A new method for classification and characterization of voltage sags Academic Article

abstract

• This paper presents new software developments related to sag classification and characterization. A new fuzzy rule based algorithm for classifying the types of voltage sags is proposed. The voltage sags are categorized into three types, i.e. sags due to the faults, large motor starting, or due to interaction between motor operation and faults. Three distinctive features of sag waveforms are defined and extracted first. Then a fuzzy logic based inference engine utilizing these features as inputs is implemented for decision making. Also presented are the characterization methods and suggested monitoring parameters for each of the three types of sags. Finally the application of the proposed characterization approaches for the equipment sensitivity study is illustrated. The results of case studies are reported. The presented approach has been implemented in MATLAB. 2001 Elsevier Science B.V.

authors

• Kezunovic, Mladen

published proceedings

• ELECTRIC POWER SYSTEMS RESEARCH

author list (cited authors)

• Kezunovic, M., & Liao, Y.

citation count

• 26

complete list of authors

• Kezunovic, M||Liao, Y

publication date

• May 2001

publisher

• Elsevier  Publisher

keywords

• Fuzzy Logic
• Parameter Estimation
• Pattern Classification
• Power Quality
• Voltage Sag

Digital Object Identifier (DOI)

• 10.1016/S0378-7796(01)00104-3

start page

• 27

end page

• 35

volume

• 58

issue

• 1

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fs0378-7796%2801%2900104-3