NDLI: Benchmark of machine learning algorithms on capturing future distribution network anomalies

Content Provider	IET Digital Library
Author	Mohammadpourfard, Mostafa Weng, Yang Tajdinian, Mohsen
Abstract	The conventional distribution network is undergoing structural changes and becoming an active grid due to the advent of smart grid technologies encompassing distributed energy resources (DERs), aggregated demand response and electric vehicles (EVs). This establishes a need for state estimation-based tools and real-time monitoring of the distribution grid to correctly apply active controls. Although such new tools may be vulnerable to cyber-attacks, cyber-security of distribution grid has not received enough attention. As smart distribution grid intensively relies on communication infrastructures, the authors assume in this study that an attacker can compromise the communication and successfully conduct attacks against crucial functions of the distribution management system, making the distribution system prone to instability boundaries for collapses. They formulate the attack detection problem in the distribution grid as a statistical learning problem and demonstrate a comprehensive benchmark of statistical learning methods on various IEEE distribution test systems. The proposed learning algorithms are tested using various attack scenarios which include distinct features of modern distribution grid such as integration of DERs and EVs. Furthermore, the interaction between transmission and distribution systems and its effect on the attack detection problem are investigated. Simulation results show attack detection is more challenging in the distribution grid.
Starting Page	1441
Ending Page	1455
Page Count	15
ISSN	17518687
Volume Number	13
e-ISSN	17518695
Issue Number	Issue 8, Apr (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/13/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.6801
Journal	IET Generation, Transmission & Distribution
Publisher Date	2019-02-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Active Grid Attack Attack Detection Problem Attacker Conventional Distribution Network Data Security Distributed Power Generation Distribution Management System Distribution Network Distribution System Electric Vehicle Future Distribution Network Anomalies IEEE Distribution Test System Knowledge Engineering Technique Learning in AI Modern Distribution Grid Optimisation Technique Security of Data Smart Distribution Grid Smart Grid Technology Smart Power Grid Transmission Transportation
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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