NDLI: Coherency approach by hybrid PSO, K-Means clustering method in power system

Content Provider	IEEE Xplore Digital Library
Author	Davodi, M. Modares, H.-R. Reihani, E. Davodi, M. Sarikhani, A.
Copyright Year	2008
Description	Author affiliation: Fac. of Electr. & Robotic Eng., Shahrood Univ. of Technol., Shahrood (Davodi, M.; Modares, H.-R.; Reihani, E.; Davodi, M.; Sarikhani, A.)
Abstract	This paper presents a new method for recognition the identical behaviors of synchronous generators for particular fault location on power system. In this method, a hybrid algorithm combining particle swarm optimization (PSO) algorithm with k-means algorithm, also referred to PSO-KM algorithm is proposed to find the specified number of clusters in electric network. Each cluster represents a number of generators such that these generators named coherent generators. Clustering process is based on similarity of time domain data in transient stability studies. The new algorithm is evaluated on 39-Bus New England test system. Results show that the proposed algorithm has much potential in finding coherent generators.
Starting Page	1203
Ending Page	1207
File Size	118327
Page Count	5
File Format	PDF
ISBN	9781424424047
DOI	10.1109/PECON.2008.4762659
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-01
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hybrid power systems Clustering methods Clustering algorithms Power system faults Synchronous generators Fault location Particle swarm optimization Power system transients Stability System testing Coherent generators Coherency Particle Swarm optimization (PSO) K-Means Clustering
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

Online coherency analysis of synchronous generators in a power system

Combining K-means and particle swarm optimization for dynamic data clustering problems

Based on Hybrid PSO-K-Means Clustering 1

A hybrid particle swarm optimization-genetic algorithm for optimal location of svc devices in power system planning

Anomaly Intrusion Detection Method Based on K-Means Clustering Algorithm with Particle Swarm Optimization

Particle Swarm Optimization for Fuzzy c-Means Clustering

A Clustering K-means Algorithm Based on Improved PSO Algorithm

Energy optimization in wireless sensor networks using a hybrid K-means PSO clustering algorithm

Energy optimization in wireless sensor networks using a hybrid K-means PSO clustering algorithm

Coherency approach by hybrid PSO, K-Means clustering method in power system

Similar Documents

Online coherency analysis of synchronous generators in a power system

Combining K-means and particle swarm optimization for dynamic data clustering problems

Based on Hybrid PSO-K-Means Clustering 1

A hybrid particle swarm optimization-genetic algorithm for optimal location of svc devices in power system planning

Anomaly Intrusion Detection Method Based on K-Means Clustering Algorithm with Particle Swarm Optimization

Particle Swarm Optimization for Fuzzy c-Means Clustering

A Clustering K-means Algorithm Based on Improved PSO Algorithm

Energy optimization in wireless sensor networks using a hybrid K-means PSO clustering algorithm

Energy optimization in wireless sensor networks using a hybrid K-means PSO clustering algorithm

Coherency approach by hybrid PSO, K-Means clustering method in power system