Eliasstam, H.Genikomsakis, Konstantinos N.Ioakimidis, Christos S.2026-09-262026-09-262013-03Eliasstam, Genikomsakis, & Ioakimidis. (2013). Wind power and electricity consumption forecasting on a smart house location. Renewable Energy and Power Quality Journal, 1(11), 655-659. https://doi.org/10.24084/REPQJ11.40410.24084/REPQJ11.404https://hdl.handle.net/20.500.14454/6698This paper presents the use of an artificial neural network for classification on a residence house that uses wind and electricity consumption predictions to identify patterns at the desired location, in order to obtain a stochastic distribution of the daily wind and electricity profile. This is a step on the further creation of a short-term operation model that allows determining the technical and economic impact of stationary/mobile batteries of electric vehicles in presence of microrenewables along with the electricity consumption. This short-term operation model will be in the day-ahead perfect market operation (unit commitment) where specific changes are made to consider stationary and mobile operation.engArtificial neural networksElectricityForecastingSmart homesWind energyjournal article2026-09-262172-038X