NDLI: Transient stability assessment on China Southern Power Grid system with an improved pattern discovery-based method

Content Provider	IEEE Xplore Digital Library
Author	Yan Xu Lin Guan Zhao Yang Dong Kit Po Wong
Copyright Year	2010
Description	Author affiliation: Electric Power College, South China University of Technology, Guangzhou, 510640, China (Yan Xu; Lin Guan) \|\| Electrical Engineering Department, The Hong Kong Polytechnic University, Kowloon, Hong Kong (Zhao Yang Dong; Kit Po Wong)
Abstract	Intelligent systems (IS) have been widely adopted to facilitate very fast transient stability assessment (TSA) to prevent blackouts. More recently, a TSA model based on pattern discovery (PD) method has been proposed and demonstrated on several IEEE standard test systems. It has exhibited many attractive features, including high accuracy, ability to provide classification rules and system weak-points information, etc. In this paper, the PD-based TSA method is further improved by use an alternative feature selection method which is very computational efficient and tend to result in better performance. The improved model is examined on China Southern Power Grid dynamic equivalent system and compared with state-of-art IS methods. The simulation results show that the improved model has been significantly improved in modelling efficiency and its accuracy is competitive with state-of-the-art IS techniques.
Starting Page	1
Ending Page	6
File Size	681252
Page Count	6
File Format	PDF
ISBN	9781424459384
e-ISBN	9781424459407
DOI	10.1109/POWERCON.2010.5666045
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines China Southern Power Grid transient stability assessment pattern discovery feature selection
Content Type	Text
Resource Type	Article

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

Power System Transient Stability Assessment Based on Adaboost and Support Vector Machines

Multi-support vector machine power system transient stability assessment based on relief algorithm

A data mining technique based on pattern discovery and k-nearest neighbor classifier for transient stability assessment

Power system transient stability assessment based on geometric features of disturbed trajectory and DTW

Fast Transient Stability Assessment Based on Data Mining for Large-Scale Power System

A New Method of Transient Stability Assessment in Power Systems Using LS-SVM

Support Vector Regression Machine with Enhanced Feature Selection for Transient Stability Evaluation

Transient stability assessment of a large actual power system using least squares support vector machine with enhanced feature selection

Feature Selection Method Based on Overlapped Probability for Transient Voltage Stability Assessment

Transient stability assessment on China Southern Power Grid system with an improved pattern discovery-based method

Similar Documents

Power System Transient Stability Assessment Based on Adaboost and Support Vector Machines

Multi-support vector machine power system transient stability assessment based on relief algorithm

A data mining technique based on pattern discovery and k-nearest neighbor classifier for transient stability assessment

Power system transient stability assessment based on geometric features of disturbed trajectory and DTW

Fast Transient Stability Assessment Based on Data Mining for Large-Scale Power System

A New Method of Transient Stability Assessment in Power Systems Using LS-SVM

Support Vector Regression Machine with Enhanced Feature Selection for Transient Stability Evaluation

Transient stability assessment of a large actual power system using least squares support vector machine with enhanced feature selection

Feature Selection Method Based on Overlapped Probability for Transient Voltage Stability Assessment

Transient stability assessment on China Southern Power Grid system with an improved pattern discovery-based method