DocumentCode
3077257
Title
Detection and identification of Potentially Disturbing Loads and consumers: Methodology and case study
Author
Coelho, J. ; Neto, E. A C Aranha ; Thomae, S. ; Pereira, J.C. ; Bettiol, A.L. ; Coelho, G.M. ; Zimath, S.L. ; Braz, R. ; Homma, R.Z.
Author_Institution
Fed. Univ. of Santa Catarina, Florianópolis, Brazil
fYear
2010
fDate
8-10 Nov. 2010
Firstpage
568
Lastpage
574
Abstract
This work shows an algorithm developed from a knowledge base, which consists of four lists inter-relatable and multiple criteria methodology. From an expert system, it is possible to calculate the index C2P that can be used in an “a priori” analysis to determine Potentially Disturbing Loads or, using a set of electrical data measurements, perform an “a posteriori” analysis in order to assign a comparative index for Potentially Disturbing Consumers. Besides the knowledge base implemented, these analysis also include the susceptibility curves to voltage variations ITIC and SEMI and proposed indices of Brazilian (PRODIST) and global (IEEE and IEC) references. The methodology was applied, as a case study, in an industrial consumer in plastics domain of Southern Brazil.
Keywords
distribution networks; expert systems; power supply quality; power system harmonics; power system transients; electrical data measurements; expert systems; industrial consumer; industrial power systems harmonics; industrial power systems transients; potentially disturbing loads; power distribution; power quality; susceptibility curves; voltage variations; Expert systems; Frequency measurement; Indexes; Plastics; Power quality; Voltage fluctuations; Expert systems; Industrial power systems harmonics; Industrial power systems transients; Power distribution and Power quality;
fLanguage
English
Publisher
ieee
Conference_Titel
Transmission and Distribution Conference and Exposition: Latin America (T&D-LA), 2010 IEEE/PES
Conference_Location
Sao Paulo
Print_ISBN
978-1-4577-0488-8
Type
conf
DOI
10.1109/TDC-LA.2010.5762939
Filename
5762939
Link To Document