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05 July 2017
Poster (Scientific congresses and symposiums)
Characterising Industrial Sites' Flexibility with Reservoir Models
Cuvelier, Thibaut 
2017 • DS3 Data Science Summer School
 

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Keywords :
Industrial optimisation; Electrical flexibility; Data science
Abstract :
[en] Electro-intensive industrial sites are very dependent on electricity prices to remain competitive. Nevertheless, they can often tune their processes in order to decrease their electricity consumption during the most critical periods, for example by using decision support systems based on mathematical modelling of their processes. Our goal is to estimate the flexibility potential of a complete site, not to tune each process very precisely. To this end, we propose a generic paradigm to help conceiving such models: reservoirs are the basic building block, which allows for great expressiveness while being close to the physics. More specifically, we do not need very precise models for our purposes, but ones that can be efficiently included in optimisation models. Our first results show that the obtained reservoir models can give sufficiently good approximations for metallurgical and other processes.
Research center :
Montefiore Institute - Montefiore Institute of Electrical Engineering and Computer Science - ULiège
Disciplines :
Mathematics
Author, co-author :
Cuvelier, Thibaut ;  Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation : Optimisation discrète
Language :
English
Title :
Characterising Industrial Sites' Flexibility with Reservoir Models
Alternative titles :
[fr] Caractérisation de la flexibilités de sites industriels par modèles de réservoirs
Publication date :
August 2017
Number of pages :
A0
Event name :
DS3 Data Science Summer School
Event organizer :
École polytechnique
Event place :
Paris, France
Event date :
from 28-08-2017 to 01-09-2017
Audience :
International

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