Wind Energy Analysis and-Forecast using Deep Learning (LSTM)

A Deep Learning model that predict forecast the power generated by wind turbine in a Wind Energy Power Plant using LSTM (Long Short Term Memory) i.e modified recurrent neural network.

VIsualization and Output

1. Visualization

a. Correlation using Heatmap

It is easily understood from the graph that the Wind Direction hat no impact on the Power generated by Wind Turbine.

b. Wind Direction Vs Wind Speed Plot using Windrose Library

c. KDE Plot on data

Fit and plot a univariate or bivariate kernel density estimate.

d. Date/Time VS Wind Power

2. Output Visualization

The model shows 96%(approx.) Accuracy on the forecasting which is quite great can be inreased by inreasing the Epochs.