Load forecasting has become one of the major areas of research in electrical engineering,
and most traditional forecasting models and artificial intelligence techniques have been tried …

Energy is vital for sustainable development of any nation–be it social, economic or
environment. In the past decade energy consumption has increased exponentially globally …

Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …

Recently there has been a significant proliferation in the use of forecasting techniques,
mainly due to the increased availability and power of computation systems and, in particular …

Part of the second edition of The Electric Power Engineering Handbook, Power System
Stability and Control offers conveniently focused and detailed information covering all …

This paper presents the development of an artificial neural network (ANN) based short-term
load forecasting model for the Energy Control Center of the Greek Public Power Corporation …

While most of the existing artificial neural networks (ANN) models for building energy
prediction are static in nature, this paper evaluates the performance of adaptive ANN models …

This paper presents a novel approach to short-time load forecasting by the application of
nonparametric regression. The method is derived from a load model in the form of a …

This paper presents an artificial neural network (ANN) approach for annual electricity
consumption in high energy consumption industrial sectors. Chemicals, basic metals and …

This paper describes the third generation of an hourly short-term load forecasting system
known as ANNSTLF (Artificial Neural Network Short-Term Load Forecaster). This forecaster …