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Power system state estimation: theory and implementation
Abur, Ali,
- ISBN:0824755707
- Call Number : TK 1005 .A264 2004
- Main Entry: Abur, Ali, 1957-
- Title:Power system state estimation: theory and implementation / Ali Abur, Antonio Gomez Exposito.
- Publisher:New York, NY : Marcel Dekker, 2004.
- Physical Description:xiv, 327 p.: ill.; 24 cm
- Series:Power engineering
- Notes:"Also in electronic format is available"
- Notes:Includes bibliographical references and index
- Subject:Electric power systems -- State estimation.
- Added Entry:Gomez Exposito, Antonio.
Power system state estimation: theory and implementationمحتواي کتاب
- dke507_fm.pdf
- DKE507_CH01.pdf
- DKE507_CH02.pdf
- Power System State Estimation: Theory and Implementation
- Contents
- Chapter 2: Weighted Least Squares State Estimation
- Power System State Estimation: Theory and Implementation
- DKE507_CH03.pdf
- DKE507_CH04.pdf
- Power System State Estimation: Theory and Implementation
- Contents
- Chapter 4: Network Observability Analysis
- 4.1 Networks and Graphs
- 4.2 Network Matrices
- 4.3 Loop Equations
- 4.4 Methods of Observability Analysis
- 4.5 Numerical Method Based on the Branch Variable Formulation
- 4.6 Numerical Method Based on the Nodal Variable Formulation
- 4.7 Topological Observability Analysis Method
- 4.8 Determination of Critical Measurements
- 4.9 Measurement Design
- 4.10 Summary
- 4.11 Problems
- References
- Power System State Estimation: Theory and Implementation
- DKE507_CH05.pdf
- Power System State Estimation: Theory and Implementation
- Contents
- Chapter 5: Bad Data Detection and Identification
- 5.1 Properties of Measurement Residuals
- 5.2 Classification of Measurements
- 5.3 Bad Data Detection and IdentiRability
- 5.4 Bad Data Detection
- 5.5 Properties of Normalized Residuals
- 5.6 Bad Data Identification
- 5.7 Largest Normalized Residual (rNMax ) Test
- 5.8 Hypothesis Testing Identification ( HTI)
- 5.9 Summary
- 5.10 Problems
- References
- Power System State Estimation: Theory and Implementation
- DKE507_CH06.pdf
- DKE507_CH07.pdf
- Power System State Estimation: Theory and Implementation
- Contents
- Chapter 7: Network Parameter Estimation
- 7.1 Introduction
- 7.2 Influence of parameter errors on state estimation results
- 7.3 Identification of suspicious parameters
- 7.4 Classification of parameter estimation methods
- 7.5 Parameter estimation based on residual sensitivity analysis
- 7.6 Parameter estimation based on state vector augmentation
- 7.7 Parameter estimation based on historical series of data
- 7.8 Transformer tap estimation
- 7.9 Observability of network parameters
- 7.10 Discussion
- 7.11 Problems
- References
- Power System State Estimation: Theory and Implementation
- DKE507_CH08.pdf
- Power System State Estimation: Theory and Implementation
- Contents
- Chapter 8: Topology Error Processing
- 8.1 Introduction
- 8.2 Types of topology errors
- 8.3 Detection of topology errors
- 8.4 Classification of methods for topology error analysis
- 8.5 Preliminary topology validation
- 8.6 Branch status errors
- 8.7 Substation configuration errors
- 8.8 Substation graph and reduced model
- 8.9 Implicit substation model: state and status estimation
- 8.10 Observability analysis revisited
- 8.11 Problems
- References
- Power System State Estimation: Theory and Implementation
- DKE507_appa.pdf
- Power System State Estimation: Theory and Implementation
- Contents
- Appendix A: Review of Basic Statistics
- A.1 Random Variables
- A.2 The Distribution Function ( d. f.), F( x)
- A.3 The Probability Density Function ( p. d. f),
- A.4 Continuous Joint Distributions
- A.5 Independent Random Variables
- A.6 Conditional Distributions
- A.7 Expected Value
- A.8 Variance
- A.9 Median
- A.10 Mean Squared Error
- A.11 Mean Absolute Error
- A.12 Covariance
- A.13 Normal Distribution
- A 14 Standard Normal Distribution
- A.15 Properties of Normally Distributed Random Variables
- A.16 Distribution of Sample Mean
- A.17 Likelihood Function and Maximum Likelihood Estimator
- A. 18 Central Limit Theorem for the Sample Mean
- Power System State Estimation: Theory and Implementation
- DKE507_appb.pdf
- Power System State Estimation: Theory and Implementation
- Contents
- Appendix B: Review of Sparse Linear Equation Solution
- B.1 Solution by Direct Methods
- B.2 Elementary Matrices
- B.3 LU Factorization Using Elementary Matrices
- B.4 Factorization Path Graph
- B.5 Sparse Forward/ Back Substitutions
- B.6 Solution of Modified Equations
- B.7 Sparse Inverse
- B.8 Orthogonal Factorization
- B.9 Storage and Retrieval of Sparse Matrix Elements
- B.10 Inserting and/or Deleting Elements in a Linked List
- References
- Power System State Estimation: Theory and Implementation
- DKE507_CH09.pdf
- Power System State Estimation: Theory and Implementation
- Contents
- Chapter 9: State Estimation Using Ampere Measurements
- 9.1 Introduction
- 9.2 Modeling of Ampere Measurements
- 9.3 Difficulties in Using Ampere Measurements
- 9.4 Inequality- Constrained State Estimation
- 9.5 Heuristic Determination of , P-0 Solution Uniqueness
- 9.6 Algorithmic Determination of Solution Uniqueness
- 9.7 Identification of Nonuniquely Observable Branches
- 9.8 Measurement Classification and Bad Data Identification
- 9.9 Problems
- References
- Power System State Estimation: Theory and Implementation