitigate the impact of such extreme events. The proposed schemes broadly aim to- a) improve grid performance in the immediate aftermath of a disruptive event, and b) enhance grid monitoring to identify precursors of impending failures. To improve grid performance after a disruption, we propose a proactive islanding strategy for the bulk power grid, aimed at arresting the propagation of cascading failures. For the distribution network, a mixed-integer linear program is formulated for identifying optimal sub-networks with load and distributed generators that may be retrofitted to operate as self-adequate microgrids, if supply from the bulk power systems is lost. To address the question of enhanced monitoring, we develop model-agnostic, computationally efficient recovery algorithms for archived and streamed data from Phasor Measurement Units (PMU) with data drops and additive noise. PMUs are highly precise sensors that provide high-resolution insight into grid dynamics. We also illustrate an application where PMU data is used to identify the location of temporary line faults.

The research topics presented in this dissertation focus on validation of customer-level voltage synchrophasor data for transmission system analysis, detection and categorization of power system events as measured by phasor measurement units (PMUs), and identification of the influence of power system conditions (wind power, daily and seasonal load variation) on low-frequency oscillations. Synchrophasor data can provide information across entire power systems but obtaining the data, handling the large dataset and developing tools to extract useful information from it is a challenge. To overcome the challenge of obtaining data, an independent synchrophasor network was created by taking synchrophasor measurements at customer-level voltage. The first objective is to determine if synchrophasor data taken at customer-level voltage is an accurate representation of power system behavior. The validation process was started by installing a transmission level (69 kV) PMU. The customer-level voltage measurements were validated by comparison of long term trends and low-frequency oscillations estimates. The techniques best suited for synchrophasor data analysis were identified after a detailed study and comparison. The same techniques were also applied to detect power system events resulting in the creation of novel categories for numerous events based on shared characteristics. The numerical characteristics for each category and the ranges of each numerical characteristic for each event category are identified. The final objective is to identify trends in power system behavior related to wind power and daily and seasonal variations by utilizing signal processing and statistical techniques. / text

In the Nordic power network, the existence of poorly damped low-frequency inter-area oscillations (LFIOs) has long affected stability constraints, and thereby, limited power transfer capacity. Adequate damping of inter-area modes is, thus, necessary to secure system operation and ensure system reliability while increasing power transfers. Power system stabilizers (PSS) is a prevalent means to enhance the damping of such modes. With the advent of phasor measurement units (PMUs), it is expected that wide-area damping control (WADC), that is, PSS control using wide-area measurements obtained from PMUs, would effectively improve damping performance in the Nordic grid, as well as other synchronous interconnected systems. Numerous research has investigated one ``branch'' of the problem, that is, PSS design using various control schemes. Before addressing the issue of controller design, it is important to focus on developing proper understanding of the ``root'' of the problem: system-wide oscillations, their nature, behavior and consequences. This understanding must provide new insight on the use of PMUs for feedback control of LFIOs. The aim of this thesis is, therefore, to lay important concepts necessary for the study of power system small signal stability analysis that considers the availability of synchrophasors as a solid foundation for further development and implementation of ideas and related applications. Particularly in this study, the focus is on the application addressed damping controller design and implementation. After a literature review on the important elements for wide-area damping control (WADC), the thesis continues with classical small signal stability analysis of an equivalent Nordic model; namely, the KTH-NORDIC32 which is used as a test system throughout the thesis. The system's inter-area oscillations are identified and a sensitivity analysis of the network variables directly measured by synchrophasors is evaluated. The concept of network modeshapes, which is used to relate the dynamical behavior of power systems to the features of inter-area modes, is elaborated. Furthermore, this network modeshape concept is used to determine dominant inter-area oscillation paths, the passageways containing the highest content of the inter-area oscillations. The dominant inter-area paths are illustrated with the test system. The degree of persistence of dominant paths in the study system is determined through contingency studies. The properties of the dominant paths are used to construct feedback signals as input to the PSS. Finally, to exemplify the use of the dominant inter-area path concept for damping control, the constructed feedback signals are implemented in a PSS modulating the AVR error signal of a generator on an equivalent two-area model, and compared with that of conventional speed signals.

There is an ever increasing demand of electricity and to meet this demand, installation of new transmission and distribution lines is required. This task requires a significant investment and consent from the respective authorities. An alternative is to utilize maximum capability of the existing lines. Static line ratings are based on a conservative estimate, which means that on most occasions, the actual capacity of lines is much higher than the static line ratings. In order to provide a solution to this problem, this thesis introduces an approach that has been developed to utilize real time weather conditions, conductor sag data and the actual line loading of the conductor from PMU to provide dynamic line ratings for active distribution networks. The application has been developed in LabVIEW environment which provides a user friendly front panel where real-time ampacity can be seen as a waveform while being compared to the actual line loading.  The developed application has been tested on the reference grid created for IDE4L project. The ampacity calculation method introduced here makes use of real-time data available through a real-time simulator in SmarTS lab at KTH, Sweden. / Det är ett ökande behov av elektricitet och för att möta detta behövet, installation av nya transmission och distributionsledningar behövs. Denna utbyggnad kräver ett stort engagemang och förståelse från ansvariga grupper. Ett alternativ är att utnyttja max-kapaciteten på redan befintliga ledningar. Installerade ledningar har räknats på ett konservativt sätt, vilket innebär att det vid vissa tillfällen går att öka belastingen på på dessa. För att ge en lösning på detta problem, introducerar den här avhandlingen en metod för att använda realtids-väderdata, tabeller för ledningarnas utvidgning och realtids-belastningsdata från PMU för att framställa dynamisk data för aktiva distributions-nätverk. Applikationen har utvecklas i LabVIEW-miljön som har ett användarvänligt GUI, där “Real-time ampacity” kan ses som en vågform medans den jämförs mot den faktiska belastningen på ledningen.  Den utvecklade appliktionen har testats på referens-miljön som skapts för IDE4L projektet. “Ampacity calculation metoden” som introduceras här använder sig av realtidsdata som görs tillgänglig igenom en realtids-simulator i SmarTSlab på Kungliga Tekniska Högskolan i Sverige.

Software Defined Networking (SDN) has gained popularity and attractiveness in the past years’ thanks to its dynamic and programmable nature. The possibility to decouple the data plane and control plane allows for the implementation of Internet networks in an innovative way. Thanks to its ease in changing flow rules in network switches, SDN allows network resources optimization. In the case of critical applications, an essential aspect is to ensure connectivity on the network even in case of link failures. Even when a failure causes an interruption of connectivity, the challenge also stays in recovering as fast as possible. Nonetheless, the SDN controller should have the policy to decide which pairs of end-hosts to disable connectivity when there is a shortage of resources to keep the most important connections active. In this thesis, we developed a proactive-reactive SDN controller coded in Python that copes with restoring end-hosts connectivity as fast as possible. The controller prioritizes the couples of end-hosts that need connectivity based on their importance. During a shortage of network resources, the connectivity of pairs of end-hosts with low importance is disabled, and the connectivity between the most important couples can be ensured. We tested our solution with a reactive-only SDN controller and a proactive-reactive SDN controller that does not consider any prioritization order between end-hosts connectivity. Both the benchmark SDN controllers were developed in the thesis. Experiments were run on the same network topology, with the same couple of endhosts involved. The comparison between the proactive-reactive and reactive-only controllers showed the first one to be faster in restoring the connectivity after a failure. It saves time restoring the connectivity and has fewer packets lost under certain conditions in the relationship between the switch-to-switch and the switchto-controller transmission delay. The comparison between the proactive-reactive iii controller and the controller with no prioritization confirms that without an ordered queue of priorities, it may be the most important couple of end-hosts to lose connectivity in case of shortages of network resources. To simulate a realistic scenario, the project considers the case study of electric power transmission networks using SDN. In particular, the focus is on reconnecting Phasor Measurement Unit (PMU)s to the power grid to ensure system observability. During our experiments, we adopted the typical measurement transmission frequency used by PMUs (50Hz). The SDN switches are deployed with P4, and the SDN controller is coded in Python. Furthermore, it exploits P4Runtime to communicate with the switches in run-time. / Software Defined Networking (SDN) har vunnit popularitet och attraktionskraft under de senaste åren tack vare sin dynamiska och programmerbara natur. Möjligheten att frikoppla dataplanet från kontrollplanet gör det möjligt att genomföra Internetnät på ett innovativt sätt. Tack vare att det är lätt att ändra flödesreglerna i nätverksväxlar gör SDN det möjligt att optimera nätverksresurserna. När det gäller kritiska tillämpningar är en viktig aspekt att säkerställa konnektiviteten i nätet även vid länkfel. Även när ett fel orsakar ett avbrott i konnektiviteten är utmaningen också att återhämta sig så snabbt som möjligt. Trots detta bör SDNstyrenheten ha en policy för att avgöra vilka par av slutvärdar som ska inaktivera anslutningen när det råder brist på resurser för att hålla de viktigaste anslutningarna aktiva. I den här avhandlingen har vi utvecklat en proaktiv-reaktiv SDN-styrenhet kodad i Python som klarar av att återställa slutvärdarnas anslutning så snabbt som möjligt. Styrenheten prioriterar paren av slutvärdar som behöver anslutning utifrån deras betydelse. Vid brist på nätverksresurser inaktiveras anslutningen för par av slutvärdar med låg betydelse, och anslutningen mellan de viktigaste paren kan säkerställas. Vi testade vår lösning med en enbart reaktiv SDN-styrenhet och en proaktiv-reaktiv SDN-styrenhet som inte tar hänsyn till någon prioriteringsordning mellan slutvärdarnas konnektivitet. Båda riktmärkeskontrollerna SDN utvecklades i avhandlingen. Experimenten genomfördes på samma nätverkstopologi med samma antal slutvärdar. Jämförelsen mellan den proaktivt-reaktiva och den enbart reaktiva kontrollören visade att den förstnämnda kontrollören var snabbare när det gäller att återställa anslutningen efter ett fel. Den sparar tid för att återställa anslutningen och har färre förlorade paket under vissa förhållanden i förhållandet mellan överföringsfördröjningen från switch till switch och från switch till styrenhet. Jämförelsen mellan den proaktiva-reaktiva styrenheten och v styrenheten utan prioritering bekräftar att utan en ordnad kö av prioriteringar kan det vara det viktigaste paret av slutvärdar som förlorar konnektiviteten vid brist på nätverksresurser. För att simulera ett realistiskt scenario används SDN i projektet som fallstudie för elöverföringsnät. Fokus ligger särskilt på att återansluta Phasor Measurement Unit (PMU)s till elnätet för att säkerställa systemets observerbarhet. Under våra experiment antog vi den typiska överföringsfrekvensen för mätningar som används av PMUs (50Hz). SDN-växlarna installeras med P4, och SDN-styrenheten är kodad i Python. Dessutom utnyttjas P4Runtime för att kommunicera med växlarna i körtid.

Recent large-scale blackouts revealed that power systems around the world are far from the stability and reliability requirement as they suppose to be. The post-event analysis clarifies that one major reason of the interconnection blackout is lack of wide area information. Frequency dynamics is one of the most important parameters of an electrical power system. In order to understand power system dynamics effectively, accurately measured wide-area frequency is needed. The idea of building an Internet based real-time GPS synchronized wide area Frequency Monitoring Network (FNET) was proposed to provide the imperative dynamic information for the large-scale power grids and the implementation of FNET has made the synchronized observations of the entire US power network possible for the first time. The FNET system consists of Frequency Disturbance Recorders (FDR), which work as the sensor devices to measure the real-time frequency at 110V single-phase power outlets, and an Information Management System (IMS) to work as a central server to process the frequency data. The device comparison between FDR and commercial PMU (Phasor Measurement Unit) demonstrate the advantage of FNET. The web visualization tools make the frequency data available for the authorized users to browse through Internet. The research work addresses some preliminary observations and analyses with the field-measured frequency information from FNET. The original algorithms based on the frequency response characteristic are designed to process event detection, localization and unbalanced power estimation during frequency disturbances. The analysis of historical cases illustrate that these algorithms can be employed in real-time level to provide early alarm of abnormal frequency change to the system operator. The further application is to develop an adaptive under frequency load shedding scheme with the processed information feed in to prevent further frequency decline in power systems after disturbances causing dangerous imbalance between the load and generation. / Ph. D.

Renewable energy is playing an increasingly significant role in power system operation and stability assessment with its numerous penetration expansion. This is not only brought by its uncertain power output and inverter-based equipment structures but also its operation characteristics like Low Voltage Ride Through (LVRT). It is thus necessary to take these characteristics into consideration and further to find more adaptive schemes to implement them for more effective analysis and safer power system operation. All the aforementioned is based on the accurate identification of the system fundamental information. In this dissertation, a systematic approach is proposed to find the valid system model by estimating the transmission line parameters in the system with PMU measurements. The system transient stability assessment is conducted based on this validated model. The constrained stability region is estimated with Lyapunov functions family based method in the center of angles reference frame considering renewables LVRT as operation limits. In order to integrate the LVRT constraints, a polytopic inner approximation mechanism is introduced to linearize and organize the transformed constraints in state space, which brings much scalability to the whole process. From the voltage stability perspective, an approach to adaptively adjust LVRT settings of the renewable energy sources in the system is formulated to guarantee the system load margin and thus the voltage security. A voltage prediction method is introduced for critical renewable energy sources identification. Estimation methods based on interpolation and sensitivities are developed and conducted for saving computation effort brought by continuation power flows. Multiple test cases are studied utilizing the proposed approaches and results are demonstrated. / Doctor of Philosophy / Renewable energy utilization is continuously rising nowadays. They are clean but highly dependent on natural resources, which causes their uncertainty and intermittence in electric power output. The power system, on the other hand, is designed for schedulable and controllable power generators, which make the traditional methods for system operation and analysis of the system stability much less effective facing the trend of renewables integration. In this dissertation, a series of systematic approaches are proposed firstly identify the system parameters for more accurate system modeling through PMU measurements, then to assess the system transient stability considering the renewable energy sources operation limits, and finally to adaptively adjust these operation limit for improving the system voltage security. The operation limits are transferred into the form in terms of system states. Linearization and approximation methods are also introduced to enhance the scalability of the processes. Multiple test cases are studied with the proposed approaches and the results demonstrate their effectiveness and efficiency.

This study takes advantage of wide area measurements to propose a centralized nonlinear controller that acts on power system stabilizers, to cooperatively increase the damping of problematic small signal oscillations all over the system. The structure based on decision trees results in a simple, efficient, and dependable methodology that imposes much less computational burden than other nonlinear design approaches, making it a promising candidate for actual implementation by utilities and system operators. Details are given to utilize existing stabilizers while causing minimum changes to the equipment, and warranting improvement or at least no detriment of current system behavior. This enables power system stabilizers to overcome their inherent limitation to act only on the basis of local measurements to damp a single target frequency. This study demonstrates the implications of this new input on mathematical models, and the control functionality that is made available by its incorporation to conventional stabilizers. In preparation of the case of study, a heuristic dynamic reduction methodology is introduced that preserves a physical equivalent model, and that can be interpreted by any commercial software package. The steps of this method are general, versatile, and of easy adaptation to any particular power system model, with the aggregated value of producing a physical model as final result, that makes the approach appealing for industry. The accuracy of the resulting reduced network has been demonstrated with the model of the Central American System. / Ph. D.

Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-04-10T14:04:24Z No. of bitstreams: 1 renatoribeiroaleixo.pdf: 11717772 bytes, checksum: 92418eff47ec8bfa0e099a19d849c068 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-04-10T14:22:50Z (GMT) No. of bitstreams: 1 renatoribeiroaleixo.pdf: 11717772 bytes, checksum: 92418eff47ec8bfa0e099a19d849c068 (MD5) / Made available in DSpace on 2018-04-10T14:22:50Z (GMT). No. of bitstreams: 1 renatoribeiroaleixo.pdf: 11717772 bytes, checksum: 92418eff47ec8bfa0e099a19d849c068 (MD5) Previous issue date: 2018-03-01 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho tem como objetivo a proposta de uma Unidade de Medição Fasorial (do inglês, Phasor Measurement Unit)(PMU), de baixo custo, voltada para o monito-ramento da distribuição de energia elétrica. O medidor proposto pode ser conectado à rede de baixa tensão, possibilitando assim o monitoramento dos sistemas de dis-tribuição e transmissão de energia. O algoritmo de estimação fasorial que compõe o software embarcado do equipamento faz uso do filtro Savitzky-Golay como aproxima-ção da derivada, necessária no processo de estimação da frequência do componente fundamental do sinal. O hardware utilizado é composto pelo microprocessador ARM TM4C1294NCPDT da Texas Instruments, um módulo GPS NEO-6M da uBlox, um módulo Wi-Fi ESP8266, além de um circuito de condicionamento do sinal analógico. O sincronismo das medições realizadas é garantido graças ao sinal composto por um pulso por segundo fornecido pelo GPS. Para o envio dos dados gerados pelo medidor pro-posto, o protocolo definido na norma vigente para PMUs foi utilizado. As estimações podem ser armazenadas e vizualizadas em tempo real através de um software monitor de dados de sincrofasores. Os resultados contemplam os testes exigidos pela norma, avaliando-se o erro total da estimação do fasor, o erro de frequência e o erro de taxa de variação da frequência. Por último, a fim de se reafirmar o sincronismo existente entre as medições realizadas por mais de um equipamento, estimou-se os fasores e a frequência em pontos distintos do sistema 4 Barras do IEEE, simulado em tempo real no RTDS, onde pode-se observar a estimação correta da defasagem entre duas barras desse sistema. / The present work proposes of a low cost Phasor Measurement Unity (PMU), for monitoring the power distribution system. The proposed meter can be connected at the low voltage level, making possible the monitoring of the distribution system and the transmission system. The algorithm used to compute the phasor estimation that composes the embedded software in the equipment uses the Savitzky-Golay filter to approximate the differentiation process, necessary in the frequency estimation of the fundamental component of the signal. The hardware of the equipment is composed by a microprocessor AMR TM4C1294NCPDT of Texas Instruments, a uBlox GPS NEO-6M module, a Wi-Fi ESP8266 module and an analog conditioning circuit. The synchronism of the measurements is guaranteed due to a pulse per second signal from the GPS module. For the transmission of the data generated by the PMU, the protocol suggested by the standard is used. The estimated parameters can be visualized in real time through the Synchrophasor Data Monitor Software. The results contemplate the tests required by the IEEE standard C37.118.1 and the analyses of the total vector error, frequency error and rate of change of frequency error. Finally, to attest the synchronism between different PMUs, a test in a Real Time Digital Simulator (RTDS) was made, where the 4 bus IEEE system was simulated. The difference of the angles estimated for different buses was computed and the obtained values were according to the expected.