.png){kind=icon}
.png){kind=icon}
Return
Fuzzy-based adaptive digital power metering using a genetic algorithm
.png){kind=icon}
PRE
AI
DOI：10.1109/19.728815.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper describes an innovative, fuzzy-based, adaptive approach to the metering of power and mts voltage and current employing a genetic algorithm. The fuzzy-based adaptive metering engine adjusts the number of points per cycle to be processed and the location of these points. Adjustments are based on the optimal fuzzy rules constructed by a genetic algorithm to satisfy overall metering-error criteria under different operating environments while minimizing the number of points actually employed in the metering computation. This results in a reduction in the metering-computation effort, which frees up the processor for other tasks such as communication or power quality measurements. The fuzzy-based adaptive metering algorithm has been implemented on a microcontroller-based power metering system that employs a multitasking operating system which exploits the efficiencies achieved by the reduced metering rate. The fuzzy-based adaptive metering algorithm has been tested with a variety of actual and synthesized power-system waveforms and the experimental evaluations have demonstrated excellent accuracy in the metered power system quantities.
Keywords:
adaptive
fuzzy logic
genetic algorithm
meter
power
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.9
Papers:
1.9W
Citations:
5.8W
Organization
No organization information available