Power System Reliability Analysis Research Articles

Service-oriented architectural model for generating system adequacy evaluation

A service-oriented architectural (SOA) model is proposed for power system reliability analysis especially for generating capacity adequacy evaluation. Generating system adequacy evaluation is performed to evaluate the ability of the system generating capacity to meet the total system demand. The proposed SOA model is composed of generation system reliability (GSR) service provider, power system service registry and service requester. The data pertaining to power system reliability analysis are represented in extensible markup language (XML) for exchanging the reliability data among the users and service providers. The GSR service provider describes the reliability evaluation services and publishes them to the power system service registry. The calling sequences of reliability evaluation services along with required data are configured as SOAP (Simple Object Access Protocol) messages and the proposed SOA model communicates between the service provider and the service requester with formally defined messages. The proposed model for generating system reliability analysis is highly distributed and has inherent features such as scalability and flexibility and provides a loosely coupled environment for power system reliability analysis.

An Enhanced Distributed Model for Reliability Evaluation of Power Distribution Systems

Reliability assessment is the most important factor in designing and planning of distribution systems that should operate in an economic manner with minimal interruption of customer loads. The main aim of this paper is to develop interoperable services for power distribution systems reliability evaluation using SOAP communication in which the reliability data is included as attachment within the SOAP message. The proposed XML based SOAP with attachment model is composed of Power System Reliability service provider and Reliability Service Requester. The Power System reliability services are designed to enhance the interoperability based on standards such as HTTP, XML and Simple Object Access Protocol (SOAP). The data pertaining to Power Systems reliability analysis are represented in eXtensible Markup Language (XML) for exchanging the reliability data among the users and service providers. The calling sequences of reliability evaluation services along with required data are configured as SOAP messages. The proposed model for Distribution system reliability evaluation provides flexible loosely coupled as well as high-efficient integration architecture in the deregulating and competitive electric market and has inherent features such as scalable and reliable environment for Power Systems reliability analysis.

Integrated approach for security of electricity supply analysis

The methods and tools needed for security of supply assessment range from long term market models for predicting future generation and load patterns to more detailed network simulation models for analyzing contingencies and reliability of supply for delivery points. This paper describes an integrated approach for security of electricity supply analysis, by the integration of power system reliability analysis with the power market analysis. An integrated methodology will enable the long-term security of supply assessment and provide a more consistent input to the various analyses, as well as a better information exchange and interaction between the different methods and tools involved. The integrated methodology is under development in an ongoing research project focusing the power system reliability analysis, making it possible to take the risk of extraordinary events into account.

Adoptability of grid computing technology in power systems analysis, operations and control

With the deregulation and constant expansion in power systems, the demand of high performance computing (HPC) for power system adequacy and security analysis has been increased rapidly. HPC also plays an important role in ensuring efficient and reliable communication for power system operation and control. In past few years, grid computing technology is catching up much attention from the power engineers and researchers. Grid computing technology is an infrastructure, which can provide HPC and communication mechanism for providing services in these areas of power system. A review is presented on the research which has been carried out in the last few years in this area regarding the applicability of grid computing technology in power system reliability and security analysis, operations, monitoring and control systems. We also introduce more grid computing applications for the future research directions in order to provide more open access and more efficient and effective computing services to meet the increasing needs of the power industry. This review presents a comprehensive and clear picture of the benefits of using this technology in terms of efficiency and cost.

A graph trace based reliability analysis of electric power systems with time-varying loads and dependent failures

A new approach to the prediction of the reliability of electrical systems is presented. In this approach a graph trace based reliability analysis of electric transmission and/or distribution systems is used. The systems are modeled using containers with iterators, where the iterators manage graph edges and are used to process through the topology of the graph. The analysis provides a means of computationally handling dependent failure rates and cascading failures. The effects of weather, time-varying loads, equipment age, wetness, and dependent failures associated with repaired components are considered. A sequential Monte Carlo simulation is used to evaluate the reliability changes for different system configurations, including distributed generation and transmission lines. Historical weather records and loading are used to update the component failure rates on-the-fly. Simulation results are compared against historical reliability field measurements.

Application of the fault tree analysis for assessment of power system reliability

A new method for power system reliability analysis using the fault tree analysis approach is developed. The method is based on fault trees generated for each load point of the power system. The fault trees are related to disruption of energy delivery from generators to the specific load points. Quantitative evaluation of the fault trees, which represents a standpoint for assessment of reliability of power delivery, enables identification of the most important elements in the power system. The algorithm of the computer code, which facilitates the application of the method, has been applied to the IEEE test system. The power system reliability was assessed and the main contributors to power system reliability have been identified, both qualitatively and quantitatively.

Windfarm Generation Assessment for Reliability Analysis of Power Systems

Due to the fast development of wind generation in the past ten years, increasing interest has been paid to techniques for assessing different aspects of power systems with a large amount of installed wind generation. One of these aspects concerns power system reliability. Windfarm modelling plays a significant role in this assessment and different models have been created for it, but a representation which includes all of them has not been developed yet. This paper deals with this issue. First, a list of nine influencing Factors is presented and discussed. Secondly, these Factors are included in a reliability model and the generation of a windfarm is evaluated by means of sequential Monte Carlo simulation. Results are used to analyse how each mentioned Factor influences the assessment, and why and when they should be included in the model.

New finding on out-of-step separation configuration of large-scale power systems

In this paper, two new concepts—“main out-of-step mode” and “minor out-of-step mode”—are proposed for power system reliability analysis. Large-scale power system studies found that out-of-step generator groups may have characteristics of the main out-of-step mode and the minor out-of-step mode. The generator groups with main out-of-step modes can determine the out-of-step interface of the large-scale power system, while generators with the minor out-of-step modes cannot play such a role. Therefore, the method of capturing the out-of-step interface by seeking the lowest voltage point (the out-of-step center) can only group the generators with the main out-of-step modes, and may fail to combine the generators with the minor out-of-step modes into proper coherent generator groups. Thus, it is necessary in engineering applications to equip the generators that are likely to have the characteristics of the minor out-of-step modes with separation devices based on off-line simulation studies in order to reduce the risk of further accidents caused by these generators after system separation.

Predicting Bulk Electricity System Reliability Performance Indices Using Sequential Monte Carlo Simulation

System reliability performance is usually based on average customer interruption information. These average values are valuable information, but provide only a single customer risk dimension without underlying probability distributions. The average annual indices give no insight on how reliability may vary from year to year as a result of the random behavior of bulk electric systems (BES). A significant advantage when utilizing sequential Monte Carlo simulation in bulk electric system reliability analysis is the ability to provide reliability index probability distributions in addition to the expected values of their indices. Parameter distribution analysis and its potential utilization are relatively new concepts in composite power system reliability analysis and decision making. This paper presents a technique to predict future reliability performance indices of the BES using a sequential simulation approach. The results obtained using the sequential software show that the system performance index probability distributions have unique characteristics that are basically dependent on the system topology and the operating philosophy. Operating policies involving load shedding procedures have a considerable impact on the system performance indices and their associated distributions. Two test systems are used to illustrate the concepts associated with the determination of system performance indices and their associated probability distributions. The results obtained using two different load shedding policies are presented and compared.

Delivery Point Reliability Indices of a Bulk Electric System Using Sequential Monte Carlo Simulation

A significant advantage when utilizing sequential Monte Carlo simulation in bulk electric system reliability analysis is the ability to provide reliability index probability distributions in addition to the expected values of their indices. Reliability index probability distributions provide a pictorial representation of the annual variability of these parameters around their mean values. Parameter distribution analysis and its potential utilization are relatively new concepts in composite power system reliability analysis and decision making. Computer software has been developed to produce reliability index probability distributions for the individual delivery points (DPs) in a bulk electric system. The results obtained using the sequential software show that the DP reliability index probability distributions have unique characteristics that are basically dependent on the system topology and the system operating philosophy. Operating policies such as load shedding procedures have a significant impact on the DP reliability indices and their associated distributions. The IEEE Reliability Test System is used to illustrate the concepts associated with the determination of DP and system indices and their associated probability distributions. The results obtained using two different load shedding policies are also presented and compared.

Development of power system reliability analysis program with consideration of system operation

This paper describes a new program which analyzes the reliability of composite power systems with consideration of power system operational aspects. It uses the sequential Monte Carlo method and calculates annual risk indices for each load point. The program deals with the system problems involved in load flow, voltage, frequency, and small-signal stability if necessary. The distinctive feature of the program is consideration of power system operation in a sequential manner, such as generation dispatch and system restoration after equipment failure. This makes possible the evaluation of both power system planning and operation from the reliability point of view. Several new methods of reducing calculation time are developed and implemented, including the concurrent LP/load flow method, which improves solvability. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 153(4): 20–31, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20138

Power system probabilistic security assessment using Bayes classifier

This paper presents a method for power system security assessment based on the Bayes classifier. This method can be applied to calculate probabilistic security indices as well as on-line security assessment. In general, the determination of security breach is a cumbersome and time-consuming process due to dynamic and steady-state effects. These effects can be incorporated by considering transient stability, satisfaction of system load without violation of constraints, and voltage stability studies. The variation of the system load, as well as contingencies, may cause system transition to a different operating state. It is impractical if not impossible to evaluate all these situations, such as contingencies resulting from load variation. The straightforward Monte Carlo simulation, one of the possible methods in power system reliability analysis, requires the evaluation of a system operating state for each sampled state and is computation-intensive. In the proposed method, first the joint probability density of feature vectors has been obtained by using some training data. Once this joint distribution is obtained, the Bayes classifier provides the assessment of system security without complicated contingency analyses and can reduce the computational burden. Security status of a given feature vector can be determined by a posteriori probability rule called Bayes rule, which can be implemented in on-line security assessment or power system reliability studies.

Seismic reliability analysis of large electric power systems

Based on the De.Morgan laws and Boolean simplification, a recursive decomposition method is introduced in this paper to identify the main exclusive safe paths and failed paths of a network. The reliability or the reliability bound of a network can be conveniently expressed as the summation of the joint probabilities of these paths. Under the multivariate normal distribution assumption, a conditioned reliability index method is developed to evaluate joint probabilities of various exclusive safe paths and failed paths, and, finally, the seismic reliability or the reliability bound of an electric power system. Examples given in the paper show that the method is very simple and provides accurate results in the seismic reliability analysis.

“An Island of Technicality in a Sea of Discretion”: A Critique of Existing Electric Power Systems Reliability Analysis and Policy

Although the existing analytical framework has performed admirably in the past, the changing industry structure requires improvements, including the use of modeling techniques of the sort successfully used in the nuclear power industry.

A framework of voltage stability assessment in power system reliability analysis

This paper provides a novel framework for extending conventional probabilistic reliability analysis to account for system stability limits. The scheme integrates a voltage stability index with existing reliability tools for offline assessment. The index relates the probability of instability to the proximity of voltage collapse. The scheme is successfully tested using the IEEE Reliability test system.

Evaluation of power systems reliability by an artificial neural network

A new method for reliability analysis of power systems is presented in this paper. This method is based on the artificial neural networks (ANNs), which as shown, need short training times. The objective of this paper is presentation of a new method which can solve difficulties of the previous reliability analysis methods, such as low accuracy, complex modelling and large computations. The proposed method is applied for reliability evaluation of generating units and the transmission system. Obtained results from this method for the IEEE reliability test system are mentioned, which confirm the validity of the developed approach. Other advantages of the proposed method for reliability evaluation are also explained.

Reliability analysis of emergency and standby power systems

Different facilities have varying requirements for reliability of electric power supply. The reliability indices of an actual physical system can be estimated by collecting data on the occurrence of failures and the durations of repair. The Monte Carlo method mimics the failure and repair history of the components and the system by using the probability distributions of the component state durations. Statistics are then collected and indices estimated using statistical inference. There are two basic approaches for Monte Carlo simulation: (1) sequential simulation and (2) random sampling. The sequential simulation proceeds by generating a sequence of events using random numbers and probability distributions of random variables representing component state durations. In random sampling, states are drawn based on the probability distributions of component states and random numbers. Further, there are two methods for representing the passage of time in sequential simulation: (1) the fixed interval method, also called synchronous timing, and (2) the next event or asynchronous timing method. In the fixed interval method, time is advanced in steps of fixed length and the system state is updated. In the next event method, time is advanced to the occurrence of the next event. In actual implementations, it is likely that combinations of the timing controls may be used. The sampling method is generally faster than the sequential technique, but is suitable when component failures and repairs are independent. This article presents the sequential method for reliability analysis.

Reliability analysis of industrial power systems with sensitive loads

A method for the reliability analysis of power system has been developed that includes the behaviour of the system during a disturbance. The power system is modelled as an electrical network in which branches are removed and inserted by stochastic events, generated by a Monte Carlo simulation. This method considers short circuits followed by an interruption of the protection, in stead of just the removal of a component. By using a maximum-permissable voltage sag as an interruption criterion the method can be used for industrial power systems with sensitive loads. The (correct and incorrect) behaviour of the protection, ageing of components, and the influence of preventive maintenance are also included in the method. An example of the use of the method is given: a power system feeding four industrial plants. The influence of plant voltage solidity and of preventive maintenance in the feeding network are investigated. Both turn out to have considerable influence.

The influence of motor reacceleration on voltage sags

The assumption that a voltage sag is rectangular is not correct in a power system with large induction motor loads. The motors decelerate during the short circuit. After fault-clearing, they will accelerate again, drawing a high reactive current from the supply, causing a prolonged postfault voltage sag. This is aggravated by the removal of branches by the protection. The resulting shape of some voltage sags in an example power system is shown and discussed. For the example power system, a stochastic voltage sag table is determined. This table gives the expected number of sags of different depth and duration. The influence of faster protection and of reduced transformer impedance on the table is presented. A simple motor model is implemented in a method for including interruptions due to voltage sags in the reliability analysis of power systems. This model is presented briefly and used to show the influence of motor parameters on the number of sags that lead to an interruption of plant operation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cost-benefit analysis of power system reliability: two utility case studies

There is an emerging recognition that utility investments and other decisions that affect electric service reliability should be explicitly evaluated on the basis of their cost and benefit implications. A cost-benefit approach that quantifies the reliability benefits of alternatives in terms of the reduction in costs resulting from unserved energy enables the evaluation of generation and transmission capacity additions on a consistent, economic basis. This approach has been applied to two utility case studies. In a case study for Pacific Gas and Electric Company, it was used to evaluate three options for maintaining reliability in a major load center-two involving local generation, and the third, a new 230 kV transmission connection. In a case study for Duke Power Company, the approach was used to evaluate alternative designs for proposed additions to a transmission station. This paper describes the methodology and presents the two utility studies. >