NDLI: Comprehensive evaluation of power quality based on meaningful classification

Content Provider	IEEE Xplore Digital Library
Author	Ding Zejun Zhu Yongqiang Chen Caihong
Copyright Year	2010
Description	Author affiliation: School of Electrical and Electronic Engineering (North China Electric Power University), Ministry of Education Beijing 102206, China (Ding Zejun; Zhu Yongqiang; Chen Caihong)
Abstract	In a liberalized electricity market, it is not surprising that different customers need different power quality levels with different price. So how to achieve the synthetic grading evaluation of power quality becomes a concerned problem. In this paper, the idea of classified evaluation of power quality is emphasized, and the major differences between the continuous and event-based power quality problems both in the characteristics and time scales are analyzed. In addition, least squares support vector machine (LSSVM) theory is applied to the comprehensive evaluation of continuous power quality. Meanwhile, power supply reliability index is introduced to evaluate the overall quality level of the event-based power quality. On this basis, subjective weighting method is used to achieve the comprehensive evaluation of two types of power quality problems. Comprehensive evaluation of power quality based on meaningful classification not only highlights the two types of power quality problems, but also achieves the overall level of power quality.
Starting Page	1
Ending Page	4
File Size	672731
Page Count	4
File Format	PDF
ISBN	9781424480807
e-ISBN	9781424480814
DOI	10.1109/CRIS.2010.5617506
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Economics Support vector machines Voltage fluctuations Biological system modeling Power quality comprehensive evaluation power quality Meaningful classification Reliability least squares support vector machine power supply reliability
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

Identifying Power Quality Disturbances in Real Time Using Incremental Wavelet Decomposition and Least Square Support Vector Machine

Improved Multivariate Calibration Based on Least Square Support Vector Machines

Power Load Forecasting with Least Squares Support Vector Machines and Chaos Theory

Investigation on the effectiveness of classifying the voltage sag using support vector machine

Research on Power Plant Superheated Steam Temperature Based on Least Squares Support Vector Machines

Power quality problem classification using support vector machine

Study of fault diagnosis model based on multi-class wavelet support vector machines

Power Load Forecasting with Least Squares Support Vector Machines and Chaos Theory

Classification of power quality disturbances using wavelet and fuzzy support vector machines

Comprehensive evaluation of power quality based on meaningful classification

Similar Documents

Identifying Power Quality Disturbances in Real Time Using Incremental Wavelet Decomposition and Least Square Support Vector Machine

Improved Multivariate Calibration Based on Least Square Support Vector Machines

Power Load Forecasting with Least Squares Support Vector Machines and Chaos Theory

Investigation on the effectiveness of classifying the voltage sag using support vector machine

Research on Power Plant Superheated Steam Temperature Based on Least Squares Support Vector Machines

Power quality problem classification using support vector machine

Study of fault diagnosis model based on multi-class wavelet support vector machines

Power Load Forecasting with Least Squares Support Vector Machines and Chaos Theory

Classification of power quality disturbances using wavelet and fuzzy support vector machines

Comprehensive evaluation of power quality based on meaningful classification