NDLI: Decision tree-based classifiers for root-cause detection of equipment-related distribution power system outages

Content Provider	IET Digital Library
Author	Dehbozorgi, Mohammad Reza Rastegar, Mohammad Dabbaghjamanesh, Morteza
Abstract	Recently, power system reliability has been challenged due to the increment of electrical demand. When an outage occurs, locating the outage may take a long time because of the distribution system's radial structure and the presence of various elements. To decrease the outage detection time, this study proposes to classify the equipment-related outage causes to diagnose the faulty equipment at the time of outage occurrence. To this end, available historical outage, load and weather data sets are integrated, and various features are defined. Then, binary classifiers are developed to classify each equipment's failures against others'. To enhance classifiers' performance, this study also proposes to use cost function and ensemble models. The results of applying proposed classifiers show the accuracy of the proposed method and improvements in outcomes.
Starting Page	5809
Ending Page	5815
Page Count	7
ISSN	17518687
Volume Number	14
e-ISSN	17518695
Issue Number	Issue 24, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/14/24
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2020.0570
Journal	IET Generation, Transmission & Distribution
Publisher Date	2020-07-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Binary Classifier Combinatorial Mathematics Decision Tree Distribution System Electrical Demand Equipment-related Distribution Power System Outages Equipment-related Outage Faulty Equipment Knowledge Engineering Technique Outage Detection Time Outage Occurrence Pattern Classification Power System Fault Power System Reliability Reliability Root-cause Detection Statistics Tree-based Classifier Weather Data Sets
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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