TY - JOUR
T1 - A probability model for grid faults using incomplete information
AU - Al-Kanj, Lina
AU - Bouzaiene-Ayari, Belgacem
AU - Powell, Warren Buckler
N1 - Funding Information:
Manuscript received February 26, 2015; revised May 19, 2015; accepted June 12, 2015. Date of publication July 29, 2015; date of current version February 16, 2017. This work was supported in part by the National Science Foundation under Contract ECCS-1127975, and in part by the SAP Initiative for Energy Systems Research. Paper no. TSG-00234-2015.
Publisher Copyright:
© 2015 IEEE.
PY - 2017/3
Y1 - 2017/3
N2 - Utilities face the challenge of responding to power outages due to storms and ice damage, but most power grids are not equipped with sensors to pinpoint the precise location of fault causing the outage. Instead, utilities have to depend primarily on phone calls (trouble calls) from customers who have lost power. This paper presents an information model of the grid in the presence of outages; the developed model is used to estimate the probability of power line faults causing the outages. However, the computational complexity of the problem grows exponentially with the number of power lines in the grid. Thus, several methods are proposed for handling the combinatorial growth of events and the behavior is demonstrated using the data of a real-power grid. Performance results show that power line fault detection can be achieved with high accuracy, even with a very low percentage of customers calling to report an outage.
AB - Utilities face the challenge of responding to power outages due to storms and ice damage, but most power grids are not equipped with sensors to pinpoint the precise location of fault causing the outage. Instead, utilities have to depend primarily on phone calls (trouble calls) from customers who have lost power. This paper presents an information model of the grid in the presence of outages; the developed model is used to estimate the probability of power line faults causing the outages. However, the computational complexity of the problem grows exponentially with the number of power lines in the grid. Thus, several methods are proposed for handling the combinatorial growth of events and the behavior is demonstrated using the data of a real-power grid. Performance results show that power line fault detection can be achieved with high accuracy, even with a very low percentage of customers calling to report an outage.
KW - Distribution system fault
KW - Grid fault
KW - Ower line fault
KW - Power outage
KW - Probability model
KW - Probability of fault
KW - Trouble call
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U2 - 10.1109/TSG.2015.2447275
DO - 10.1109/TSG.2015.2447275
M3 - Article
AN - SCOPUS:85027704874
VL - 8
SP - 956
EP - 968
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
SN - 1949-3053
IS - 2
ER -