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 …

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 …

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 …

The electrical short term load forecasting has been emerged as one of the most essential
field of research for efficient and reliable operation of power system in last few decades. It …

Growth in electricity demand also gives a rise to the necessity of cheaper and safer electric
supply and forecasting electricity load plays a key role in this goal. In this study recurrent …

This empirical paper compares the accuracy of six univariate methods for short-term
electricity demand forecasting for lead times up to a day ahead. The very short lead times …

In recent years, a large amount of literature has evolved on the use of artificial neural
networks (ANNs) for electric load forecasting. ANNs are particularly appealing because of …

The paper addresses the problem of predicting hourly load demand using adaptive artificial
neural networks (ANNs). A particle swarm optimization (PSO) algorithm is employed to …

In this paper a new approach for short-term load prediction in buildings is shown. The
method is based on a special kind of artificial neural network (ANN), which feeds back a part …

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