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Multiobjective optimization of multi-carrier energy system using a combination of ANFIS and genetic algorithms

Autor
Kampouropoulos, K.; Andrade, F.; Sala, E.; Garcia, A.; Romeral, L.
Tipus d'activitat
Article en revista
Revista
IEEE Transactions on Smart Grid
Data de publicació
2016-09-14
Volum
PP
Número
99
Pàgina inicial
1
Pàgina final
9
DOI
https://doi.org/10.1109/TSG.2016.2609740 Obrir en finestra nova
Projecte finançador
Euroenergest- Increase of Automative Factory competitivences trough an integral energy management system
Repositori
http://hdl.handle.net/2117/101849 Obrir en finestra nova
URL
http://ieeexplore.ieee.org/document/7567591/ Obrir en finestra nova
Resum
This paper presents a novel method for the energy optimization of multi-carrier energy systems. The presented method combines an adaptive neuro-fuzzy inference system, to model and forecast the power demand of a plant, and a genetic algorithm to optimize its energy flow taking into account the dynamics of the system and the equipment’s thermal inertias. The objective of the optimization algorithm is to satisfy the total power demand of the plant and to minimize a set of optimization criteria, ...
Paraules clau
Energy Optimization, Multicarrier Systems, Dynamic Optimization, Mixed-integer Programming, Multiobjective Problem, Energy Hub, Energy Prediction, Optimal Control, Manufacturing Plants
Grup de recerca
MCIA - Centre MCIA Innovation Electronics
PERC-UPC - Centre de Recerca d'Electrònica de Potència UPC

Participants