Expert system for analysis of electric power system harmonics

Shipp, D.D.; Vilcheck, W.; Swartz, Michael E.; Woodley, N.H.

doi:10.1109/2943.384625

Cited by 10 publications

(2 citation statements)

References 3 publications

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“…The AI based programs were used in numerous applications, such as pattern recognition for identification of defects in electric power apparatus and systems, loading forecasting, controls design and setting, disturbance diagnostics, decision support, harmonic analysis, etc. [9][10][11][12][13][14][15]. In this research we are developing the AI based software called SAGE (acronym for System Asset Group Examiner) [16], however this is a generic concept and can be implemented using different programing applications.…”

Section: B Artificial Inteligence Based Diagnosticsmentioning

confidence: 99%

Advanced transformer fleet monitoring system

Ziomek¹,

Vijayan²,

Sanders³

2014

2014 IEEE PES T&D Conference and Exposition

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The paper presents the concept of a transformer fleet monitoring and diagnostic system. The system collects data from the sensors installed on the transformers and sends the information through two data streams: to local SCADA and to the server with a diagnostic program. The diagnostic program is using the expert rules and artificial intelligence for data analysis and interpretation. The power utility is informed about the analysis results through warnings, alarms, and/or periodical reports.

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Section: B Artificial Inteligence Based Diagnosticsmentioning

confidence: 99%

Advanced transformer fleet monitoring system

Ziomek¹,

Vijayan²,

Sanders³

2014

2014 IEEE PES T&D Conference and Exposition

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“…The issue of automatic analysis of various PQ disturbances has been addressed in the form of the development of expert systems for PQ event identification or the classification of disturbances such as transients and voltage sags [3] - [9]. The expert system for analyzing power system harmonics focuses on symptoms associated with harmonics related problems and providing possible solutions [3], [10], [11]. This paper presents a new approach for automatic and intelligent identification of harmonic sources originating from nonlinear loads by classifying the different types of nonlinear loads that contribute harmonics to the supply system and then quantifying the harmonic distortion levels of each type of load.…”

Section: Introductionmentioning

confidence: 99%

A Rule Based Expert System for Identification of Harmonics Originating from Single Phase Nonlinear Loads

Mohamed¹,

Umeh

Hussain³

et al. 2006

International Journal of Emerging Electric Power Systems

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Presently, there is still a critical shortage of experts to interpret and diagnose problems associated with power system harmonics. Thus, the use of a rule based expert system is proposed for the identification of harmonic sources originating from various single phase nonlinear loads such as uninterruptible power supply, personal computer, fluorescent lamp with magnetic and electronic ballasts, PC monitor and oscilloscope. Identification of harmonics originating from single phase nonlinear loads is implemented by first analyzing the harmonic current waveforms using fractal and fast Fourier transform analyses so as to characterize the harmonic signatures of the different types of nonlinear loads. Then, a rule-based expert system is developed in which the system identifies and classifies the different types of nonlinear loads from the input current waveforms. The expert system with its user interface has been developed in MATLAB and it has been verified with real current measurements. The results obtained prove that the system enables accurate identification of nonlinear loads.

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