Reliability Analysis of Modern Power Systems

fmatter
	Title Page
	Copyright
	Contents
	About the Authors
	List of Contributors
	Foreword
	Preface
	Acknowledgments
ch1
	Chapter 1 Basic Principles and Scientific Importance of Reliability Theory
		1.1 Introduction
		1.2 Basic Concept of Reliability Engineering
			1.2.1 The Role of Reliability Engineering
			1.2.2 Key Features of Reliability Engineering
		1.3 Scientific Importance of Reliability in Modern Technology
		1.4 Basic Concept of Probability Theory
		1.5 Basic Concepts of System Reliability
			1.5.1 Bathtub Curve
				1.5.1.1 Initial Period (debugging/Burn‐In/Infant‐Monolith Period)
				1.5.1.2 Constant Hazard Model
				1.5.1.3 Wear‐Out Region
				1.5.1.4 Burn‐In Screening
			1.5.2 Reliability Functions
			1.5.3 Mean Time to Failure of Component
			1.5.4 Additional Examples
		1.6 Conclusion
		References
ch2
	2.1 Introduction
	2.2 Bayesian Network
	2.3 Bayesian Reliability
	2.4 Application of BN in Reliability and Remaining Useful Life
		2.4.1 BN Structure Modeling
		2.4.2 BN Parameter Learning
		2.4.3 BN Inference
		2.4.4 Validation and Verification
	2.5 Dynamic Bayesian Networks
	2.6 Advantages and Limitations of BN and DBN
	2.7 Conclusion
	References
ch3
	3.1 Introduction
	3.2 Markov Process
	3.3 Solution of State Equations
		3.3.1 Steady State Solution: Continuous Time Case
		3.3.2 Complete Solution: Continuous Time Case
			3.3.2.1 Laplace Transform Method
			3.3.2.2 Solution by Computing eAT
			3.3.2.3 Discretization
			3.3.2.4 Steady State Solution of Discrete Markov Process
			3.3.2.5 Complete Solution of Discrete Markov Chain
	3.4 Functions of a Single Component\'s Availability and Unavailability
	3.5 Two‐Component State Model and State Probabilities
	3.6 Three‐Component State Transition Diagram
	3.7 Concept of Frequency and Mean Duration
	3.8 Frequency of Combined Events
	3.9 State Enumeration Technique for Obtaining Frequency‐Duration (FD)
	3.10 Conclusion
	References
ch4
	4.1 Introduction
	4.2 Series Network
	4.3 Parallel Network
	4.4 Partially Redundant System
	4.5 Reliability Evaluation of Complex Networks
		4.5.1 Event Space Method
		4.5.2 Decomposition Method
		4.5.3 Tie‐Set Method
		4.5.4 Cut‐Set Method
	4.6 Determination of Tie‐Sets
		4.6.1 Connection Matrix Method Using Node Elimination
	4.7 Method of Obtaining Cut‐Set
	4.8 Multistate Model
		4.8.1 Event‐Space Method
		4.8.2 Decomposition Approach
	4.9 Illustrative Examples
	4.10 Conclusions
	References
ch5
	5.1 Introduction
	5.2 Reliability Evaluation Under Ideal Condition
	5.3 Standby System Reliability Evaluation Under Nonideal Condition
		5.3.1 Switching is Imperfect (Endrenyi )
		5.3.2 Switching is Imperfect and Switch has a Failure Rate λs (Imperfect Switch)
		5.3.3 Consider the Standby Components Might Fail While they are in Idle Mode in Addition
	5.4 Reliability Evaluation of Load‐Sharing System (Endrenyi )
	5.5 Illustrative Examples
	5.6 Conclusion
	References
ch6
	Chapter 6 Physical Reliability Methods and Design for System Reliability
		6.1 Introduction
		6.2 Reliability Methods
			6.2.1 Block Diagram Analysis
				6.2.1.1 Cut Sets and Tie Sets
				6.2.1.2 Common Mode Failures
				6.2.1.3 Enabling Events
			6.2.2 Fault Tree Analysis
				6.2.2.1 Steps of FTA
				6.2.2.2 Applications of FTA
			6.2.3 State Space Analysis (Markov Analysis)
				6.2.3.1 Advantages, Limitations, and Application of Markov Analysis
			6.2.4 Petri Nets
				6.2.4.1 Fault Tree and Petri Net Transformation
			6.2.5 Failure Mode Effects and Criticality Analysis (FMECA)
				6.2.5.1 Steps in Performing an FMECA
				6.2.5.2 Advantages of FMEA
			6.2.6 Accelerated Life Testing (ALT)
			6.2.7 Reliability Apportionment
		6.3 Design Analysis and Process
			6.3.1 Design for Reliability
				6.3.1.1 Design for Reliability Tools
				6.3.1.2 Design for Reliability Metrics
			6.3.2 Reliability Verification
			6.3.3 Analytical Physics
			6.3.4 Reliability Life Cycle
		6.4 Conclusions
		Bibliography
ch7
	7.1 Introduction
	7.2 Elements of Maintainability
		7.2.1 Maintainability and System Engineering
		7.2.2 Maintainability Analysis Process
		7.2.3 Maintainability Analysis Mathematics
	7.3 Availability of the Systems
		7.3.1 Availability of Repairable Systems
		7.3.2 Availability of Nonrepairable Systems
	Problems
	7.4 Conclusion
	Bibliography
ch8
	8.1 Introduction
	8.2 Reliability‐based Design
		8.2.1 Performance‐based Reliability
		8.2.2 RBDO Problem
		8.2.3 Probability Sufficiency Factor
		8.2.4 MCS Approach
		8.2.5 Latin Hyper Cube Design
		8.2.6 Artificial Neural Networks
		8.2.7 Real‐coded GA
	8.3 RBDO Methodology Using PSF and ANNs
		8.3.1 Case Study: EMI Shielding Design for the Required Load of 80 dB
	8.4 Conclusion
	Evaluation of Electromagnetic Shielding Effectiveness
	References
ch9
	9.1 Introduction
	9.2 Maintenance Actions on Maintained Systems
	9.3 Classifications of Imperfect Maintenance Categories
		9.3.1 Perfect, Imperfect, and Minimal Repairs
	9.4 Parametric Reliability Estimation Models for Maintained Systems
		9.4.1 Definitions
		9.4.2 Parametric Analysis Approaches
			9.4.2.1 Renewal Process
			9.4.2.2 Nonhomogeneous Poisson Process
	9.5 NHPP: Illustrative Example
	9.6 Generalized Renewal Process
		9.6.1 Arithmetic Reduction of Age Models
			9.6.1.1 Kijima ‐ I Model
			9.6.1.2 Kijima ‐ II Model
			9.6.1.3 Virtual Age based Reliability Metrics
	9.7 GRP: Illustrative Examples
	9.8 Conclusion
	Practice Problems
	References
ch10
	Chapter 10 Transmission System Reliability Evaluation Including Security
		10.1 Introduction
		10.2 Problem Formulation
		10.3 Monte Carlo Simulation for Evaluation of the Security Index: With and Without Considering the Absence of Transmission Lines
		10.4 Evaluation of the Load Flow\'s Minimal Eigenvalue Jacobian
		10.5 Evaluation of Schur\'s Inequality
		10.6 Evaluation of the PSI and the Cut‐set Approach
		10.7 Recurrent Neural Network (RNN) Assessment of Probabilistic Insecurity
		10.8 Results and Discussions
			10.8.1 IEEE Six‐Bus System
			10.8.2 IEEE 14‐Bus System
			10.8.3 IEEE 25‐Bus System
		10.9 Conclusions
		10.A.1 Data for IEEE six‐bus, seven‐line test system (100 MVA Base)
		10.A.2 Data for IEEE 14‐bus, 20‐line system (100 MVA Base)
		10.A.3 Data for IEEE 25‐bus, 35 line system (100 MVA Base)
		References
ch11
	11.1 Introduction
	11.2 Computation of Probabilistic Insecurity Index (PII) Using Cut‐set Technique
	11.3 Computation of Probabilistic Insecurity Index (PII) Sensitivity using ANN
	11.4 Voltage Security Enhancement using a Monovariable Approach
	11.5 Results and Discussion
		11.5.1 14‐bus System
		11.5.2 25‐bus System
	11.6 Conclusions
	References
ch12
	Chapter 12 Modern Aspects of Probabilistic Distributions for Reliability Evaluation of Engineering Systems
		12.1 Introduction
		12.2 Life Distribution of Power Components: An Overview
			12.2.1 Binomial Distribution
			12.2.2 Exponential Distribution
			12.2.3 Poisson Distribution
			12.2.4 Geometric Distribution
			12.2.5 Weibull Distribution
				12.2.5.1 Weibull Distribution Mean and Variance
			12.2.6 Normal Distribution
			12.2.7 Gamma Distribution
		12.3 Failure Distribution Functions for Reliability Evaluation
			12.3.1 Evaluation of Reliability Based on Exponential Distribution
			12.3.2 Reliability Evaluation Based on Weibull Distribution
			12.3.3 Normal Distribution‐based Reliability Evaluation
		12.4 Use of Exponential Model to Evaluate Reliability and MTBF
			12.4.1 Components Connected in Serial
			12.4.2 Parallel System
		12.5 Probabilistic Methods For Reliability Evaluation
			12.5.1 Gaussian Distribution Approach (GDA)
			12.5.2 Safety Factor Concept (SFC) and Peak Load Consideration (PLC)‐based Evaluation of Reliability
			12.5.3 LOLP Evaluation using Simpson\'s 1/3rd rule
		12.6 Additional Solved Examples
		12.7 Conclusion
		References
ch13
	13.1 Introduction
	13.2 Electrical Distribution Reliability Indices: Customer and Energy Based
	13.3 Defining the Problem
		13.3.1 DG Location Determination
		13.3.2 Connecting DGs in the System as Standby Units
		13.3.3 Analysis of Costs and Benefits
	13.4 The Flower Pollination Algorithm Overview
	13.5 Solution Approach
		13.5.1 Evaluation of the DG Locations (Steps)
		13.5.2 Evaluating the Optimized Solution with the Help of Flower Pollination Method (Steps)
		13.5.3 Analyzing the Costs and Benefits
	13.6 Discussions and Outcomes
		13.6.1 Roy Billinton Test System (RBTS‐2)
		13.6.2 Comparison Research
	13.7 Conclusion
	References
ch14
	14.1 Introduction
	14.2 Reward and Penalty System (RPS)
	14.3 Problem Identification
	14.4 Rao Algorithms: An Overview
	14.5 Steps to Solve the Problem
	14.6 A Discussion of the Findings
		14.6.1 Test System‐Bus 2 by Roy Billinton (RBTS‐2)
	14.7 Conclusion
	References
ch15
	15.1 Introduction
	15.2 Components Modeling in Composite Distribution System (CDS)
		15.2.1 Capacity Modeling
		15.2.2 Load Modeling
	15.3 Frequency‐Duration Concept for Reliability Indices Evaluation
	15.4 MCS‐Based Reliability Indices Evaluation of CDS
	15.5 Result and Discussion
	15.6 Illustrative Examples
	15.7 Conclusions
	References
ch16
	Chapter 16 Reliability Assessment of Distribution Systems Integrated with Renewable Energy Systems
		16.1 Introduction
		16.2 Reliability Functions
		16.3 Renewable Energy Sources
			16.3.1 Solar Energy
			16.3.2 Wind Energy
			16.3.3 Vehicle Charging‐Discharging
			16.3.4 Other Renewable Energy Sources
		16.4 Optimization and Control
		16.5 Case Study
			16.5.1 IEEE Reliability Test System‐79
			16.5.2 Roy Billinton Test System
			16.5.3 Bahir Dar\'s Power Distribution Test System
		16.6 Challenges and Future Directions
			16.6.1 Challenges
			16.6.2 Future Directions
		Problems
		Solution
		16.7 Conclusion
		References
ch17
	17.1 Introduction
	17.2 Reliability Indices
	17.3 Markov Process
	17.4 Reliability of the System
		17.4.1 System with Series Components
		17.4.2 System with Parallel Components
			17.4.2.1 Complex (Series–Parallel) System
		17.4.3 Renewable Hybrid PV System
			17.4.3.1 PV Arrays
			17.4.3.2 Converter
			17.4.3.3 Inverter
			17.4.3.4 Charge Controller and Solar Batteries
			17.4.3.5 DG Set
	17.5 Conclusion
	References
ch18
	18.1 Introduction
	18.2 Residual Magnetism in SEIG: Restoration and Loss
		18.2.1 Residual Magnetism Losses
		18.2.2 Residual Magnetism Restoration
	18.3 Problems with SEIG Excitation Failure in RE Systems
	18.4 SEIG Tests with Lowest Capacitive Excitation
	18.5 Rotor Core Magnetization of SEIG Reliability Assessment Using Least Capacitor Score
		18.5.1 Assessment of Reliability‐Related Functions
		18.5.2 Probabilities of Failure and Success
	18.6 Discussion and Outcomes
	18.7 Conclusion
	References
ch19
	19.1 Introduction
	19.2 Methodology
		19.2.1 Cell Temperature
		19.2.2 Degradation Equations
		19.2.3 Mean Life Without Cooling
		19.2.4 Mean Life After Cooling
			19.2.4.1 Mean Life with Cooling up to 25 °C
			19.2.4.2 Mean Life with Cooling up to 35 °C
			19.2.4.3 Mean Life with Cooling up to 45 °C
	19.3 Reliability Assessment
		19.3.1 Cooling up to 25 °C
		19.3.2 Cooling up to 35 °C
		19.3.3 Cooling up to 45 °C
	19.4 Probability Density Function
		19.4.1 Cooling up to 25 °C
		19.4.2 Cooling up to 35 °C
		19.4.3 Cooling up to 45 °C
	19.5 Cumulative Distribution Function
		19.5.1 Cooling up to 25 °C
		19.5.2 Cooling up to 35 °C
		19.5.3 Cooling up to 45°C
	19.6 Results
	19.7 Conclusion
	References
ch20
	20.1 Introduction
		20.1.1 Basic Reliability Estimation Concepts
		20.1.2 Hazard Rate Function
		20.1.3 Reliability Block Diagram
	20.2 Reliability Modeling of PV Topology
		20.2.1 Reliability Modeling of Central PV Topology
		20.2.2 Reliability Modeling of String PV Topology
		20.2.3 Reliability Modeling of Micro PV Topology
	20.3 Estimation of Failure Rate
		20.3.1 DC‐Link Capacitor
		20.3.2 Diodes
		20.3.3 Switch
		20.3.4 Filter
	20.4 Reliability Estimation Using RBD
		20.4.1 Central Topology
		20.4.2 String Topology
		20.4.3 Micro Topology
	20.5 Results
	20.6 Conclusions
	References
ch21
	Chapter 21 Reliability Evaluation of Power Electronics Converters for Modern Power System Applications
		21.1 Introduction
		21.2 Failures in Power Electronics Converters
			21.2.1 Catastrophic Failure
			21.2.2 Wear‐Out Failure
		21.3 Estimation and Monitoring of Junction Temperature
			21.3.1 Direct Method
			21.3.2 Indirect Method
				21.3.2.1 Estimation by Vceon(Ihigh)
				21.3.2.2 Estimation by Threshold Voltage (Vthr)
				21.3.2.3 Estimation by Short Circuit Current (SCC)
				21.3.2.4 Estimation by Turn‐On/Off Delay Time
				21.3.2.5 Estimation by Rgint with the Help of Igpeak
		21.4 Reliability of a Modern Power System
			21.4.1 Power Converter Availability Model
			21.4.2 HVDC Availability Model
			21.4.3 Reliability Model of Modern Power System
		21.5 Challenges and Future Directions
		References
ch22
	22.1 Introduction
	22.2 Electric Vehicles and Grid Integration
		22.2.1 Charging Infrastructure
		22.2.2 Load Management and Grid Stability
		22.2.3 Benefits and Challenges of Grid Integration
	22.3 Sub‐components of EVs
		22.3.1 Reliability Study of Sub‐components in EVs
			22.3.1.1 Methodologies of Reliability Studies
	22.4 Reliability Assessment Techniques in EVs
		22.4.1 Markov Model
		22.4.2 Monte Carlo Simulation (MCS)
		22.4.3 Contingency Enumeration Method
		22.4.4 State Space Method
		22.4.5 Electric Vehicles Trend
		22.4.6 Fundamental Considerations in Assessing the Reliability of EVs
		22.4.7 EVs Battery Management Systems (BMS)
	22.5 Evaluation of Distribution Systems Reliability with Integrated EVs
		22.5.1 Distribution Network (DN) Reliability Assessment
		22.5.2 Reliability Evaluation Using a V2G Approach and High EV Penetration
		22.5.3 Reliability Parameters
			22.5.3.1 Reliability Parameters of EVs
			22.5.3.2 Grid System Reliability Parameters
	22.6 Conclusion
	References
ch23
	23.1 Introduction
	23.2 Reliability Assessment Techniques
	23.3 Types of Multilevel Inverters (MLIs)
		23.3.1 Cascaded H‐Bridge Multilevel Inverters
		23.3.2 Neutral‐Point Clamped Three‐Level Inverter (NPC)
		23.3.3 Flying Capacitors Three‐Level Inverter
		23.3.4 Three‐Level T‐Type Inverter
	23.4 Comparative Reliability Assessment of MLIs
	23.5 Conclusion
	References
ch24
	24.1 Introduction
	24.2 Passive Snubber Circuit
		24.2.1 Surge Across Switch
	24.3 Selection of Turn‐OFF Snubber
		24.3.1 Snubbers Across Each Switching Device
			24.3.1.1 RC Snubber Circuit
			24.3.1.2 RCD Charge‐Discharge Snubber
			24.3.1.3 Discharge‐Suppressing RCD Snubber
		24.3.2 Lumped Snubbers Between Power Buses
			24.3.2.1 C Snubber
			24.3.2.2 RCD Snubber
	24.4 Design of a Discharge‐Suppressing RCD Snubber
	24.5 Simulation Results of RCD Snubber
	24.6 Reliability Aspects in Snubber Design for Industrial Power Applications
	24.7 Conclusion
	References
ch25
	25.1 Introduction
	25.2 Concept of PEDS Reliability in Modern Power System
	25.3 V‐Shape Model‐Based Reliability Assessment in PEDS
		25.3.1 Hierarchical Reliability Modeling and Assessment
		25.3.2 Model‐Based Reliability Enhancement
	25.4 Converter Reliability Modeling
	25.5 Conclusion and Future Challenges
	References
ch26
	26.1 Introduction
	26.2 Architecture and Operation of Microgrid
		26.2.1 Types of Microgrid
		26.2.2 Microgrid Technology
	26.3 Microgrid Control Strategies
		26.3.1 Advantages and Disadvantages of Microgrid
	26.4 Reliability Aspects in Microgrid Planning and Design
		26.4.1 Reliability Evaluation
		26.4.2 Energy Scheduling, Forecasting, and Optimization Techniques
		26.4.3 Reliability Aspects of Power Electronics in Microgrids
		26.4.4 Component to System: Layer‐Wise Reliability
	26.5 Conclusion and Future Challenges
	References
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index