Power system state estimation : theory and implementation

By Ali Abur, Antonio Gómez Expósito. 2004

2,806 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

In Electrical and Electronic Engineering

Citations in the corpus

Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach (2022, background): “…model for state estimation is described as follows: where z = { z 1 , z 2 , · · · , z I } is the measurement vector, which represents the power injection of each bus and the power ﬂow of each branch; Multiple approaches for solving the system state vectors x have been proposed in [29].”
Semidefinite programming for power system state estimation (2012, methodology): “For example, the most successful and widely used algorithm to solve the WLS state estimation problem is the Newton’s method [17].”
Cyber security analysis of state estimators in electric power systems (2010, methodology): “Detailed formulae relating measurements z and state x may be found in [11].”
Unified PMU Placement for Observability and Bad Data Detection in State Estimation (2014, background): “1) Identification of Critical Measurements: It is obvious that the null columns in correspond to critical measurements in , which is similar to the results in [4].”
Modeling Load Redistribution Attacks in Power Systems (2011, background): “Then measurement residuals can be expressed as (A.2) where matrix is called residual sensitivity matrix, representing the sensitivity of measurement residuals to the measurement errors [23].”
PMU Measurement Uncertainty Considerations in WLS State Estimation (2009, methodology): “The measurement uncertainties are commonly assumed to have the following statistical properties [21].”
Physical Authentication of Control Systems: Designing Watermarked Control Inputs to Detect Counterfeit Sensor Outputs (2015, methodology): “For example, traditional bad data detection techniques such as the largest residue test [3] have been widely used for systems with a static model, such as the power grid.”
Malicious Data Attacks on the Smart Grid (2011, background): “To this end, very little is known about the worst case scenario although the detection of interacting bad data has been considered [9], [20]–[22].”
Strategic Protection Against Data Injection Attacks on Power Grids (2011, methodology): “where is the vector of measurements, is the measurement Jacobian matrix of size , and is the measurement noise [3].”
Detecting False Data Injection Attacks on Power Grid by Sparse Optimization (2014, methodology): “State estimation [4], which estimates the power system operation state based on a real-time electric network model, is a key function of the Energy Management System (EMS).”
Transmission Line Conductor Temperature Impact on State Estimation Accuracy (2007, methodology): “Since the measurement error expectation values have been assumed to be zero, the most likely estimation in this case [1], [4] corresponds to the states minimizing the following objective function:”