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Resilient decentralized consensus-based state estimation for smart grid in presence of false data

Etemad, Reza Hassani and Lahouti, Farshad (2016) Resilient decentralized consensus-based state estimation for smart grid in presence of false data. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016. IEEE , Piscataway, NJ, pp. 3466-3470. ISBN 978-1-4799-9988-0. http://resolver.caltech.edu/CaltechAUTHORS:20170111-141027940

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Abstract

State estimation is an essential part of energy management system in smart grid as it is a basis for many of the associated management and control processes. In this paper, we present a decentralized state estimation approach, based on consensus optimization and the alternating direction method of multipliers, that is robust against certain harsh class of false data injection schemes. The proposed scheme provides a reliable estimate of the global system state in a distributed manner even if the system is regionally unobservable to some regional controllers, but globally observable across regions. The scheme also accommodates different communication network topologies for a given power network. We assess the performance of the presented schemes on IEEE 14 and 118 bus test systems.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1109/ICASSP.2016.7472321DOIArticle
http://ieeexplore.ieee.org/document/7472321/PublisherArticle
Additional Information:© 2016 IEEE. Date Added to IEEE Xplore: 19 May 2016.
Subject Keywords:State Estimation, Smart Grid, ADMM
Record Number:CaltechAUTHORS:20170111-141027940
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170111-141027940
Official Citation:R. H. Etemad and F. Lahouti, "Resilient decentralized consensus-based state estimation for smart grid in presence of false data," 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, 2016, pp. 3466-3470. doi: 10.1109/ICASSP.2016.7472321
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:73440
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:20 Jan 2017 07:06
Last Modified:20 Jan 2017 07:06

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