This paper focuses on feature selection problems that arise in renewable energy
applications. Feature selection is an important problem in machine learning, both in …

The intermittent nature of wind energy raised multiple challenges to the power systems and
is the biggest challenge to declare wind energy a reliable source. One solution to overcome …

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 …

Abstract Machine learning algorithms (MLAs) are applied to predict wind speed data for
Osorio wind farm that is located in the south of Brazil, near the Osorio city. Forecasting wind …

Buildings are the major source of energy consumption in urban areas. Accurate modeling
and forecasting of the building energy use intensity (EUI) in the urban scale have many …

Smart grid is a platform that enables the participants of electricity market to adjust their
bidding strategies based on Demand-Side Management (DSM) models. Responsiveness of …

Efficient and effective city planning in improving the energy performance of residential
buildings requires a clear understanding of the influential features. Previous studies on …

This paper presents a new method based on the Smart Energy System concept to link the
water infrastructure and the energy system of an island. The principal aim of this study is to …

Obtaining high-precision wind speed prediction results is very beneficial to the utilization of
wind energy and the operation of the power system. The purpose of this study is to develop …

Wind speed estimation at ungauged locations is one of the preliminary steps for wind
resource assessment. With the availability of high-resolution Digital Elevation Models (DEM) …