Very short term irradiance forecasting using the lasso

摘要

We find an application of the lasso (least absolute shrinkage and selection operator) in sub-5-min solar irradiance forecasting using a monitoring network. Lasso is a variable shrinkage and selection method for linear regression. In addition to the sum of squares error minimization, it considers the sum of l-norms of the regression coefficients as penalty. This bias variance trade-off very often leads to better predictions.