Electrical utilities depend on short-term demand forecasting to proactively adjust production
and distribution in anticipation of major variations. This systematic review analyzes 240 …

It is important to understand and forecast a typical or a particularly household daily
consumption in order to design and size suitable renewable energy systems and energy …

In this paper, we have proposed a methodology for energy consumption prediction in
residential buildings. The proposed method consists of four different layers, namely data …

The recent technological developments monitoring the electricity use of small customers
provides with a whole new view to develop electricity distribution systems, customer-specific …

Precise Short term load forecasting (STLF) plays a significant role in the management of
power system of countries and regions on the grounds of insufficient electric energy for …

The goal of this paper is to describe a forecasting model for the hourly electricity load in the
area covered by an electric utility located in the southeast of Brazil. A different model is …

Short-term load forecasting is crucial for the operations planning of an electrical grid.
Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize …

In this work several univariate approaches for short-term load forecasting based on neural
networks are proposed and compared. They include: multilayer perceptron, radial basis …

Daily peak electricity demand forecasting in South Africa using a seasonal autoregressive
integrated moving average (SARIMA) model, a SARIMA model with generalized …

This work presents a neural network based on the ART architecture (adaptive resonance
theory), named fuzzy ART&ARTMAP neural network, applied to the electric load-forecasting …