06178nam 2200805 450 991014028730332120230125200434.01-306-47326-81-118-84322-31-118-84335-510.1002/9781118849972(CKB)2670000000530799(EBL)1638154(SSID)ssj0001131388(PQKBManifestationID)11625899(PQKBTitleCode)TC0001131388(PQKBWorkID)11144326(PQKB)11729662(OCoLC)858159486(MiAaPQ)EBC1638154(DLC) 2013037234(CaBNVSL)mat06774612(IDAMS)0b000064820aba7d(IEEE)6774612(Au-PeEL)EBL1638154(CaPaEBR)ebr10842316(CaONFJC)MIL578577(PPN)257640983(EXLCZ)99267000000053079920151222d2014 uy engur|n|---|||||txtccrRisk assessment of power systems models, methods, and applications /Wenyuan Li, Ph.D., Fellow, IEEE, CAE, EIC, Chongqing University, China, BC Hydro, CanadaSecond edition.Hoboken, New Jersey :Wiley, IEEE Press,[2014][Piscataqay, New Jersey] :IEEE Xplore,[2014]1 online resource (557 p.)Ieee press series on power engineeringDescription based upon print version of record.1-118-84997-3 1-118-68670-5 Includes bibliographical references and index.Cover; Title page; Copyright page; Dedication; Contents; Preface; Preface to the First Edition; 1: Introduction; 1.1 Risk in Power Systems; 1.2 Basic Concepts of Power System Risk Assessment; 1.2.1 System Risk Evaluation; 1.2.2 Data in Risk Evaluation; 1.2.3 Unit Interruption Cost; 1.3 Outline of the Book; 2: Outage Models of System Components; 2.1 Introduction; 2.2 Models of Independent Outages; 2.2.1 Repairable Forced Failure; 2.2.2 Aging Failure; 2.2.3 Nonrepairable Chance Failure; 2.2.4 Planned Outage; 2.2.5 Semiforced Outage; 2.2.6 Partial Failure Mode; 2.2.7 Multiple Failure Mode2.3 Models of Dependent Outages2.3.1 Common-Cause Outage; 2.3.2 Component-Group Outage; 2.3.3 Station-Originated Outage; 2.3.4 Cascading Outage; 2.3.5 Environment-Dependent Failure; 2.4 Conclusions; 3: Parameter Estimation in Outage Models; 3.1 Introduction; 3.2 Point Estimation on Mean and Variance of Failure Data; 3.2.1 Sample Mean; 3.2.2 Sample Variance; 3.3 Interval Estimation on Mean and Variance of Failure Data; 3.3.1 General Concept of Confidence Interval; 3.3.2 Confidence Interval of Mean; 3.3.3 Confidence Interval of Variance; 3.4 Estimating Failure Frequency of Individual Components3.4.1 Point Estimation3.4.2 Interval Estimation; 3.5 Estimating Probability from a Binomial Distribution; 3.6 Experimental Distribution of Failure Data and Its Test; 3.6.1 Experimental Distribution of Failure Data; 3.6.2 Test of Experimental Distribution; 3.7 Estimating Parameters in Aging Failure Models; 3.7.1 Mean Life and Its Standard Deviation in the Normal Model; 3.7.2 Shape and Scale Parameters in the Weibull Model; 3.7.3 Example; 3.8 Conclusions; 4: Elements of Risk Evaluation Methods; 4.1 Introduction; 4.2 Methods for Simple Systems; 4.2.1 Probability Convolution4.2.2 Series and Parallel Networks4.2.3 Minimum Cutsets; 4.2.4 Markov Equations; 4.2.5 Frequency-Duration Approaches; 4.3 Methods for Complex Systems; 4.3.1 State Enumeration; 4.3.2 Nonsequential Monte Carlo Simulation; 4.3.3 Sequential Monte Carlo Simulation; 4.4 Correlation Models in Risk Evaluation; 4.4.1 Correlation Measures; 4.4.2 Correlation Matrix Methods; 4.4.3 Copula Functions; 4.5 Conclusions; 5: Risk Evaluation Techniques for Power Systems; 5.1 Introduction; 5.2 Techniques Used in Generation-Demand Systems; 5.2.1 Convolution Technique; 5.2.2 State Sampling Method5.2.3 State Duration Sampling Method5.3 Techniques Used in Radial Distribution Systems; 5.3.1 Analytical Technique; 5.3.2 State Duration Sampling Method; 5.4 Techniques Used in Substation Configurations; 5.4.1 Failure Modes and Modeling; 5.4.2 Connectivity Identification; 5.4.3 Stratified State Enumeration Method; 5.4.4 State Duration Sampling Method; 5.5 Techniques Used in Composite Generation and Transmission Systems; 5.5.1 Basic Procedure; 5.5.2 Component Failure Models; 5.5.3 Load Curve Models; 5.5.4 Contingency Analysis; 5.5.5 Optimization Models for Load Curtailments5.5.6 State Enumeration Method"Risk Assessment of Power Systems addresses the regulations and functions of risk assessment with regard to its relevance in system planning, maintenance, and asset management. Brimming with practical examples, this edition introduces the latest risk information on renewable resources, the smart grid, voltage stability assessment, and fuzzy risk evaluation. It is a comprehensive reference of a highly pertinent topic for engineers, managers, and upper-level students who seek examples of risk theory applications in the workplace"--Provided by publisher."This book discusses the models, methods and applications of risk assessment in physical power systems with a focus on various application problems"--Provided by publisher.Ieee press series on power engineeringElectric power systemsReliabilityMathematical modelsElectric power failuresRisk assessmentMonte Carlo methodElectric power systemsReliabilityMathematical models.Electric power failuresRisk assessment.Monte Carlo method.621.319/13011TEC007000bisacshLi Wenyuan1946-771711CaBNVSLCaBNVSLCaBNVSLBOOK9910140287303321Risk assessment of power systems1574915UNINA