Solar energy prediction


New Member
I am prediction one-day-ahead solar energy output using 30 days historical data. The data sets are hourly, so the prediction is done hourly from sunrise to sunset.
I have doe the prediction using sliding window technique, When I am predicting 01/06, I am using 30 days historical data (from 02/05 – 31/05 ) for the training dataset that will be used to build the model, the training dataset include weather variables (global horizontal irradiance, direct normal irradiance, temperature and humidity) as input to the model and actual solar energy output (not the predicted) as dependent variable. I do this for 360 days.
I got comment: So many lagged dependent variables will raise multicollinearity issue, in linear regression model. Did you check it?

What is the answer for this.

Hope some one can help me on this.