Journal ArticleDOI
Whither dynamic state estimation
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TLDR
In this article, the authors present some feasible directions along which investigations on dynamic state estimation have been carried out and could be developed in the future, and they show that the benefits which could be encountered from dynamic estimation are linked to its predictive ability which provides the necessary information to perform preventive analysis and control.About:
This article is published in International Journal of Electrical Power & Energy Systems.The article was published on 1990-04-01. It has received 70 citations till now. The article focuses on the topics: Extended Kalman filter & Observability.read more
Citations
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Journal ArticleDOI
Electric power system state estimation
TL;DR: In this article, the state of the art in electric power system state estimation is discussed, which is a key function for building a network real-time model, a quasi-static mathematical representation of the current conditions in an interconnected power network.
Journal ArticleDOI
Unscented kalman filter for power system dynamic state estimation
TL;DR: In this article, the unscented Kalman filter (UKF) is proposed for power system dynamic state estimation, which is based on the application of the Unscented Transformation (UT) combined with the Kalman Filter theory.
Journal ArticleDOI
Monitoring and Optimization for Power Grids: A Signal Processing Perspective
Georgios B. Giannakis,Vassilis Kekatos,Nikolaos Gatsis,Seung-Jun Kim,Hao Zhu,Bruce Wollenberg +5 more
TL;DR: In this article, the authors highlight the importance of the North American power grid as the most important engineering achievement of the 20th century, with particular emphasis on the integration of renewable energy resources.
Journal ArticleDOI
Forecasting-Aided State Estimation—Part I: Panorama
TL;DR: A comprehensive survey of forecasting-aided state estimators can be found in this article, where the main benefits achieved by state estimation with forecasting capability regarding: data redundancy, innovation analysis, observability, filtering, bad data, and network configuration and parameter error processing.
Journal ArticleDOI
Robust dynamic state estimation of power systems based on M-Estimation and realistic modeling of system dynamics
G. Durgaprasad,S.S. Thakur +1 more
TL;DR: In this paper, a new scheme of dynamic state estimation, utilizing a statistical approach called the M-Estimation to resolve the filtering problem robustly, has been presented, which has been tested on 5-bus, 14-bus and 30-bus test systems and the results are presented.
References
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Journal Article
Optimal Filtering
TL;DR: This book helps to fill the void in the market and does that in a superb manner by covering the standard topics such as Kalman filtering, innovations processes, smoothing, and adaptive and nonlinear estimation.
Journal ArticleDOI
A Dynamic Estimator for Tracking the State of a Power System
Atif S. Debs,Robert E. Larson +1 more
TL;DR: In this paper, the problem of real-time estimation of the state of a power system is treated from the point of view of the theory of least-squares estimation (Kalman-Bucy filtering).
State forecasting in electric power systems
TL;DR: In this paper, a new algorithm for forecasting and filtering the state vector, using exponential smoothing and least-squares estimation techniques, is presented, and compared with another one based on standard Kalman filtering theory.
Journal ArticleDOI
Detection of Topology Errors by State Estimation
Felix F. Wu,W.-H.E. Liu +1 more
TL;DR: In this article, the use of global information in state estimation to correct errors in the direct measurements of the status data is proposed and conditions for detectability of errors are analyzed, where the telemetered data of breaker and switch status are processed in the EMS computer to determine the present network topology of the system.
Journal ArticleDOI
A Two-Level Static State Estimator for Electric Power Systems
TL;DR: In this paper, a hierarchical concept is used to solve the static state estimation problem for large-scale composite power systems, and the solution is obtained by performing a two-level calculation.