Prediction of Wind speed and Wind direction using Machine learning algorithm

Computer Engineering

A group of wind turbines in the same location used to produce electricity . Turbines can work efficiently with optimum wind speed , heavy wind cause damage to the turbine, In this project , the wind speed and direction for wind farm can be predicted to the efficient work of wind turbines. So, the output of the wind turbines will be having greater efficiency. Big data and Machine learning is outlined because the massive assortment of datasets that is advanced to method. Predicting wind speed and direction is one of the most important and critic tasks in a wind farm. Machine learning techniques are often used to predict the time series non-linear wind evolution. In this context, this project proposes a short term wind data prediction model based on Least Square Support Vector Machines (LSSVM) and Random forest algorithm in their regression mode, which have the advantage of being simple, fast and well adapted for the short term. This project also tries to prove how wind direction may influence power generation, and why it is important to predict it. A real time series data set contains the historical values of parameters like wind speed, wind direction which are used to predict the wind speed and direction . The predicted model will be evaluated with Mean Absolute , Mean Square Error value and both models will be compared for their performance.

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