Power System State Estimation: Theory and Implementation(Power Engineering Willis)

Offering an up-to-date account of the strategies utilized in state estimation of electric power systems, this text provides a broad overview of power system operation and the role of state estimation in overall energy management. It uses an abundance of examples, models, tables, and guidelines to clearly examine new aspects of state estimation, the testing of network observability, and methods to assure computational efficiency.

Includes numerous tutorial examples that fully analyze problems posed by the inclusion of current measurements in existing state estimators and illustrate practical solutions to these challenges.

Written by two expert researchers in the field, Power System State Estimation extensively details topics never before covered in depth in any other text, including novel robust state estimation methods, estimation of parameter and topology errors, and the use of ampere measurements for state estimation. It introduces various methods and computational issues involved in the formulation and implementation of the weighted least squares (WLS) approach, presents statistical tests for the detection and identification of bad data in system measurements, and reveals alternative topological and numerical formulations for the network observability problem.



Table of Contents:
Preface

INTRODUCTION
Operating States of a Power System
Power System Security Analysis
State Estimation
Summary

WEIGHTED LEAST SQUARES STATE ESTIMATION
Introduction
Component Modeling and Assumptions
Building the Network Model
Maximum Likelihood Estimation
Measurement Model and Assumptions
WLS State Estimation Algorithm
Decoupled Formulation of the WLS State Estimation
DC State Estimation Model
Problems
References

ALTERNATIVE FORMULATIONS OF THE WLS STATE ESTIMATION
Weaknesses of the Normal Equations Formulation
Orthogonal Factorization
Hybrid Method
Method of Peters and Wilkinson
Equality-Constrained WLS State Estimation
Augmented Matrix Approach
Blocked Formulation
Comparison of Techniques
Problems
References

NETWORK OBSERVABILITY ANALYSIS
Networks and Graphs
NetworkMatrices
LoopEquations
Methods of Observability Analysis
Numerical Method Based on the Branch Variable Formulation
Numerical Method Based on the Nodal Variable Formulation
Topological Observability Analysis Method
Determination of Critical Measurements
Measurement Design
Summary
Problems
References

BAD DATA DETECTION AND IDENTIFICATION
Properties of Measurement Residuals
Classification of Measurements
Bad Data Detection and IdentiRability
Bad Data Detection
Properties of Normalized Residuals
Bad Data Identification
Largest Normalized Residual Test
Hypothesis Testing Identification (HTI)
Summary
Problems
References

ROBUST STATE ESTIMATION
Introduction
Robustness and Breakdown Points
Outliers and Leverage Points
M-Estimators
Least Absolute Value (LAV) Estimation
Discussion
Problems
References

NETWORK PARAMETER ESTIMATION
Introduction
Influence of Parameter Errors on State Estimation Results
Identification of Suspicious Parameters
Classification of Parameter Estimation Methods
Parameter Estimation Based on Residua! Sensitivity Analysis
Parameter Estimation Based on State Vector Augmentation
Parameter Estimation Based on Historical Series of Data
Transformer Tap Estimation
Observability of Network Parameters
Discussion
Problems
References

TOPOLOGY ERROR PROCESSING
Introduction
Types of Topology Errors
Detection of Topology Errors
Classification of Methods for Topology Error Analysis
Preliminary Topology Validation
Branch Status Errors
Substation Configuration Errors
Substation Graph and Reduced Model
Implicit Substation Model: State and Status Estimation
Observability Analysis Revisited
Problems
References

STATE ESTIMATION USING AMPERE MEASUREMENTS
Introduction
Modeling of Ampere Measurements
Difficulties in Using Ampere Measurements
Inequality-Constrained State Estimation
Heuristic Determination of F-# Solution Uniqueness
Algorithmic Determination of Solution Uniqueness
Identification of Nonuniquely Observable Branches
Measurement Classification and Bad Data Identification
Problems
References

Appendix A Review of Basic Statistics
Appendix B Review of Sparse Linear Equation Solution
References
Index