To date, the potential of on-line Dynamic Security Assessment (DSA) to monitor, alert, and enhance system security is constrained by the longer computational cycle time. Traditional techniques requiring extensive numerical computations make it challenging to complete the assessment within an acceptable time. Longer computational cycles produce obsolete security assessment results as the system operating point evolves continuously. This thesis presents a DSA algorithm, based on Transient Energy Function (TEF) method and machine learning, to enable frequent computational cycles in on-line DSA of power systems. The use of selected terms of the TEF as pre-processed input features for machine learning demonstrated the ability to successfully train a contingency-independent classifier that is capable of classifying stable and unstable operating points. The network is trained for current system topology and loading conditions. The classifier can be trained using a small dataset when the TEF terms are used as input features. The prediction accuracy of the proposed scheme was tested under the balanced and unbalanced faults with the presence of voltage sensitive and dynamic loads for different operating points. The test results demonstrate the potential of using the proposed technique for power system on-line DSA. Power system devices such as HVDC and FACTS can be included in the algorithm by incorporating the effective terms of a corresponding TEF. An on-line DSA system requires the integration of several functional components. The practicality of the proposed technique in terms of a) critical data communications aspects b) computational hardware requirements; and c) capabilities and limitations of the tools in use was tested using an implementation of an on-line DSA system. The test power system model was simulated using a real-time digital simulator. The other functional units were distributed over the Local Area Network (LAN). The implementation indicated that an acceptable computational cycle time can be achieved using the proposed method. In addition, the work carried out during this thesis has produced two tools that can be used for a) web-based automated data generation for power system studies; and b) testing of on-line DSA algorithms. / February 2017

This thesis presents a linearized technique to determine a risk-based index for dynamic security. The method is an extension to an existing technique in which the risk of steady state security is calculated using the mean and variance of load uncertainty. The proposed method is applied to calculate the risk indices for the New England 39 bus test system. The results obtained from the proposed method are validated against those estimated by Monte Carlo simulation. Both approaches produce virtually the same results for small load deviations.

This thesis presents a linearized technique to determine a risk-based index for dynamic security. The method is an extension to an existing technique in which the risk of steady state security is calculated using the mean and variance of load uncertainty. The proposed method is applied to calculate the risk indices for the New England 39 bus test system. The results obtained from the proposed method are validated against those estimated by Monte Carlo simulation. Both approaches produce virtually the same results for small load deviations.

abstract: On-line dynamic security assessment (DSA) analysis has been developed and applied in several power dispatching control centers. Existing applications of DSA systems are limited by the assumption of the present system operating conditions and computational speeds. To overcome these obstacles, this research developed a novel two-stage DSA system to provide periodic security prediction in real time. The major contribution of this research is to develop an open source on-line DSA system incorporated with Phasor Measurement Unit (PMU) data and forecast load. The pre-fault prediction of the system can provide more accurate assessment of the system and minimize the disadvantage of a low computational speed of time domain simulation. This Thesis describes the development of the novel two-stage on-line DSA scheme using phasor measurement and load forecasting data. The computational scheme of the new system determines the steady state stability and identifies endangerments in a small time frame near real time. The new on-line DSA system will periodically examine system status and predict system endangerments in the near future every 30 minutes. System real-time operating conditions will be determined by state estimation using phasor measurement data. The assessment of transient stability is carried out by running the time-domain simulation using a forecast working point as the initial condition. The forecast operating point is calculated by DC optimal power flow based on forecast load. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2017

Electric power is becoming more and more important in the modern world. Since most electric power utilizations should be supplied by the power transmission and distribution system, the security of power system is paid more and more heed to nowadays. All over the world, there are some trends to introduce the deregulated power system into the power system operation, and to increase the stability of electric power supply. As a result, making accurate predictions for the power system operating conditions is an important task for the current power system research. The research mainly interests in checking if the operating conditions are acceptable after contingencies. Dynamic Security Assessment (DSA) is proposed and studied under such context. One tool to implement the DSA is to create the Stability Indices (SI) system. The SI system is used to indicate the operating conditions for the power system. This master thesis project aims to develop the appropriate Remedial Actions Scheme (RAS) by using the SI system. The RAS is used against different instabilities. Firstly, all indices of the SI system are summarized. The summarization is based on theoretical study on to-date DSA researches. The indices of the SI system are able to predict power system operating conditions. They are also able to release the stress of DSA computing, and to reduce misclassification and failed-alarm. The SI system is computed by quantities of state variables from the components of the power system. Secondly, the functionalities of different remedial actions are clarified. Then, those remedial actions are used to develop the RAS. The RAS is developed according to the evaluation by the SI system. Using the SI system, different remedial actions are tested and evaluated. The results of evaluation are used to develop and categorize different RASs against different instabilities. After that, the RASs are analyzed, and qualities of RASs are ranked by the SI. In this way, more suitable RAS against each type of instability is developed. The results show the process of analysis is both fast and accurate. All analysis and evaluations are implemented by simulation software of PSS TMNETOMAC. The thesis has been implemented between cooperation of Royal Institute of Technology (KTH) in Sweden and Energy Sector of Siemens AG in Germany.

abstract: The past decades have seen a significant shift in the expectations and requirements re-lated to power system analysis tools. Investigations into major power grid disturbances have suggested the need for more comprehensive assessment methods. Accordingly, sig-nificant research in recent years has focused on the development of better power system models and efficient techniques for analyzing power system operability. The work done in this report focusses on two such topics 1. Analysis of load model parameter uncertainty and sensitivity based pa-rameter estimation for power system studies 2. A systematic approach to n-1-1 analysis for power system security as-sessment To assess the effect of load model parameter uncertainty, a trajectory sensitivity based approach is proposed in this work. Trajectory sensitivity analysis provides a sys-tematic approach to study the impact of parameter uncertainty on power system re-sponse to disturbances. Furthermore, the non-smooth nature of the composite load model presents some additional challenges to sensitivity analysis in a realistic power system. Accordingly, the impact of the non-smooth nature of load models on the sensitivity analysis is addressed in this work. The study was performed using the Western Electrici-ty Coordinating Council (WECC) system model. To address the issue of load model pa-rameter estimation, a sensitivity based load model parameter estimation technique is presented in this work. A detailed discussion on utilizing sensitivities to improve the ac-curacy and efficiency of the parameter estimation process is also presented in this work. Cascading outages can have a catastrophic impact on power systems. As such, the NERC transmission planning (TPL) standards requires utilities to plan for n¬-1-1 out-ages. However, such analyses can be computationally burdensome for any realistic pow-er system owing to the staggering number of possible n-1-1 contingencies. To address this problem, the report proposes a systematic approach to analyze n-1-1 contingencies in a computationally tractable manner for power system security assessment. The pro-posed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the WECC system. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

O presente trabalho tem como objetivo desenvolver um programa computacional para análise de contingências, no contexto da estabilidade transitória, capaz de identificar as contingências críticas do sistema elétrico de potência via métodos diretos. A análise de estabilidade é realizada em diversas etapas, onde serão aplicados diversos filtros, baseados em métodos de análise de ilhamento, não existência de pontos de equilíbrio, PEBS, BCU e simulação computacional, no domínio do tempo, do sistema. Em cada etapa da análise, os casos serão classificadas como sendo estáveis, instáveis ou incertos segundo diferentes critérios, restando portanto, ao fim de cada etapa, um conjunto menor de possíveis contingências críticas. A metodologia proposta foi desenvolvida para modelos de SEPs com rede reduzida, porém as técnicas discutidas neste trabalho aplicam-se também a modelos que preservam a estrutura do sistema de transmissão. / The main objective of this work is to design a transient stability screening contingency program that is able to identify all critical contingencies in an electric power system using direct methods. The stability assessment is performed through several steps by mean of filters based on islanding detection, nonexistence of equilibrium points, PEBS, BCU and time-domain simulation of the power system. In each step of the analysis, all cases are classified as stable, unstable or uncertain cases by different criteria, resulting at the end of each step in a small number of possible critical contingencies. The proposed methodology was designed for reduced models of electric power systems, but all the techniques discussed in this work are also suitable for preserving structure models.

O presente trabalho tem como objetivo desenvolver um programa computacional para análise de contingências, no contexto da estabilidade transitória, capaz de identificar as contingências críticas do sistema elétrico de potência via métodos diretos. A análise de estabilidade é realizada em diversas etapas, onde serão aplicados diversos filtros, baseados em métodos de análise de ilhamento, não existência de pontos de equilíbrio, PEBS, BCU e simulação computacional, no domínio do tempo, do sistema. Em cada etapa da análise, os casos serão classificadas como sendo estáveis, instáveis ou incertos segundo diferentes critérios, restando portanto, ao fim de cada etapa, um conjunto menor de possíveis contingências críticas. A metodologia proposta foi desenvolvida para modelos de SEPs com rede reduzida, porém as técnicas discutidas neste trabalho aplicam-se também a modelos que preservam a estrutura do sistema de transmissão. / The main objective of this work is to design a transient stability screening contingency program that is able to identify all critical contingencies in an electric power system using direct methods. The stability assessment is performed through several steps by mean of filters based on islanding detection, nonexistence of equilibrium points, PEBS, BCU and time-domain simulation of the power system. In each step of the analysis, all cases are classified as stable, unstable or uncertain cases by different criteria, resulting at the end of each step in a small number of possible critical contingencies. The proposed methodology was designed for reduced models of electric power systems, but all the techniques discussed in this work are also suitable for preserving structure models.

[pt] Os sistemas de energia elétrica estão operando atualmente próximos dos limites de estabilidade, comprometendo a segurança. Este fato tem sido evidenciado por diversos blackouts no mundo inteiro. A avaliação da segurança dinâmica torna-se, então, fundamental. O objetivo é a busca de um método rápido e, sobretudo, confiável, para analisar o comportamento dinâmico de um sistema de energia elétrica. Esta dissertação trata, portanto, do problema da avaliação da segurança dinâmica de sistemas de energia elétrica. A avaliação é realizada através da determinação das margens de estabilidade, utilizando os resultados de simulações no domínio do tempo, que fornece informações qualitativas a respeito da estabilidade na primeira oscilação. O grupo de geradores severamente perturbados é determinado e a margem de estabilidade de cada um deles é calculada. O gerador que apresentar a menor margem determina a margem de estabilidade do sistema. Quando a margem de estabilidade assume valor nulo, o tempo crítico de eliminação da falta é obtido. Estes resultados são comparados com aqueles determinados pelo método de tentativa e erro, utilizando um programa convencional de estabilidade transitória. Desta forma, as contingências são classificadas em função dos tempos críticos de eliminação de falta, de acordo com o nível de severidade. Essa classificação permite reduzir o conjunto de contingências a ser estudado. A contribuição deste trabalho é mostrar que o critério baseado na aceleração imediatamente após a eliminação da falta é mais eficaz que aquele baseado na aceleração imediatamente após a ocorrência da falta para a indicação do grupo de geradores severamente perturbados. / [en] Power systems have been operating nowadays near to the stability limits putting security under risk. This is one of the reasons why the dynamic security assessment is a fundamental tool to avoid the occurrence of blackouts in the whole world. The goal is a reliable and fast way to evaluate the dynamic behavior of a power system. This dissertation deals with the problem of dynamic security assessment of power systems. The evaluation is performed based on stability margins calculated from time domain simulation results, providing qualitative information about the first swing stability. The group of severely disturbed machines is defined and the stability margins are determined. The machine with the lowest margin determines the stability margin of the system. When the system margin approaches the zero value, the critical clearing time is obtained. These outcomes are compared with that ones determined by trial and error method using a conventional transient stability program. Having done that, a contingency ranking is defined according to the critical clearing time. The ranking minimizes the number of contingencies that have to be studied. This dissertation shows that the criterion to define the group of severely disturbed machines based on the machine accelerations at the instant immediately after the fault clearing time is more efficient than that one based on the machine accelerations at the instant immediately after the fault occurrence.