1 January 2013

A decentralized approach to generalized power system state estimation

Kekatos, V., Vlachos, E., Ampeliotis, D., Giannakis, G., Berberidis, K.
IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
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Abstract

Distributed generation and the urge for a more effi- cient grid operation will increase the frequency of network topol- ogy reconfigurations in tomorrow’s power grids. High-throughput synchrophasor and intelligent electronic device readings provide unprecedented instrumentation capabilities for generalized state estimation (GSE), which deals with identifying the power system state jointly with its network topology. This task is critically challenged by the complexity scale of a grid interconnection, especially under the detailed GSE model. Upon modifying the original GSE cost by block-sparsity promoting regularizers, a decentralized solver with enhanced circuit breaker verification capabilities is developed. Built on the alternating direction method of multipliers, the novel method maintains compatibility with existing solvers and requires minimum information exchanges across the control centers of neighboring power grids. Numer- ical tests on an extended IEEE 14-bus model corroborate the effectiveness of the novel approach. I. I NTRODUCTION Network topology cognition and state estimation are two basic modules in power system monitoring [1].

Type 1
Publication IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
DOI 10.1109/camsap.2013.6714011
Date January 2013
Research 6G UAVs

Key Contributions

  • Development of a decentralized generalized state estimation (GSE) approach that verifies circuit breaker statuses.
  • Utilization of block-sparsity promoting regularizers to enhance breaker status verification capabilities.
  • Formulation of the GSE problem as a distributed optimization problem amenable to the alternating direction method of multipliers (ADMM).
  • Design of a communication-efficient framework that maintains compatibility with existing power system solvers.

NMSE performance comparison between the centralized and decentralized GSE approaches.
NMSE performance comparison between the centralized and decentralized GSE approaches.
This figure demonstrates that the decentralized algorithm achieves estimation accuracy comparable to the centralized solution within a few iterations.

Breaker status verification error rate as a function of the number of suspected breakers.
Breaker status verification error rate as a function of the number of suspected breakers.
The results show that the proposed decentralized `2-regularized GSE significantly reduces the number of incorrect breaker status identifications compared to the ordinary GSE approach.

Research 6G UAVs