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Power System State Estimation : Theory and Implementation

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TLDR
In this paper, Peters and Wilkinson this paper proposed a WLS state estimation algorithm based on the Nodal Variable Formulation (NVF) and the Branch Variable Factorization (BVF).
Abstract
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

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Citations
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Journal ArticleDOI

Robust state estimation for power systems via moving horizon strategy

TL;DR: In this article, a re-weighted moving horizon estimation (RMHE) is proposed to improve the robustness of power systems by updating their error variances real-time and reweighting their contributions adaptively for robust power system state estimation.
Proceedings ArticleDOI

Tracking network state from combined SCADA and synchronized phasor measurements

TL;DR: In this article, the authors explore the possibility to track the network state using both SCADA and synchronized phasor measurements when a SCADA measurement is received, it is used in the next state reconstruction; otherwise it is replaced by a pseudo-measurement stemming from the previous state reconstruction.
Proceedings ArticleDOI

Branch current based state estimation for distribution system monitoring

TL;DR: In this article, a branch current-based state estimation (BCSE) method is used for real-time monitoring and control of a distribution feeder, and the authors discuss the properties of the method and its use when new data from various field devices become available such as Advanced Meeting Infrastructures.
Journal ArticleDOI

Forecast aided measurements data synchronisation in robust power system state estimation

TL;DR: In this paper, the robustness of the proposed method is guaranteed by rejecting outlier (large amplitude error) by forecasting conventional measurements data and using robustness property of the Kalman filter against noise in data (small amplitude error).
Journal ArticleDOI

Methodology for multiarea state estimation solved by a decomposition method

TL;DR: In this article, a decentralized optimization scheme with minimum information exchange among subsystems is proposed to solve the multi-area state estimation problem by a decomposition method, which is derived from the Lagrangian relaxation method and is named optimality condition decomposition.
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