Title
Dynamic State Estimation of Power Systems With Quantization Effects: A Recursive Filter Approach.
Abstract
In this paper, a recursive filter algorithm is developed to deal with the state estimation problem for power systems with quantized nonlinear measurements. The measurements from both the remote terminal units and the phasor measurement unit are subject to quantizations described by a logarithmic quantizer. Attention is focused on the design of a recursive filter such that, in the simultaneous presence of nonlinear measurements and quantization effects, an upper bound for the estimation error covariance is guaranteed and subsequently minimized. Instead of using the traditional approximation methods in nonlinear estimation that simply ignore the linearization errors, we treat both the linearization and quantization errors as norm-bounded uncertainties in the algorithm development so as to improve the performance of the estimator. For the power system with such kind of introduced uncertainties, a filter is designed in the framework of robust recursive estimation, and the developed filter algorithm is tested on the IEEE benchmark power system to demonstrate its effectiveness.
Year
DOI
Venue
2016
10.1109/TNNLS.2014.2381853
IEEE Trans. Neural Netw. Learning Syst.
Keywords
Field
DocType
recursive filter,nonlinear systems,state estimation.,power systems,quantized estimation
Nonlinear system,Computer science,Control theory,Phasor measurement unit,Electric power system,Recursive Bayesian estimation,Recursive filter,Quantization (signal processing),Linearization,Estimator
Journal
Volume
Issue
ISSN
PP
99
2162-2388
Citations 
PageRank 
References 
1
0.35
13
Authors
3
Name
Order
Citations
PageRank
Liang Hu1694.38
Zidong Wang211003578.11
Xiaohui Liu35042269.99