Authors:
Hannes Eliasstam, Christos Ioakimidis, Konstantinos Genikomsakis

Abstract:

This paper presents the use of an artificial neural network for classification on a residence house that uses local air temperature and solar insulation predictions to identify patterns at the desired location, in order to obtain a stochastic distribution of the daily solar profile. This is a first 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. 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.



Proceedings: Proceedings of the 1st International Conference on Energy, Environment and Sustainability
Presented at:

1st International Conference on Energy, Environment and Sustainability (2012)


Year:

2012


Citation
Hannes Eliasstam, Christos Ioakimidis, Konstantinos Genikomsakis. (2012) "Electricity consumption and wind power forecasting on a smart house location" In Proceedings of the 1st International Conference on Energy, Environment and Sustainability.