Wind Turbine Operation Information System

Authors

  • J Mahalakshmi Student, Department of Computer Science and Engineering, Grace College of Engineering, Thoothukudi, Tamil Nadu, India
  • K.M. Annammal Assistant Professor, Department of Computer Science and Engineering, Grace College of Engineering, Thoothukudi, Tamil Nadu, India

DOI:

https://doi.org/10.37591/tmd.v10i3.7761

Keywords:

Wind turbine, machine learning algorithm, smart projects, Renewable energy, SCADA

Abstract

The ability of wind energy to produce energy steadily and consistently makes it an important and necessary energy source. However wind energy has faced many challenges, such as discontinuation of wind farm equipment, early investment costs and therefore finding wind energy efficiency areas. The main aim of this project is to determine the energy efficiency of wind turbines, and it will also help to make suggestions to reduce the maintenance costs of wind turbines. In this study, data analysis of turbine generators was performed daily using machine learning and deep learning algorithms to obtain wind speed data for the day. We present an approach that leverages deep learning and machine learning algorithms to reliably estimate variable costs. Therefore the performance of machine learning and deep learning algorithms is reviewed. For long term forecasts, these algorithms can be used in conjunction with electricity generation costs that historical correlations with wind speed data.

References

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Published

2024-03-27

Issue

Vol. 10 No. 3 (2023)

Section

Articles

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