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Machine Learning Approaches to forcast long term Direct Normal Irradiance

Md Mehedi Hasan, Kamlesh Sarkar


Nowadays, the adoption of solar energy into the power grid has increased, and it has become essential to accurate forecasts of direct normal irradiance from solar power for the effective operation and maintenance of power systems, ensuring their ability. Photovoltic panels track the sun to receive more DNI. DNI accounts for a large portion of the solar energy from PV. Forecasting DNI for the long term is a very cumbersome task. In this project, we will use a time series forecasting-based machine learning model to forecast a week ahead of DNI.

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