2002•IEE Proceedings - Generation Transmission and DistributionRequires access

Quantifying electric power quality via fuzzy modelling and analytic hierarchy processing

S.A. Farghal, Mahmoud Kandil, Akram Ibrahim Elmitwally

Open publisher page 74 citations

Abstract

There is no one universal, even approximate, piece of data that entirely characterises, qualitatively or quantitatively, the status of the power quality at a utilisation point. This is due, on the one hand, to the great dimensionality of the parameters involved in the problem of power quality evaluation. On the other hand, the available data is featured with imprecision, uncertainty and vagueness, which renders it a very tedious and problematical task to assess the power quality level through one index. It is attempted to formulate one such comprehensive measure for the level of power quality at a loading point. Knowledge acquisition sessions, analytic hierarchy processing and fuzzy reasoning are the assistant tools employed to propose this new measure.

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What this paper is about

There is no one universal, even approximate, piece of data that entirely characterises, qualitatively or quantitatively, the status of the power quality at a utilisation point. This is due, on the one hand, to the great dimensionality of the parameters involved in the problem of power quality evaluation. On the other hand, the available data is featured with imprecision, uncertainty and vagueness, which renders it a very tedious and problematical task to assess the power quality level through one index. It is attempted to formulate one such comprehensive measure for the level of power quality at a loading point. Knowledge acquisition sessions, analytic hierarchy processing and fuzzy reasoning are the assistant tools employed to propose this new measure.

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OpenAlex reports 74 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

There is no one universal, even approximate, piece of data that entirely characterises, qualitatively or quantitatively, the status of the power quality at a utilisation point. This is due, on the one hand, to the great dimensionality of the parameters involved in the problem of power quality evaluation. On the other hand, the available data is featured with imprecision, uncertainty and vagueness, which renders it a very tedious and problematical task to assess the power quality level through one index. It is attempted to formulate one such comprehensive measure for the level of power quality at a loading point. Knowledge acquisition sessions, analytic hierarchy processing and fuzzy reasoning are the assistant tools employed to propose this new measure.

Key concepts: Vagueness, Measure (data warehouse), Fuzzy logic, Quality (philosophy), Computer science, Point (geometry), Hierarchy, Task (project management)

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