TY - JOUR
T1 - Compressive System Identification for Multiple Line Outage Detection in Smart Grids
AU - Babakmehr, Mohammad
AU - Harirchi, Farnaz
AU - Al-Durra, Ahmed
AU - Muyeen, S. M.
AU - Simoes, Marcelo Godoy
N1 - Funding Information:
Manuscript received July 9, 2018; revised November 25, 2018 and February 18, 2019; accepted May 10, 2019. Date of publication June 4, 2019; date of current version August 14, 2019. Paper 2018-PSEC-0692.R2, presented at the 2018 IEEE Industry Applications Society Annual Meeting, Portland, OR, USA, Sep. 23–27, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Power Systems Engineering Committee of the IEEE Industry Applications Society. This work was supported in part by CSM-PI Grant 470039. This paper was presented in part at the IAS Annual Meeting, Portland, OR, USA, Sep. 23–27, 2018 [41]. (Corresponding author: Mohammad Babakmehr.) M. Babakmehr, F. Harirchi, and M. G. Simões are with the Department of Electrical Engineering, Colorado School of Mines, Golden, CO 80401 USA (e-mail: [email protected]; [email protected]; [email protected]).
Publisher Copyright:
© 1972-2012 IEEE.
PY - 2019/9/1
Y1 - 2019/9/1
N2 - Real-time power line outage detection (POD) and localization is an important monitoring task for the modern smart grid. Reliable monitoring of power lines status plays a critical role in the system-wide blackout prevention. In this paper, the main aim is to address the multiple POD problems by exploiting the compressive system identification - a time-efficient approach in a complex network analysis. A typical power network is considered as a single graph, and the mathematical formulation of the POD problem is initialized using the dc power-flow model and graph theory concepts. Next, a sparse representation-based formulation for this problem (POD-SRP) is reported and further improved and generalized in case of multiple large-scale outages. Practical and technical challenges associated with this sparse recovery problem are partially addressed by developing new SRP solvers. Furthermore, a new sparse-based mathematical formulation for POD is introduced and termed as 'Binary-POD-SRP,' which specifically deals with two particular issues, namely, the high coherence and the signal dynamic outrange. Finally, the identification performance of the proposed framework is evaluated by a variety of case studies, which are modeled using IEEE standard test-beds. We specifically discuss how the inherent challenges within large-scale multiple-outages can be solved by applying these new techniques and formulations.
AB - Real-time power line outage detection (POD) and localization is an important monitoring task for the modern smart grid. Reliable monitoring of power lines status plays a critical role in the system-wide blackout prevention. In this paper, the main aim is to address the multiple POD problems by exploiting the compressive system identification - a time-efficient approach in a complex network analysis. A typical power network is considered as a single graph, and the mathematical formulation of the POD problem is initialized using the dc power-flow model and graph theory concepts. Next, a sparse representation-based formulation for this problem (POD-SRP) is reported and further improved and generalized in case of multiple large-scale outages. Practical and technical challenges associated with this sparse recovery problem are partially addressed by developing new SRP solvers. Furthermore, a new sparse-based mathematical formulation for POD is introduced and termed as 'Binary-POD-SRP,' which specifically deals with two particular issues, namely, the high coherence and the signal dynamic outrange. Finally, the identification performance of the proposed framework is evaluated by a variety of case studies, which are modeled using IEEE standard test-beds. We specifically discuss how the inherent challenges within large-scale multiple-outages can be solved by applying these new techniques and formulations.
KW - Compressive system identification (CSI) sparse recovery
KW - power outage identification
KW - power system monitoring
KW - smart grid (SG)
UR - http://www.scopus.com/inward/record.url?scp=85071302898&partnerID=8YFLogxK
U2 - 10.1109/TIA.2019.2921260
DO - 10.1109/TIA.2019.2921260
M3 - Article
AN - SCOPUS:85071302898
SN - 0093-9994
VL - 55
SP - 4462
EP - 4473
JO - IEEE Transactions on Industry Applications
JF - IEEE Transactions on Industry Applications
IS - 5
M1 - 8731707
ER -