 The proposed framework is a powerful tool for accurately predicting future electrical load. It uses a combination of RNN layers and a dense layer to capture the underlying patterns and achieve a low-test error of 0.033. Compared to other models, it outperforms them by a large margin, demonstrating its effectiveness in capturing data patterns and trends. This article was authored by Christos Pavlatos, Evangelos Macros, Georgios Fotis, and others.