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E-raamat: Computational Methods for Electric Power Systems

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(Missouri University of Science and Technology, Rolla, USA)
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Computational Methods for Electric Power Systems introduces computational methods that form the basis of many analytical studies in power systems. The book provides the background for a number of widely used algorithms that underlie several commercial software packages, linking concepts to power system applications. By understanding the theory behind many of the algorithms, the reader can make better use of the software and make more informed decisions (e.g., choice of integration method and step size in simulation packages).

This Third Edition contains new material on preconditioners for linear iterative methods, Broydens method, and Jacobian-free NewtonKrylov methods. It includes additional problems and examples, as well as updated examples on sparse lower-upper (LU) factorization. It also adds coverage of the eigensystem realization algorithm and the double-shift method for computing complex eigenvalues.

Arvustused

"This book analyzes the most relevant mathematical tools for power system analysis. It is well written, well balanced, and treats the mathematical issues with a good degree of rigor and clarity. The numerical examples are illustrative and useful. ... Im considering to adopt this book for my course, since it condenses in a unique reference the mathematical backbone of the most important power system analysis tools." Alfredo Vaccaro, University of Sannio, Benevento, Italy

"This book fits well into my short circuit analysis course (ECE610). ... The textbook flows, and it is a good reference book even if it is not used as a textbook. ... This book is a must for any power systems faculty. ... This textbook can be a great complement to other textbooks that do not cover the material in depth. The sequential examples presented make this book quite friendly to the students." Bruno Osorno, California State University, Northridge, USA

" presents a nonconventional approach to teach or understand power system analysis: mathematics first, then each topic is related to power system applications. This approach is ideal for researchers and graduate students, and can immediately lead them into the power system field. Algorithms, however sophisticated, are explained with clarity, along with numerical examples to help the reader get the point." Lingling Fan, University of South Florida, Tampa, USA

" an excellent combination of topics regarding computational aspects and numerical algorithms for power system analysis, operations, and control. very useful for me to teach ECE530 [ on analysis techniques for large-scale energy systems]." Hao Zhu, University of Illinois, Urbana-Champaign, USA

" an excellent textbook for a graduate-level course in electric power engineering. covers a broad range of topics related to computational methods for power systems. contains very good problems for students homework. I highly recommend this book for graduate teaching in electric power." Fangxing Li, University of Tennessee, Knoxville, USA

"This book is complete in respect to the tools used for power system engineering. ... It is compact and nicely written. ... Many commercial packages are available in the market. They are just used in input-output form. Students never get the feeling of the methods used inside. It is required to understand the methods. [ Thus,] this book is very useful." Professor SN Singh, Department of Electrical Engineering, Indian Institute of Technology Kanpur

Preface to the third edition xi
1 Introduction
1(2)
2 The Solution of Linear Systems
3(50)
2.1 Gaussian Elimination
4(5)
2.2 LU Factorization
9(14)
2.2.1 LU Factorization with Partial Pivoting
16(4)
2.2.2 LU Factorization with Complete Pivoting
20(3)
2.3 Condition Numbers and Error Propagation
23(1)
2.4 Stationary Iterative Methods
24(6)
2.5 Conjugate Gradient Methods
30(6)
2.6 Generalized Minimal Residual Algorithm
36(6)
2.7 Preconditioners for Iterative Methods
42(5)
2.7.1 Jacobi
42(1)
2.7.2 Symmetric Successive Overrelaxation
43(1)
2.7.3 Symmetric Gauss--Seidel
43(1)
2.7.4 Incomplete LU Factorization
43(1)
2.7.5 Graph Based
44(3)
2.8 Problems
47(6)
3 Systems of Nonlinear Equations
53(64)
3.1 Fixed-Point Iteration
54(7)
3.2 Newton--Raphson Iteration
61(7)
3.2.1 Convergence Properties
64(1)
3.2.2 The Newton--Raphson for Systems of Nonlinear Equations
65(3)
3.3 Quasi-Newton Methods
68(15)
3.3.1 Secant Method
69(3)
3.3.2 Broyden's Method
72(2)
3.3.3 Modifications to the Newton--Raphson Method
74(1)
3.3.4 Numerical Differentiation
75(4)
3.3.5 Newton--GMRES
79(4)
3.4 Continuation Methods
83(3)
3.5 Power System Applications
86(27)
3.5.1 Power Flow
87(8)
3.5.2 Regulating Transformers
95(4)
3.5.3 Decoupled Power Flow
99(2)
3.5.4 Fast Decoupled Power Flow
101(4)
3.5.5 PV Curves and Continuation Power Flow
105(7)
3.5.6 Three-Phase Power Flow
112(1)
3.6 Problems
113(4)
4 Sparse Matrix Solution Techniques
117(46)
4.1 Storage Methods
118(9)
4.2 Sparse Matrix Representation
127(1)
4.3 Ordering Schemes
127(25)
4.3.1 Scheme 0
141(1)
4.3.2 Scheme I
142(6)
4.3.3 Scheme II
148(3)
4.3.4 Other Schemes
151(1)
4.4 Power System Applications
152(4)
4.5 Problems
156(7)
5 Numerical Integration
163(56)
5.1 One-Step Methods
164(2)
5.1.1 Taylor Series-Based Methods
164(1)
5.1.2 Forward Euler Method
165(1)
5.1.3 Runge--Kutta Methods
165(1)
5.2 Multistep Methods
166(10)
5.2.1 Adams Methods
172(3)
5.2.2 Gear's Methods
175(1)
5.3 Accuracy and Error Analysis
176(4)
5.4 Numerical Stability Analysis
180(7)
5.5 Stiff Systems
187(4)
5.6 Step Size Selection
191(7)
5.7 Differential-Algebraic Equations
198(2)
5.8 Power System Applications
200(11)
5.8.1 Transient Stability Analysis
200(8)
5.8.2 Midterm Stability Analysis
208(3)
5.9 Problems
211(8)
6 Optimization
219(54)
6.1 Least Squares State Estimation
220(10)
6.1.1 Weighted Least Squares Estimation
223(3)
6.1.2 Bad Data Detection
226(3)
6.1.3 Nonlinear Least Squares State Estimation
229(1)
6.2 Linear Programming
230(10)
6.2.1 Simplex Method
231(4)
6.2.2 Interior Point Method
235(5)
6.3 Nonlinear Programming
240(11)
6.3.1 Quadratic Programming
241(2)
6.3.2 Steepest Descent Algorithm
243(5)
6.3.3 Sequential Quadratic Programming Algorithm
248(3)
6.4 Power System Applications
251(15)
6.4.1 Optimal Power Flow
251(11)
6.4.2 State Estimation
262(4)
6.5 Problems
266(7)
7 Eigenvalue Problems
273(42)
7.1 The Power Method
274(2)
7.2 The QR Algorithm
276(10)
7.2.1 Deflation
283(1)
7.2.2 Shifted QR
283(1)
7.2.3 Double Shifted QR
284(2)
7.3 Arnoldi Methods
286(7)
7.4 Singular Value Decomposition
293(3)
7.5 Modal Identification
296(15)
7.5.1 Prony Method
298(3)
7.5.2 The Matrix Pencil Method
301(1)
7.5.3 The Levenberg--Marquardt Method
302(3)
7.5.4 Eigensystem Realization Algorithm
305(1)
7.5.5 Examples
306(5)
7.6 Power System Applications
311(1)
7.6.1 Participation Factors
311(1)
7.7 Problems
312(3)
References 315(6)
Index 321
Mariesa L. Crow is a professor of electrical engineering at the Missouri University of Science and Technology, Rolla, USA. Dr. Crow is director of the Energy Research and Development Center. Her areas of research include computer-aided analysis of power systems; dynamics and security analysis; voltage stability; computational algorithms for analyzing stressed, non-linear, non-continuous systems; power-electronic applications in bulk power systems (FACTS); and parameter estimation.
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