NDLI: An Artificial Intelligence Framework for On-Line Transient Stability Assessment of Power Systems

Content Provider	IEEE Xplore Digital Library
Author	Wehenkel, L. Van Cutsem, Th. Ribbens-Pavella, M.
Copyright Year	1981
Abstract	Transient stability assessment (TSA) of a power system pursues a twofold objective: first to appraise the system's capability to withstand major contingencies, and second to suggest remedial actions, i.e. means to enhance this capability, whenever needed. The first objective is the concern of analysis, the second is a matter of control. For the time being, the on-line TSA is still a totally open question. Indeed, none of the existing two broad classes of methods (the time domain and the direct methods) are able to meet the on-line requirements of the analysis aspects, nor are they in the least appropriate to tackle control aspects. The methodology we are introducing aims at solving the above stated on-line problem by making use of decision rules, preconstructed off-line. To this end, an inductive inference method is developed, able to provide decision rules in the form of binary trees expressing relationships between static, pre-fault operating conditions of a power system and its robustness to withstand assumed disturbances. This paper concentrates on this latter problem, which is the most difficult task, and also the kernel of the overall methodology. The proposed inductive inference (II) method pertains to a particular family of Machine Learning from examples. It derives from ID3 by Quinlan [1], tailored to our problem, where the examples are provided by numeric (load flow and stability) programs [2, 3]. According to the method, a decision tree (DT) is built on the basis of a preanalyzed learning set (LS), composed of states or operating points (OPs).
Starting Page	77
Ending Page	78
Page Count	2
File Size	492696
File Format	PDF
ISSN	02721724
Volume Number	9
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-05-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power system transients Power system stability Artificial intelligence Power system analysis computing Appraisal Time domain analysis Binary trees Power systems Robustness Kernel
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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