Wind Turbine Power Output Forecasting Using Artificial Intelligence

Abstract

In this paper, wind turbine power output is predicted using Artificial intelligence (AI) techniques. The AI techniques used for predictions are Machine Learning (ML) algorithm and Deep Learning (DL). In ML, polynomial regression is used and Long Short Term Memory(LSTM) was used in DL. This forecasting is long-term forecasting that uses three years of data collected from NIWE (National Institute of Wind Energy) and the results can be used directly for the planning of energy management. Various environmental factors were taken into consideration for forecasting for better accuracy and results. The AI helps to predict the wind turbine output with high accuracy by considering the linear and non-linear types of dataset. This technique can also be used for the preventive maintenance of wind turbines and before the installation of wind power plants in an unfamiliar place to determine the corresponding wind potential.