Nonetheless, it's a little late, people are starting to realize how bad fossil fuels are for the environment. Humans are turning to renewable energy in the hope of a cleaner and less pollutant environment. Thankfully, the sun is a reliable source of clean energy.
Solar energy is the radiant light and heat from the Sun and can be harnessed using a range of technologies. Predicting the attributes associated with solar radiation has become an important element in producing solar energy these days.
In this machine learning model, I will predict the different global radiation parameters such as Clearsky DHI, Clearsky DNI, and Clearsky GHI with the help of multivariate time series forecasting using Long Short Term Memory(LSTM) as Recurrent Neural Network(RNN) layers. Mean Absolute Error and Huber loss will be used to predict the accuracy of the model.