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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
9
Número
3
Pàgina inicial
2276
Pàgina final
2283
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, ...
Citació
Kampouropoulos, K., Andrade, F., Sala, E., Garcia, A., Romeral, L. Multiobjective optimization of multi-carrier energy system using a combination of ANFIS and genetic algorithms. "IEEE Transactions on Smart Grid", 14 Setembre 2016, vol. 9, núm. 3, p. 2276-2283.
Paraules clau
Dynamic optimization, Energy hub, Energy optimization, Energy prediction, Manufacturing plants, Mixed-integer programming, Multicarrier systems, Multiobjective problem, Optimal control
Grup de recerca
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Centre de Recerca d'Electrònica de Potència UPC

Participants

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