Interval Methods for Uncertain Power System Analysis
1st Edition
Published on 25. July 2023
Book
Hardback
144 pages
978-1-119-85504-0 (ISBN)
Description
Interval Methods for Uncertain Power System Analysis In Interval Methods for Uncertain Power System Analysis, accomplished engineer Dr. Alfredo Vaccaro delivers a comprehensive discussion of the mathematical foundations of range analysis and its application to solving traditional power system operation problems in the presence of strong and correlated uncertainties. The book explores highly relevant topics in the area, from interval methods for uncertainty representation and management to a variety of application examples.
The author offers readers the latest methodological breakthroughs and roadmaps to implementing the mathematics discussed within, as well as best practices commonly employed across the industry. Interval Methods for Uncertain Power System Analysis includes examinations of linear and non-linear equations, as well as:
A thorough introduction to reliable computing, including discussions of interval arithmetic and interval-based operators
Comprehensive explorations of uncertain power flow analysis, including discussions of problem formulation and sources of uncertainty in power flow analysis
In-depth examinations of uncertain optimal power flow analysis
Fulsome discussions of uncertain small signal stability analysis, including treatments of how to compute eigenvalues of uncertain matrices
Perfect for engineers working in power flow and optimal power flow analyses, optimization theory, and computer aided simulation, Interval Methods for Uncertain Power System Analysis will also earn a place in the libraries of researchers and graduate students studying decision making under uncertainty in power systems operation.
The author offers readers the latest methodological breakthroughs and roadmaps to implementing the mathematics discussed within, as well as best practices commonly employed across the industry. Interval Methods for Uncertain Power System Analysis includes examinations of linear and non-linear equations, as well as:
A thorough introduction to reliable computing, including discussions of interval arithmetic and interval-based operators
Comprehensive explorations of uncertain power flow analysis, including discussions of problem formulation and sources of uncertainty in power flow analysis
In-depth examinations of uncertain optimal power flow analysis
Fulsome discussions of uncertain small signal stability analysis, including treatments of how to compute eigenvalues of uncertain matrices
Perfect for engineers working in power flow and optimal power flow analyses, optimization theory, and computer aided simulation, Interval Methods for Uncertain Power System Analysis will also earn a place in the libraries of researchers and graduate students studying decision making under uncertainty in power systems operation.
More details
Series
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 13 mm
Weight
375 gr
ISBN-13
978-1-119-85504-0 (9781119855040)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Alfredo Vaccaro
Interval Methods for Uncertain Power System Analysis
E-Book
07/2023
1st Edition
Wiley
€103.99
Available for download
Alfredo Vaccaro
Interval Methods for Uncertain Power System Analysis
E-Book
07/2023
1st Edition
Wiley
€106.99
Available for download
Person
Alfredo Vaccaro, PhD, is a Full Professor of Electric Power Systems in the Department of Engineering at the University of Sannio. He is Editor-in-Chief of Technology and Economics of Smart Grids and Sustainable Energy, Springer Nature and Chair of the PES-IEEE Task Force on Enabling Paradigms for High-Performance Computing in Wide Area Monitoring Protective and Control Systems.
Content
About the Author ix
Preface xi
Acknowledgments xiii
Acronyms xv
Introduction 1
1 Introduction to Reliable Computing 3
1.1 Elements of Reliable Computing 4
1.2 Interval Analysis 7
1.3 Interval-Based Operators 8
1.4 Interval Extensions of Elementary Functions 9
1.5 Solving Systems of Linear Interval Equations 11
1.6 Finding Zeros of Nonlinear Equations 15
1.7 Solution of Systems of Nonlinear Interval Equations 16
1.8 The Overestimation Problem 20
1.9 Affine Arithmetic 22
1.9.1 Conversion Between AA and IA 25
1.9.2 AA-Based Operators 25
1.9.3 Chebyshev Approximation of Univariate Nonaffine Functions 28
1.9.4 Multiplication of Affine Forms 31
1.9.5 Effects of Recursive Solution Schemes 35
1.10 Integrating AA and IA 35
2 Uncertain Power Flow Analysis 37
2.1 Sources of Uncertainties in Power Flow Analysis 39
2.2 Solving Uncertain Linearized Power Flow Equations 41
2.3 Solving Uncertain Power Flow Equations 46
2.3.1 Optimization-Based Method 48
2.3.2 Domain Contraction Method 52
3 Uncertain Optimal Power Flow Analysis 59
3.1 Range Analysis-Based Solution 61
3.1.1 Optimal Economic Dispatch 63
3.1.2 Reactive Power Dispatch 66
3.2 AA-Based Solution 70
4 Uncertain Markov Chain Analysis 75
4.1 Mathematical Preliminaries 77
4.2 Effects of Data Uncertainties 78
4.3 Matrix Notation 79
4.4 AA-Based Uncertain Analysis 80
4.5 Application Examples 83
4.5.1 Case Study 1: Grid Resilience Analysis 83
4.5.2 Case Study 2: Energy Storage Model 84
4.5.3 Summary 86
5 Small-Signal Stability Analysis of Uncertain Power Systems 87
5.1 Problem Formulation 89
5.2 The Interval Eigenvalue Problem 90
5.3 Applications 92
5.3.1 Case Study 1 92
5.3.2 Case Study 2 93
6 Uncertain Power Components Thermal Analysis 95
6.1 Thermal Rating Assessment of Overhead Lines 96
6.1.1 Sources of Data Uncertainties 98
6.1.2 AA-Based Thermal Rating Assessment 99
6.1.3 Application Examples 100
6.2 Thermal Rating Assessment of Power Cables 104
6.2.1 Thermal Modeling of Power Cables 105
6.2.2 Sources of Data Uncertainties 107
6.2.3 Tolerance Analysis of Cable Thermal Dynamics by IA 108
6.2.4 Application Examples 109
References 112
Index 119
Preface xi
Acknowledgments xiii
Acronyms xv
Introduction 1
1 Introduction to Reliable Computing 3
1.1 Elements of Reliable Computing 4
1.2 Interval Analysis 7
1.3 Interval-Based Operators 8
1.4 Interval Extensions of Elementary Functions 9
1.5 Solving Systems of Linear Interval Equations 11
1.6 Finding Zeros of Nonlinear Equations 15
1.7 Solution of Systems of Nonlinear Interval Equations 16
1.8 The Overestimation Problem 20
1.9 Affine Arithmetic 22
1.9.1 Conversion Between AA and IA 25
1.9.2 AA-Based Operators 25
1.9.3 Chebyshev Approximation of Univariate Nonaffine Functions 28
1.9.4 Multiplication of Affine Forms 31
1.9.5 Effects of Recursive Solution Schemes 35
1.10 Integrating AA and IA 35
2 Uncertain Power Flow Analysis 37
2.1 Sources of Uncertainties in Power Flow Analysis 39
2.2 Solving Uncertain Linearized Power Flow Equations 41
2.3 Solving Uncertain Power Flow Equations 46
2.3.1 Optimization-Based Method 48
2.3.2 Domain Contraction Method 52
3 Uncertain Optimal Power Flow Analysis 59
3.1 Range Analysis-Based Solution 61
3.1.1 Optimal Economic Dispatch 63
3.1.2 Reactive Power Dispatch 66
3.2 AA-Based Solution 70
4 Uncertain Markov Chain Analysis 75
4.1 Mathematical Preliminaries 77
4.2 Effects of Data Uncertainties 78
4.3 Matrix Notation 79
4.4 AA-Based Uncertain Analysis 80
4.5 Application Examples 83
4.5.1 Case Study 1: Grid Resilience Analysis 83
4.5.2 Case Study 2: Energy Storage Model 84
4.5.3 Summary 86
5 Small-Signal Stability Analysis of Uncertain Power Systems 87
5.1 Problem Formulation 89
5.2 The Interval Eigenvalue Problem 90
5.3 Applications 92
5.3.1 Case Study 1 92
5.3.2 Case Study 2 93
6 Uncertain Power Components Thermal Analysis 95
6.1 Thermal Rating Assessment of Overhead Lines 96
6.1.1 Sources of Data Uncertainties 98
6.1.2 AA-Based Thermal Rating Assessment 99
6.1.3 Application Examples 100
6.2 Thermal Rating Assessment of Power Cables 104
6.2.1 Thermal Modeling of Power Cables 105
6.2.2 Sources of Data Uncertainties 107
6.2.3 Tolerance Analysis of Cable Thermal Dynamics by IA 108
6.2.4 Application Examples 109
References 112
Index 119