Authors:
Hannes Eliasstam, Konstantinos Genikomsakis, Christos Ioakimidis

Abstract:

This 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.



Proceedings: Proceedings of the International Conference on Renewable Energies and Power Quality
Presented at:

ICREPQ (2013)


Year:

2013


Citation
Hannes Eliasstam, Konstantinos Genikomsakis, Christos Ioakimidis. (2013) "Wind Power and Electricity Consumption Forecasting on a Smart House Location" In Proceedings of the International Conference on Renewable Energies and Power Quality.