Estimate and Analysis the Availability of Generator in Electric Power Plant Using ANN

Authors

  • Asmaa J. Awad Department of Automated Manufacturing Engineering/Al-Khwarizmi College of Engineering/ University of Baghdad, Al-Jadriayh /Baghdad/Iraq
  • Ahmed A. Ahmed Department of Mechanical Engineering/ University of Baghdad/ Al-Jadriayh/Baghdad/ Iraq
  • Osamah F. Abdulateef Department of Automated Manufacturing Engineering/Al-Khwarizmi College of Engineering/ University of Baghdad, Al-Jadriayh /Baghdad/Iraq

DOI:

https://doi.org/10.22153/kej.2022.04.001

Abstract

The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching of Feed-Forward, Back-Propagation. Operating data from the years 2015–2017 were used to calculate the availability by traditional method (Weibull distribution) and train the ANNs, while data from the year 2018 of operation were used to verify the model. The study implies that the ANN may be able to forecast the availability of the generator with a correlation coefficient (R) 0.99874 and a Mean Square Error (MSE) 5.6937E-06 between the availability predicted by ANN and Weibull distribution output.

 

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References

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Published

2022-06-16

How to Cite

Awad, A. J., Ahmed, A. A. ., & Abdulateef , O. F. . (2022). Estimate and Analysis the Availability of Generator in Electric Power Plant Using ANN . Al-Khwarizmi Engineering Journal (Alkej), 18(2), 1–12. https://doi.org/10.22153/kej.2022.04.001