Privacy preserving decentralized power system state estimation with phasor measurement units

Neelabh Kashyap, Stefan Werner, Yih Fang Huang, Reza Arablouei

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

This paper presents a privacy preserving approach to decentralized state estimation in multi-area power systems. By formulating state estimation as a model-distributed regularized least-squares (MDRLS) problem, we ensure that the state variables and system matrix of each area are hidden from all other areas in order to protect privacy and sensitive information. We present a scheme that solves the primal MDRLS problem using the alternating direction method of multipliers, and a second method that solves the dual problem using a distributed form of the coordinate descent algorithm. Only information related to current measurements on tie-lines linking neighboring areas is exchanged between those areas. The proposed schemes enable the local state estimator in each area to estimate the voltage magnitude and phase angle of each bus in its own control area from phasor measurement units (PMU) without the need for full local PMU-observability. The novelty of the proposed methods is in that they employ the inherently hierarchical architecture of the wide-area monitoring system to perform decentralized state estimation. Our simulation results show that the estimation error of both methods converges to that of the centralized approach.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016
Number of pages5
Volume2016-September
ISBN (Electronic)9781509021031
DOIs
Publication statusPublished - 15 Sep 2016
MoE publication typeA4 Article in a conference publication
EventIEEE Sensor Array and Multichannel Signal Processing Workshop - Rio de Janeiro, Brazil
Duration: 10 Jul 201613 Jul 2016
Conference number: 9

Publication series

NameIEEE Workshop on Sensor Array and Multichannel Signal Processing
PublisherIEEE
ISSN (Electronic)2151-870X

Workshop

WorkshopIEEE Sensor Array and Multichannel Signal Processing Workshop
Abbreviated titleSAM
CountryBrazil
CityRio de Janeiro
Period10/07/201613/07/2016

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