Privacy preserving decentralized power system state estimation with phasor measurement units

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

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

3 Sitaatiot (Scopus)

Abstrakti

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.

AlkuperäiskieliEnglanti
OtsikkoProceedings of the 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016
Sivumäärä5
Vuosikerta2016-September
ISBN (elektroninen)9781509021031
DOI - pysyväislinkit
TilaJulkaistu - 15 syyskuuta 2016
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaIEEE Sensor Array and Multichannel Signal Processing Workshop - Rio de Janeiro, Brasilia
Kesto: 10 heinäkuuta 201613 heinäkuuta 2016
Konferenssinumero: 9

Julkaisusarja

NimiIEEE Workshop on Sensor Array and Multichannel Signal Processing
KustantajaIEEE
ISSN (elektroninen)2151-870X

Workshop

WorkshopIEEE Sensor Array and Multichannel Signal Processing Workshop
LyhennettäSAM
MaaBrasilia
KaupunkiRio de Janeiro
Ajanjakso10/07/201613/07/2016

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