The balance between supplied and demanded power is a crucial issue in the economic
dispatching of electricity energy. With the emergence of renewable sources and data-driven …

Access to electricity is a cornerstone for sustainable development and is pivotal to a
country's progress. The absence of electricity impedes development and elevates poverty …

This paper presents an innovative univariate Deep LSTM-based Stacked Autoencoder
(DLSTM-SAE) model for short-term load forecasting, equipped with a Multi-Stage Attention …

Mid-term electricity demand forecasting plays an important role in ensuring the operational
safety of the power system and the economic efficiency of grid companies. Most studies …

Energy consumption prediction has always remained a concern for researchers because of
the rapid growth of the human population and customers joining smart grids network for …

Reliable forecast of electricity demand is crucial to stability, supply, and management of
electricity grids. Short-term hourly and sub-hourly demand forecasts are difficult due to the …

Precise electric load forecasting at different time horizons is an essential aspect for electricity
producers and consumers who participate in energy markets in order to maximize their …

Due to the complicated features of process data in terms of high dimension, nonlinearity and
coupling, it tends to be a grand challenge to extract important features from complicated …

Medium Neural Networks (MNN), Whale Optimization Algorithm (WAO), and Support Vector
Machine (SVM) methods are frequently used in the literature for estimating electricity …

As the global population is growing at a high rate, so is the electricity demand also
increasing at a faster rate. This exerts pressure on electricity-generating plants and …