Reliability Assessment of Electric Power Systems Using Monte Carlo Methods

The application of quantitative reliability evaluation in electric power sys- tems has now evolved to the point at which most utilities use these techniques in one or more areas of their planning, design, and operation. Most of the techniques in use are based on analytical models and resulting analytical evaluation procedures. Improvements in and availability of high-speed digi- tal computers have created the opportunity to analyze many of these prob- lems using stochastic simulation methods and over the last decade there has been increased interest in and use made of Monte Carlo simulation in quantitative power system reliability assessment. Monte Carlo simulation is not a new concept and recorded applications have existed for at least 50 yr. However, localized high-speed computers with large-capacity storage have made Monte Carlo simulation an available and sometimes preferable option for many power system reliability applications. Monte Carlo simulation is also an integral part of a modern undergrad- uate or graduate course on reliability evaluation of general engineering systems or specialized areas such as electric power systems. It is hoped that this textbook will help formalize the many existing applications of Monte Carlo simulation and assist in their integration in teaching programs. This book presents the basic concepts associated with Monte Carlo simulation.

Table of Contents:
1 Introduction.- 2 Basic Concepts of Power System Reliability Evaluation.- 3 Elements Of Monte Carlo Methods.- 4 Generating System Adequacy Assessment.- 5 Composite System Adequacy Assessment.- 6 Distribution System and Station Adequacy Assessment.- 7 Reliability Cost/Worth Assessment.- Appendix A Reliability Test Systems.- A.1. IEEE Reliability Test System (IEEE RTS).- A.1.1. Load Model.- A.1.2. Generating System.- A.1.3. Transmission System.- A.1.4. Additional Data.- A.2. Roy Billinton Test System (RBTS).- A.2.1. Brief Description of the RBTS.- A.2.2. Load Model.- A.2.3. Generating System.- A.2.4. Transmission System.- A.2.5. Station Data.- A.2.6. Reliability Worth Assessment Data.- A.3. References.- Appendix B Elements of Probability and Statistics.- B.1. Probability Concept and Calculation Rules.- B.1.1. Probability Concept.- B.1.2. Probability Calculation Rules.- B.2. Probability Distributions of Random Variables.- B.2.1. Probability Distribution Function and Density Function.- B.2.2. Important Distributions in Reliability Evaluation.- B.3. Numerical Characteristics of Random Variables.- B.3.1. Expectation and Variance.- B.3.2. Covariance and Correlation Function.- B.4. Limit Theorems.- B.4.1. Law of Large Numbers.- B.4.2. Central Limit Theorem.- B.5. Parameter Estimation.- B.5.1. Basic Definitions.- B.5.2. Sample Mean and Sample Variance.- B.6. References.- Appendix C Power System Analysis Techniques.- C.1. AC Load Flow Models.- C.1.1. Load Flow Equations.- C.1.2. Newton-Raphson Model.- C.1.3. Fast Decoupled Model.- C.2. DC Load Flow Models.- C.2.1. Basic Equations.- C.2.2. Relationship between Power Injections and Line Flows.- C.3. Optimal Power Flow.- C.4. Contingency Analysis.- C.5. References.- Appendix D Optimization Techniques.- D.1. Linear Programming.- D.1.1. Basic Concepts.- D.1.2. Generalized Simplex Method.- D.1.3. Duality Principle.- D.1.4. Dual Simplex Method.- D.1.5. Linear Programming Relaxation Technique.- D.2. Maximum Flow Method.- D.2.1. Basic Concepts.- D.2.2. Maximum Flow Problem.- D.3. References.