Probabilistic Reliability Analysis of Power Systems: A Student’s Introduction

✍ Scribed by Bart W. Tuinema, José L. Rueda Torres, Alexandru I. Stefanov, Francisco M. Gonzalez-Longatt, Mart A. M. M. van der Meijden

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 337
• Category: Library

✦ Synopsis

This textbook provides an introduction to probabilistic reliability analysis of power systems. It discusses a range of probabilistic methods used in reliability modelling of power system components, small systems and large systems. It also presents the benefits of probabilistic methods for modelling renewable energy sources. The textbook describes real-life studies, discussing practical examples and providing interesting problems, teaching students the methods in a thorough and hands-on way.

The textbook has chapters dedicated to reliability models for components (reliability functions, component life cycle, two-state Markov model, stress-strength model), small systems (reliability networks, Markov models, fault/event tree analysis) and large systems (generation adequacy, state enumeration, Monte-Carlo simulation). Moreover, it contains chapters about probabilistic optimal power flow, the reliability of underground cables and cyber-physical power systems.

After reading this book, engineering students will be able to apply various methods to model the reliability of power system components, smaller and larger systems. The textbook will be accessible to power engineering students, as well as students from mathematics, computer science, physics, mechanical engineering, policy & management, and will allow them to apply reliability analysis methods to their own areas of expertise.

✦ Table of Contents

Preface
Contents
About the Authors
Part I Introduction
1 Introduction
1.1 Reliability of Power Systems
1.2 Definitions of Reliability and Risk
1.3 Reliability Analysis of Power Systems
1.3.1 Reliability Analysis Approach
1.3.2 Deterministic Versus Probabilistic Analysis
1.3.3 Software for Power System Reliability Analysis
1.3.4 Test Networks
1.4 Transmission System Operator (TSO) Activities
1.4.1 Three Main Processes
1.4.2 Grid Development
1.4.3 Asset Management
1.4.4 System Operation
1.4.5 Overview of TSO Activities
References
2 Power System Failures
2.1 Component Failure Statistics
2.1.1 Failure Frequencies
2.1.2 Repair Times
2.2 Component Failure Behavior
2.2.1 Concepts and Definitions
2.2.2 Causes of Component Failures
2.2.3 Protection System Failures
2.2.4 Resulting Faults
2.2.5 Dependency and Correlation
2.3 Historical Blackouts
2.3.1 Large Blackouts
2.3.2 Blackouts in the Netherlands
2.4 Conclusion
References
Part II Modeling
3 Reliability Models of Components
3.1 Reliability Functions
3.1.1 Basic Reliability Functions
3.1.2 Bathtub Curve
3.1.3 Negative Exponential Distribution
3.1.4 Weibull Distribution
3.2 Component Life Cycle
3.3 Two-State Markov Model
3.3.1 Unrepairable Component
3.3.2 Repairable Component
3.4 Stress-Strength Model
3.5 Conclusion
References
4 Reliability Models of Small Systems
4.1 Reliability Networks
4.1.1 Series Connections
4.1.2 Parallel Connections
4.1.3 Dependent Failures
4.1.4 Mixed Series-Parallel Networks
4.2 Markov Models
4.2.1 Creation of a Markov Model
4.2.2 Solution of the Markov Model
4.2.3 Markov Models of Individual Components
4.2.4 Markov Models of Small Systems
4.2.5 Reduction Techniques
4.3 Fault Tree and Event Tree Analysis
4.3.1 Fault Tree Analysis
4.3.2 Event Tree Analysis
4.4 Conclusion
References
5 Reliability Models of Large Systems
5.1 State Enumeration
5.1.1 Deterministic Contingency Analysis
5.1.2 Probabilistic Reliability Indicators
5.1.3 Probabilistic Cost Analysis
5.1.4 State Enumeration of Large Power Systems
5.1.5 State Enumeration as a (Partial) Markov Model
5.2 Generation Adequacy Analysis
5.2.1 Capacity Outage Probability Tables
5.2.2 COPT Calculation Algorithm
5.2.3 Loss of Load and Loss of Energy Indices
5.2.4 Capacity Credit of Wind Energy
5.2.5 Availability of Generators
5.3 Monte Carlo Simulation
5.3.1 Random Sampling of Component Failures
5.3.2 Monte Carlo Simulation Algorithm
5.4 Conclusion
References
Part III Applications
6 Probabilistic Power Flow Analysis
6.1 Uncertainties in Power Systems
6.1.1 Sources of Uncertainty
6.1.2 Load Modeling: The Gaussian Mixture Model
6.1.3 Load Modeling: Gaussian Mixture Model—Example
6.2 Power Flow Analysis
6.2.1 Deterministic Power Flow Analysis
6.2.2 Probabilistic Power Flow Analysis
6.3 Probabilistic Power Flow Example
6.3.1 Test System Description
6.3.2 Probabilistic Model of Generic Power Demand (Loads)
6.3.3 Probabilistic Model of Power Generation
6.3.4 Probabilistic Model of Balancing Technologies
6.3.5 Simulation Results
6.4 Conclusion
References
7 Extra-High-Voltage Underground Cables
7.1 Reliability of Overhead Line and Underground Cable Connections
7.1.1 Failure Statistics
7.1.2 Reliability Calculations of Connections
7.1.3 Failures in the Randstad380 Zuid Cable Connection
7.1.4 Solutions to Improve the Reliability
7.2 Reliability Analysis of the Dutch Transmission Network
7.2.1 Approach of the Study
7.2.2 Reliability of the Maasvlakte Region Network
7.2.3 Underground Cables in the Dutch Transmission Network
7.3 Conclusion
References
8 Cyber-Physical System Modeling for Assessment and Enhancement of Power Grid Cyber Security, Resilience, and Reliability
8.1 Acronyms
8.2 The Cyber-Physical Power System
8.3 Cyber Security and Resilience of Power Grids
8.3.1 Security Controls for Power Grids
8.3.2 Power Grid Vulnerabilities
8.3.3 Research on Cyber Security and Resilience of Cyber-Physical Power Systems
8.3.4 Resilience of Cyber-Physical Power Systems to Natural Disasters
8.4 Cyber-Physical System Modeling
8.4.1 Power System Layer
8.4.2 Cyber System Layer
8.5 Cyber-Physical System Testbed
8.6 Cyber Attacks on Power Grids
8.7 Conclusion
References
Part IV Conclusion
9 Conclusion
Appendix A Probability and Statistics
A.1 Probability
A.2 Statistics
Appendix B Load Flow Calculations
B.1 Connectivity Study
B.2 Graph Flow
B.3 AC Load Flow
B.4 DC Load Flow
Appendix C Reliability Indicators
Appendix D Solutions
Index