Appropriate feature (variable) selection is crucial for accurate forecasting. In this paper we
consider the task of forecasting the future electricity load from a time series of previous …

Selection of input features plays an important role in developing models for short-term load
forecasting (STLF). Previous studies along this line of research have focused pre-dominantly …

Abstract Short-Term Electricity Load Forecasting (STLF) has become one of the hot topics of
energy research as it plays a crucial role in electricity markets and power systems. Few …

Scientific community is currently doing a great effort of research in the area of Smart Grids
because energy production, distribution, and consumption play a critical role in the …

In this paper, we present a new approach for very short term electricity load demand
forecasting. In particular, we apply support vector regression to predict the load demand …

Electricity load forecasting is a key task in the planning and operation of power systems and
electricity markets, and its importance increases with the advent of smart grids. In this paper …

In this study, we present an empirical comparison of statistical models and machine learning
models for daily electricity price forecasting in the New Zealand electricity market. We …

Motivated by the increasing integration among electricity markets, in this paper we propose
two different methods to incorporate market integration in electricity price forecasting and to …

This article draws from research on ensembles in computational intelligence to propose
structural combinations of forecasts, which are point forecast combinations that are based on …

Short-term electricity load forecasting has become increasingly important due to the
privatization and deregulation in the energy market. This study proposes a probabilistic …