Detect and categorize errors in smart grids using voltage and current phases

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SABERI MOHAMMAD; Taghipoor Behzad

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Paper Information

Journal: DECISIONS AND OPERATIONS RESEARCH Year:2018 | Volume:3 | Issue:1 Page(s): 82-98

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Title

Detect and categorize errors in smart grids using voltage and current phases

Author(s)

SABERI MOHAMMAD | Taghipoor Behzad | Issue Writer Certificate

Keywords

Error detection and classification

Intelligent network

Phasor measurement unit

Fourier transform analysis

Nerve-fuzzy inference system

Support Vector Machine

Abstract

This paper presents a methodology for detecting and classifying the errors occurring on smart power transmission lines. In the proposed method, the voltage and current phases are estimated by the Phasor measurement unit (PMU) installed in the generator bus, and then the equivalent voltage and current angles are obtained. These angles are analyzed by fast fourier transform (FFT) and used to detect of transmission line errors. Detection of the transmission line error is performed using the Nerve-fuzzy inference system methodology, and the diagnostic error classification is performed using Support Vector Machine (SVM). Validation of the proposed method for the IEEE 14 system is also tested in the MATLAB software environment.

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APA: Copy

SABERI, MOHAMMAD, & Taghipoor, Behzad. (2018). Detect and categorize errors in smart grids using voltage and current phases. DECISIONS AND OPERATIONS RESEARCH, 3(1 ), 82-98. SID. https://sid.ir/paper/268880/en

Vancouver: Copy

SABERI MOHAMMAD, Taghipoor Behzad. Detect and categorize errors in smart grids using voltage and current phases. DECISIONS AND OPERATIONS RESEARCH[Internet]. 2018;3(1 ):82-98. Available from: https://sid.ir/paper/268880/en

IEEE: Copy

MOHAMMAD SABERI, and Behzad Taghipoor, “Detect and categorize errors in smart grids using voltage and current phases,” DECISIONS AND OPERATIONS RESEARCH, vol. 3, no. 1 , pp. 82–98, 2018, [Online]. Available: https://sid.ir/paper/268880/en

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