Power System Contingency Analysis Research Articles

Implementation of Line Stability Index for Contingency Analysis and Screening in Power Systems

Problem statement: Estimating the margin in the loadability of the power system is essential in the real time voltage stability assessment. Voltage stability is currently one of the most important research areas in the field of electrical power system. In power system operation unpredictable events is termed as contingency and may be caused by line outage in the system which could lead to entire system instability. Voltage stability analysis and contingency analysis are would be performed in a power system by evaluating the derived voltage stability index. Approach: Voltage Stability Index Lmn can be useful for estimating the distance from the current operating point to voltage collapse point. The index can either reveal the critical bus of a power system or the stability of each line connected between two buses in an interconnected network or evaluate the voltage stability margins of a system. Results: Flexible Alternating Current Transmission Systems (FACTS) devices have been proposed as an effective solution for controlling power flow and regulating bus voltage in electrical power systems, resulting in an increased transfer capability, low system losses and improved stability. However to what extent the performance of FACTS devices can be brought out highly depends upon the location and the parameters of these devices. Unified Power Flow Controller (UPFC) is the most promising FACTS device for power flow control. Conclusion/Recommendations: The performance of this index is presented and the effectiveness of the analyzed methods is demonstrated through simulation studies in IEEE 14 bus reliability test systems.

Risk analysis of critical infrastructures emphasizing electricity supply and interdependencies

Failures in critical infrastructures can cause major damage to society. Wide-area interruptions (blackouts) in the electricity supply system have severe impacts on societal critical functions and other critical infrastructures, but there is no agreed-upon framework on how to analyze and predict the reliability of electricity supply. Thus, there is a need for an approach to cross-sector risk analyses, which facilitates risk analysis of outages in the electricity supply system and enables investigation of cascading failures and consequences in other infrastructures. This paper presents such an approach, which includes contingency analysis (power flow) and reliability analysis of power systems, as well as use of a cascade diagram for investigating interdependencies. A case study was carried out together with the Emergency Preparedness Group in the city of Oslo, Norway and the network company Hafslund Nett. The case study results highlight the need for cross-sector analyses by showing that the total estimated societal costs are substantially higher when cascading effects and consequences to other infrastructures are taken into account compared to only considering the costs of electricity interruptions as seen by the network company. The approach is a promising starting point for cross-sector risk analysis of electricity supply interruptions and consequences for dependent infrastructures.

Supervised learning approach to online contingency screening and ranking in power systems

This paper proposes a supervised learning approach to fast and accurate power system security assessment and contingency analysis. The severity of the contingency is measured by two scalar performance indices (PIs): Voltage-reactive power Performance Index, PIVQ and line MVA Performance Index, PIMVA. In this paper, Feed-Forward Artificial Neural Network (FFNN) is employed that uses pattern recognition methodology for security assessment and contingency analysis. A feature selection technique based on the correlation coefficient has been employed to identify the inputs for the FFNN. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus New England system at different loading conditions corresponding to single line outage. The overall accuracy of the test results for unknown patterns highlights the suitability of the approach for online applications at Energy Management Center.

Fast voltage contingency analysis of power systems using model trees

This paper presents a model tree (MT) based approach for fast voltage contingency ranking, of most severe contingencies for online applications in energy management systems. To measure the severity of contingencies, a bus voltage violation based scalar performance index is used. Model trees are developed to estimate the real value of voltage performance index (VPI) and rank the single line outage contingencies, according to their severity. Full AC power flow is performed, to generate the training and testing patterns for the proposed MT under each contingency. The effectiveness of the proposed approach is tested on IEEE test systems. Once trained, the MT method gives fast and accurate ranking of contingencies for unknown load patterns, hence it is suitable for online applications in energy management systems.

Neural network approach to contingency screening and ranking in power systems

An artificial neural network (ANN) approach to power system contingency analysis is proposed. Using fast voltage and line-flow contingency screening. Full AC load flow is performed for each contingency case. The off-line results of full AC load flow calculations are used to construct two kinds of performance indices, namely the real power performance index ( PI MW) and voltage performance index ( PI V), which reflect the degree of severity of contingencies. The results from off-line load flow calculations are used to train the “ screening module”, which is a multi-layered perceptron (MLP) network, for estimating the performance indices ( PI MW, PI V PI V). The MLP is trained to classify the contingencies either as critical or non-critical cases using back-propagation (BP) algorithm. The screened critical contingencies are passed on to the “ ranking module” for ranking of the contingencies. The effectiveness of the proposed method is demonstrated by contingency screening and ranking on a standard 6-bus and IEEE 14-bus systems. The performance of the proposed method is compared with a traditional Newton Raphson (NR) method and the results discussed. The proposed methodology was implemented using the MATLAB Neural Network Toolbox. The generalization capability of the trained neural network was able to identify unknown contingencies with large range of operating conditions and changes in network topology. The proposed approach to contingency analysis was found to be suitable for fast voltage and line-flow contingency screening and ranking.

Método da continuação aplicado na análise de contingência de linhas de transmissão

Este trabalho apresenta um método para a análise estática de contingências em Sistemas Elétricos de Potência utilizando o Método da Continuação. A margem de carregamento pós-contingência é obtida a partir do ponto de máximo carregamento do caso base. A magnitude de tensão de uma barra qualquer é usada como parâmetro na etapa de parametrização do fluxo de carga continuado. O ramo selecionado para avaliação da contingência é parametrizado por um fator de escalonamento que possibilita a remoção gradual do ramo e assegura a convergência nos casos em que o método diverge para a retirada total da linha de transmissão. Em geral, para a maioria das contingências analisadas são necessárias poucas iterações para a determinação do ponto de máximo carregamento pós-contingência. Mostra-se que o método pode ser usado como uma técnica alternativa para a averiguação e até mesmo para a obtenção da lista de contingências críticas fornecida pela função de análise de segurança de sistemas elétricos.

05/02107 Thermal effect on electric power network components under short-circuit currents

In this paper a novel approach for power system contingency analysis is proposed. The developed expert system (HESCA), incorporates operator knowledge into the contingency selection process towards reducing the number of contingencies to be computed. The proposed hybrid approach combines the conventional numerical algorithms and knowledge-based methods to enhance the accuracy of final results.The proposed method was applied to modified IEEE 30 bus and an actual national grid power system to show its feasibility and capabilities. This paper demonstrates the improved results in comparison to conventional methods and shows that the proposed approach is reliable and efficient to be used in power network control centers.

Radial basis function networks for contingency analysis of bulk power systems

Radial basis function networks (RBFNs) are used for contingency evaluation of bulk power system. The motivation behind this work is to exploit the nonlinear mapping capabilities of RBFN in estimating line loading and bus voltage of a bulk power system following a contingency. Unlike most of the available neural networks based techniques, the proposed method utilizes the potential of RBFN in planning studies. The performance of the RBFN is compared with a standard AC load flow algorithm.

An expert system to improve power system contingency analysis

In this paper a novel approach for power system contingency analysis is proposed. The developed expert system (HESCA), incorporates operator knowledge into the contingency selection process towards reducing the number of contingencies to be computed. The proposed hybrid approach combines the conventional numerical algorithms and knowledge-based methods to enhance the accuracy of final results. The proposed method was applied to modified IEEE 30 bus and an actual national grid power system to show its feasibility and capabilities. This paper demonstrates the improved results in comparison to conventional methods and shows that the proposed approach is reliable and efficient to be used in power network control centers.

Application of the integrated safety assessment methodology to the protection of electric systems

The generalization of classical techniques for risk assessment incorporating dynamic effects is the main objective of the Integrated Safety Assessment Methodology, as practical implementation of Protection Theory. Transient stability, contingency analysis and protection setpoint verification in electric power systems are particularly appropriate domains of application, since the coupling of reliability and dynamic analysis in the protection assessment process is being increasingly demanded. Suitable techniques for dynamic simulation of sequences of switching events in power systems are derived from the use of quasi-linear equation solution algorithms. The application of the methodology, step by step, is illustrated in a simple but representative example.

Improvements on the line outage distribution factor for power system security analysis

This paper presents two sensitivity factors in terms of the generation shift distribution factor (GSDF) to improve some defects of the conventional formula for the line outage distribution factor (ODF). The sensitivity factors are established by using the concepts of generation change and power injection to simulate the outaged line flow and one of them is then applied to the case of line addition. A transfer factor is derived to calculate the power flow of the added line very quickly from the relationship between the ODF and the GSDF. The proposed method has been tested by means of a standard system. Compared with the conventional ODF in the line outage case and with DC load flow in the line addition case, the proposed method has good accuracy and a fast execution time. This method is very suitable for real-time security assessment and contingency analysis of power systems.

An efficient contingency evaluation method for power system security analysis

An efficient method for power system contingency analysis based on DC load flow using bifactorization and partial matrix refactorization techniques is described. The efficiency of this method is derived from the use of the explicit inverse of the susceptance matrix obtained by multiplication of the factor matrices of bifactorization; and subsequently from the use of partial matrix refactorization techniques (applied to the factored matrices obtained through bifactorization) and the fast screening technique based on heuristic rule-based approach. The proposed method is most suitable for multiple contingency analysis. The proposed methods has been tested on different test systems up to 118-bus and was found to be excellent.

電力系統想定事故解析のための新しいDC潮流計算法

電力系統想定事故解析のための新しいDC潮流計算法

Computational analysis of adjoint network-based methods applied to contingency evaluation

Contingency evaluation methods are typically based on algebraic manipulation of the load flow equations around a known base-case solution. Alternatively, it is possible to make use of an adjoint network-based approach to evaluate the state of a power system for simulation of single or multiple branch outages and single or multiple power outages. In this paper we analyse the most promising variants of adjoint network-based methods applied to state variable evaluation for steady state power system contingency analysis, including the case of network equivalents. The computational requirements of the methods for medium- and large-scale systems are quantified. From the computational point of view, these methods are then compared with conventional algebraic methods. In view of this comparison, we make an alternative proposal for contingency evaluation studies which is more reliable and computationally less demanding.

Fast power system voltage prediction using knowledge-based approach and on-line box data creation

The paper presents an algorithm for fast power system contingency analysis using pattern recognition. The pattern space is clustered into data boxes for ease of search and flexibility of programming. The addressable memory structure of the pattern space decouples the voltage prediction problem into subproblems for one busbar and one contingency at a time. To reduce the working memory, the algorithm learns from the short-term load trend and selects only a few data boxes for on-line processing. Further computational savings and improvements in accuracy are achieved by adopting an innovative wafer data box structure that also facilitates subsequent refinement by additions/deletions of patterns acquired from real-time operational experience. Other techniques, with the same objectives, include a procedure for eliminating insignificant features from data boxes and clumping their effects into correction terms; a methodology for selecting the best expression for voltage prediction; and a pattern filter for placing the target state at the geographical centre of the training set nearest neighbourhood patterns.

A modified linear algorithm for power system contingency analysis

This paper introduces an algorithm for fast linear contingency analysis which computes linearized system line real power flow changes due to system outages. It implements the relation between bus injected real powers and bus phase angles, taking into account the second-order changes in the relation due to the system contingencies. The effects of these changes greatly improve the DC load flow results over similar methods used previously for this type of problem.

Bound Estimates of the Severity of Line Outages in Power System Contingency Analysis and Ranking

The effect of line outages on the real power flows of a system is analyzed using the DC load flow model. It is shown that the effect of the out4ge of line jk on the power flow of an arbitrary line lm can be bounded above and below by a series of progressively tighter values which in the limit correspond to the exact DC load flow solution. The calculation of these bound estimates on the contingency line flows is progressively more computationally demanding as the limits tighten, however, the simple to compute bounds, although more conservative, still serve to filter out a large portion of the non-critical contingencies. The remaining few potentially critical outages can then be ranked and analyzed through the full DC load flow.

Bound Estimates of the Severity of Line Outages in Power System Contingency Analysis and Ranking

Bound Estimates of the Severity of Line Outages in Power System Contingency Analysis and Ranking

Automatic Contingency Selection

A fast technique has been developed for the automatic ranking and selection of contingency cases for a power system contingency analysis study. A contingency list is built containing line and generator outages which are ranked according to their expected severity as reflected in voltage level degradation and circuit overloads. An adaptive contingency processorcan be set up by performing sequential contingency tests starting with the most severe contingencies at the top of the list and proceeding down the list, stopping when the severity goes below a threshold. Computational results of this technique applied to different test systems are presented.