SolarForecast: Feature-based Model Redistribution for Solar Power Forecasting.

Abstract

"The document outlines the development of ""SolarForecast,"" a novel system for solar power forecasting using feature-based model redistribution. It aims to address the challenge of creating a flexible and generalizable solar forecasting system. This research proposes a system that utilizes a meta-learning model to combine the forecasts of an ensembling through weighted averaging and redistribution. This works by using the meta-learner on the extracted time series features of a dataset where the meta-learner will assign weights to the base models, which are used for forecasting, in the ensemble and redistribute them if below a threshold. This approach outperforms previous approaches utilizing model averaging on the tested dataset in the metrics such as sMAPE, MAE, RMSE and OWA. "