Deep Learning to estimate building energy demands in the smart grid context

Energy and Stochastics Seminar

We have the pleasure to welcome Elena Mocanu (TU Eindhoven) at DTU on 16 January 2015. She will give a seminar to share with us some of her latest research work in collaboration with Madeleine Gibescu (also at TU Eindhoven) and others. The seminar will take place in 101, room s04, at 11am.

Abstract

Prediction of temporal energy consumption plays an essential role in the current transition to future energy systems. Quantification of uncertainty introduced with the advent of new renewable energy sources only strengthens the role of accurate predictions methods, in order to be included later in more complex decision making process able to control and plan the energy consumption. At the same time these methods should be easily expandable to higher levels of aggregation such as neighborhoods and the power distribution grid. Many approaches have been proposed aiming at accurate and robust prediction of the energy consumption. For the purpose of this presentation two different Deep Learning methods are detailed. Additionally these complex neural networks methods are compared with a much popular method, namely Artificial Neural Network, able to faithfully reproduce the energy consumption of buildings under various time horizons.

Time

Fri 16 Jan 15
11:00 - 12:00

Where

DTU Lyngby Campus
Anker Engelunds Vej 1
Bygning 101, room s04
2800 Kgs. Lyngby


https://www.cee.elektro.dtu.dk/calendar/arrangement?id=96861a59-01fa-4a24-afc6-c29fe4668261
12 DECEMBER 2024