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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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Journal ArticleDOI

Robust Ensemble Kalman Filter for Medium-Voltage Distribution System State Estimation

TL;DR: In the proposed solution, low-voltage measurements at the LV side of secondary substations are used together with the mathematical model of the MV/LV substations to derive new equivalent MV measurements, which yields the improvement of measurement redundancy and robustness of the REnKF to bad data and unknown system process noise.
Proceedings ArticleDOI

Statistical outlier detection for diagnosis of cyber attacks in power state estimation

TL;DR: To detect the presence of stealthy attacks on alternating current (AC) static state estimation through false data injection using a recently proposed machine learning technique called density ratio estimation, the proposed method offers an improved detection.
Proceedings ArticleDOI

Phasor state estimation from PMU measurements with bad data

TL;DR: This work establishes the equivalence between the approaches of bad data removal and bad data estimation and subtraction, and proposes two new algorithms by exploiting the sparsity of the bad data.
Proceedings ArticleDOI

A comparative study of the methods of inclusion of PMU current phasor measurements in a hybrid state estimator

TL;DR: In this article, the authors compared three different methods of inclusion of current phasor measurements by PMUs in the conventional power system state estimator, and provided a comprehensive formulation of the hybrid estimator in the presence of conventional and PMU measurements.
Journal ArticleDOI

Probabilistic Joint State Estimation for Operational Planning

TL;DR: A graphical model for probabilistic SE modeling that captures both the uncertainties and the power grid via embedding physical laws, i.e., KCL and KVL is described.
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