Dynamic Security Assessment Research Articles

Use of Transient Stability Indices to Dynamic Security Assessment

Indices that report how much a contingency is stable or unstable in an electrical power system have been the object of several studies in the last decades. In some approaches, indices are obtained from time-domain simulation; others explore the calculation of the stability margin from the so-called direct methods, or even by neural networks.The goal is always to obtain a fast and reliable way of analysing large disturbance that might occur on the power systems. A fast classification in stable and unstable, as a function of transient stability is crucial for a dynamic security analysis. All good propositions as how to analyse contingencies must present some important features: classification of contingencies; precision and reliability; and efficiency computation. Indices obtained from time-domain simulations have been used to classify the contingencies as stable or unstable. These indices are based on the concepts of coherence, transient energy conversion between kinetic energy and potential energy, and three dot products of state variable. The classification of the contingencies using the indices individually is not reliable, since the performance of these indices varies with each simulated condition. However, collapsing these indices into a single one can improve the analysis significantly. In this paper, it is presented the results of an approach to filter the contingencies, by a simple classification of them into stable, unstable or marginal. This classification is performed from the composite indices obtained from step by step simulation with a time period of the clearing time plus 0.5 second. The contingencies originally classified as stable or unstable do not require this extra simulation. The methodology requires an initial effort to obtain the values of the intervals for classification, and the weights. This is performed once for each power system and can be used in different operating conditions and for different contingencies. No misplaced classification occurred in any of the tests, i.e., we detected no stable case classified as unstable or otherwise. The methodology is thus well fitted for it allows for a rapid conclusion about the stability of th system, for the majority of the contingencies (Stable or Unstable Cases). The tests, results and discussions are presented using two power systems: (1) the IEEE17 system, composed of 17 generators, 162 buses and 284 transmission lines; and (2) a South Brazilian system configuration, with 10 generators, 45 buses and 71 lines.

Use of Transient Stability Indices to Dynamic Security Assessment

Use of Transient Stability Indices to Dynamic Security Assessment

Development of a broadband real-time fully-digital simulator for the study and control of large power systems

While transient stability (TST) programs can represent very large systems, they are unable to model power electronic devices in detail since they use relatively large time steps and balanced representation of the network. Electromagnetic transients (EMT) simulators, on the other hand, can model relatively small systems in detail using small time steps. By interfacing both simulation tools, it will be possible to develop a broadband simulator capable of modeling large systems, but including detailed representation where required. The simulator would provide for studies ranging from fast transient to transient, dynamic, and voltage stability, with applications including closed-loop protection and control studies, as well as on-line dynamic security assessment (DSA). In this paper, we present the latest development work related to the realization of a broadband fully-digital simulator, which would be capable of meeting the challenge obtaining real-time solutions of very large networks using sufficiently small integration time steps such that power electronic devices (FACTS or HVDC) could be modeled at the device level with sufficient time resolution.

Dynamic voltage security assessment by a neural network based method

The voltage security problem is an indispensable aspect of power system security. Voltage stability limits constrain the loading capabilities of power systems. In recent years, some papers have shown that voltage stability is a dynamic problem. In practice static analysis methods, like power flow based methods, may have deficiency to evaluate voltage stability or voltage security problems. On the other hand, dynamic modeling and evaluation of voltage stability problem are complex, expensive and time consuming. In this paper, a neural network (NN) approach has been presented for this purpose. This NN can establish a mapping between operating conditions and dynamic voltage stability margin (VSM) of each bus. This analysis gives an insight about robustness of different buses and dynamic voltage security status of power system. The method has been examined on a portion of Iran's south-west transmission network. Obtained results confirm the validity of the developed approach.

Applications of artificial intelligence techniques in wind power generation

The paper presents two applications of Artificial Intelligence techniques, namely Artificial Neural Networks (ANNs) and Decision Trees (DTs), in wind power generation. The first concerns the design procedure of a permanent magnet generator for a 20 kW wind turbine prototype. This work has been developed in the frame of a research project funded by the General Secretariat for Research and Technology of Greece, concerning the design and construction of a gear-less wind turbine for both autonomous and interconnected operation with the electrical grid. The second application concerns the security assessment of networks including wind farms and has been developed in the frame of JOULE-II European Community research programme. The results from the application of ``learning from examples'' methods, namely ANNs and DTs, for the fast dynamic security assessment of the power system of Lemnos island are presented and comparatively assessed.

Online Dynamic Security Assessment using Neural Networks and the Transient Energy Function Method

This article presents a new artificial neural network (ANN)—based approach for online power system dynamic security assessment (DSA). The authors represent an application of feedforward neural networks in estimating the critical clearing time (tcr) for transient stability analysis. Knowing that for a particular fault scenario, the tcr is a function of only pre-fault system operating point, the main objective of the article is to show how one may develop an ANN-based method for estimating the tcr by considering the smallest set of directly monitorable variables characterizing this operating point adequately. The proposed technique does not require any supplementary tools such as load-flow and⁄or transient stability software for input determination of the ANN. The authors attempt to convert the DSA to a function approximation problem, which is well-suited to be tackled by multilayer feedforward neural networks. The technique has the following two main advantages: (1) The tcr is estimated as fast as possible; (2) The size of both ANN and training data set are remarkably reduced. In order to obtain the necessary training data set for the tcr, the potential energy boundary surface method is used, accompanied by the time domain simulation technique. The proposed approach has been successfully applied to the New England test system, and it has been shown that the tcr can be estimated by the trained network in a few milliseconds.

Time-varying contingency screening for dynamic security assessment using intelligent-systems techniques

A time-frequency-based approach for contingency severity ranking and rapid stability assessment is described. The aim is to classify correctly all single or multiple contingencies that may result in loss of voltage or frequency stability in the first 20 s following the last disturbing action. We start by selecting a number of strategic monitoring buses where the phasor measurement units are located to capture representative voltage magnitudes and angles during detailed time-domain simulations, which cover special protection systems and on-load tap-changers. The short-time Fourier transform is then dynamically applied to the responses for extracting selected decision features as the simulation time evolves. It is shown that frequency-domain features such as the peak spectral density of the angle, frequency and their dot product evaluated over the grid areas are reliable time-varying stability indicators that can form the basis of an entirely secure classification system able to respond within 2 to 3 s after the last event in the contingency. This allows early termination of about 60% of permanently stable simulations. Fuzzy logic and neural networks are used together to make initial decisions which are then mixed by voting in order to improve the assessment reliability and security at the expense of a reduced yield. The proposed DSA scheme is successfully tested with 1027 contingencies from two widely differing test systems: a 67-bus fictitious system and a 783-bus system in actual use at Hydro-Quebec's operations planning department.

On-line dynamic security contingency screening using artificial neural networks

On-line dynamic security analysis has now become realistic due to advances in computer technology and algorithms for security assessment. Details of pattern recognition based electro-mechanical stability screens which have been implemented within a dynamic security assessor are presented. Use of statistical functions of features is shown to overcome the dimensionality problem of applying pattern recognition techniques to large power systems. The low computational cost of this approach coupled with efficient operation has resulted in a significant step towards achieving full on-line dynamic security assessment.

Development of BCU classifiers for on-line dynamic contingency screening of electric power systems

A sequence of BCU classifiers for online dynamic contingency screening is developed and their theoretical basis is provided. The design objective of the BCU classifiers is to ensure that unstable (single-swing or multiswing) contingencies be completely captured and that the number of contingencies needed for further analysis be significantly reduced. An architecture for online dynamic security assessments consisting of the BCU classifiers and an online transient stability (time-domain) simulation program is presented. The effectiveness of the developed BCU classifiers and proposed architecture is evaluated with very promising results using 7120 contingencies on a 50-generator, 145-bus power system and a 202-generator, 1293-bus real power system data.

New trends and requirements for dynamic security assessment

This paper presents the main trends in the development of DSA tools, based on existing experience and following a questionnaire sent to more than 40 utilities world-wide. It is an abridged version of a Cigré brochure produced by the Task Force 38-02-13. It proposes a definition of DSA, and an overview of the current practices in this field, and it examines the general needs and requirements as well as the technical challenges ahead for DSA.

Probabilistic on-line transient stability analysis

The feasibility of a probabilistic framework for real-time transient stability assessment (TSA) is explored. The main contribution of the probabilistic approach consists in a natural framework for dynamic security assessment (DSA). An advantage of the proposed approach is the enlargement of the time horizon for TSA, which allows contingency analysis to be performed over a longer time. The assessment of the instability probability allows the severity of contingencies and their likelihood to be considered on a common basis.

Implementation of an on-line dynamic security assessment program for the central China power system

The central China power system is currently implementing an on-line stability program. This is the second largest power system in China to implement such an on-line stability program, and probably one of the earliest practical implementations of a dynamic security assessment program (DSA) reported in the world. This paper presents the features of this program, its computational methods, the design considerations used, and some numerical results.

A new tool for dynamic security assessment of power systems

This paper describes a new tool for dynamic security assessment of power systems, in which two technologies are combined: the EEAC method and time-domain simulations. Details of the structure and functionalities of the tool are discussed. The applications of the tool are illustrated with a realistic power-system model as an example. The results show that both fast computation speed and reliable performance are achieved.

A new hybrid method for on-line dynamic security assessment

This paper presents a new hybrid method called marginally unstable injection (MUI). This method incorporates energy function analysis into a time-domain simulator for transient stability assessment. Using a ‘controlled’ sequence of short pseudo-faults and the concept of slow energy function (SEF), the proposed method provides an improved stability index by impelling a stable system to a marginally unstable state. The resulting stability index is then utilized for estimating the amount of generation rejection required to maintain transient stability within the framework of on-line dynamic security assessment. The technique developed is applied to a 700-bus North America system.

On-line dynamic preventive control: an algorithm for transient security dispatch

This paper describes the philosophy and the implementation of a preventive control algorithm for application in power system dynamic security assessment. The methodology consists of an optimization procedure where: the objective function takes into account economic costs; inequality constraints confine the trajectory of the system in a practical domain of the state space; and equality constraints derive from the discretization of the differential-algebraic equations of the power system sparse representation. The algorithm has been implemented to reschedule the power system generation in order to guarantee transient stability. The feasibility of the approach is shown through computer simulation tests on a realistic sized test network.

Online dynamic security assessment in an EMS

System stability analysis results have been part of electric utilities' operating guidelines for move than a decade. Today, these guidelines are compiled from offline stability studies conducted jointly with other utilities and independently by each utility. The offline study results are adjusted for actual generation patterns and network conditions, based on sensitivity analysis, and presented to operators through the energy management system (EMS). These stability limits tend to be conservative for normal conditions and may indeed be inaccurate following unusual system events. The offline study scope expands each year as more significant variables are identified. Limits derived from the offline studies also require extensive engineering analysis trying to anticipate conditions which may never occur. A better alternative is to compute these limits online, based on actual operating conditions. A dynamic security assessment (DSA) function implemented in an EMS environment would improve reliability, identify additional energy transaction potential and result in better use of engineering resources. This article presents DSA functional features and an implementation of an online DSA function under development at Siemens Power Systems Control under a collaborative sponsorship of EPRI and Northern States Power Company.

A general purpose method for on-line dynamic security assessment

Time domain-based online dynamic security assessment (DSA) systems require a fast and reliable method for simulation termination and margin calculation. B.C. Hydro's online DSA uses the second kick method which proved to be an elegant and reliable method for this purpose. This method was later enhanced to improve implementation and computation requirements. The methods presented so far require the mode of disturbance (MOD) information. In this paper, the fast second kick method is expanded to remove the need for the MOD data. The new method has been tested on the large scale systems of B.C. Hydro and Hydro Quebec and the results have been compared to those of the fast second kick method. The results obtained indicate that the new method predicts the stability limits accurately. They also indicate that the new method takes in average 20% longer than the fast second kick method to calculate the stability limit. The implementation requirement for both methods is similar.

A new approach to dynamic security assessment using trajectory sensitivities

The transient stability of power systems is investigated using a new analytical tool. Instead of computing the sensitivities of energy margins, trajectory sensitivity functions of the post-fault system with respect to parameters are computed. The goal is to find how sensitive the trajectories of each state are to variations in system parameters. When the system becomes more stressed, the state trajectories become more sensitive to variations in parameters. Thus these trajectory sensitivities can be used as a measure of system security. This concept is illustrated on the IEEE single- and seventeen-machine systems, and it is shown that dynamic sensitivity functions can also be applied to systems of differential-algebraic equations where the TEF method has limitations.

An On-Line Dynamic Security Assessment Implementation

This paper presents the features and implementation of an on-line Dynamic Security Assessment (DSA) function which consists of contingency screening, time-domain simulation and calculation of stability limits. An energy based approach, including an early termination scheme to reduce the computational effort and stability index to calculate the power transfer limit, and automatically determine the degree of stability has been developed and incorporated in the simulation engine. A client server implementation of the simulation engine and concurrent execution of contingencies on multiple workstations is also described. A sample test result is presented.

A New Tool for Dynamic Security Assessment of Power Systems

This paper describes a new tool for dynamic security assessment of power systems, in which two technologies are combined: the EEAC method and time-domain simulations. Details of the structure and functionalities of the tool are discussed. The applications of the tool are illustrated with a realistic power system model as an example. The results show that both fast computation speed and reliable performance are achieved.