The ability to predict short-term electric energy demand would provide several benefits, both
at the economic and environmental level. For example, it would allow for an efficient use of …

Smart buildings are equipped with sensors that allow monitoring a range of building systems
including heating and air conditioning, lighting and the general electric energy consumption …

In recent period, electricity need is increasing because of automatic control systems in
developing modern societies. So it is necessary to estimate the consumption and needs of a …

Energy demand forecasting plays a key role in solving the majority of problems connected
with determining the economic and energy development prospects. In view of high inertia …

Foundation models (FMs) currently dominate news headlines. They employ advanced deep
learning architectures to extract structural information autonomously from vast datasets …

In this paper, we extend a previously developed bottom-up energy demand model such that
the model can be used to determine changes in behavioral and energy usage patterns of a …

Correctly defining and grouping electrical feeders is of great importance for electrical system
operators. In this paper, we compare two different clustering techniques, K-means and …

This paper tackles the problem of integrating household energy prosumers in Smart Energy
Grids by analyzing a set of state-of-the-art energy forecasting techniques that allow …

The important, while mostly underestimated, step in the process of short-term load
forecasting–STLF is the selection of similar days. Similar days are identified based on …

This article presents a simulation based approach to provide a short-term energy demand
load curve forecast in a container terminal. While common methods for forecasting electricity …