Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5476544 | Energy | 2017 | 7 Pages |
Abstract
One-day and nine-day ahead prediction performance of the proposed methodology show that intelligent integration of linear regression, time series and computational resources into a unique approach may provide accurate predictions for short-term electric loads.
Related Topics
Physical Sciences and Engineering
Energy
Energy (General)
Authors
Agostino Tarsitano, Ilaria L. Amerise,