PREDICTION OF POWER GENERATION IN WIND TURBINES

PREDICTION OF POWER GENERATION IN WIND TURBINES

Varikallu Sambasiva Rao¹, Paritala Sai Teja², Neelam vamsi³, Panguluri Venkata Siva Rama Krishna⁴

Department of ECE at R.V.R & J.C College of Engineering

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Abstract - Wind energy is a promising alternative source of clean and renewable energy that can help mitigate climate change. Accurate prediction of power generation in wind turbines is critical for the effective integration of wind energy into the power grid. In this study, we compare the performance of two popular machine learning algorithms, linear regression and random forest, for power generation prediction in wind turbines. We use wind speed and direction as input variables and power generation as the output variable. Our results show that random forest outperforms linear regression in terms of prediction accuracy and robustness.

Key Words:  Power Generation, wind turbines, Random forest, power prediction, wind power, machine learning