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  4. Optimum design of distributed energy hubs using hybrid surrogate models (HSM)
 
conference paper

Optimum design of distributed energy hubs using hybrid surrogate models (HSM)

Perera, A.T.D.  
•
Wickramasinghe, Pamuditha Udaranga  
•
Nik, Vahid M.  
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2017
Energy Procedia - CISBAT 2017 International Conference Future Buildings & Districts - Energy Efficiency from Nano to Urban Scale
CISBAT 2017 International Conference

The energy hub concept is gradually getting popular due to its capability to integrate renewable energy technologies into the energy grid with a minimum impact. Designing distributed energy hubs is a challenging task due to the coupling of optimum dispatch and energy system sizing problems. Operation of the system needs to be considered for 8760 time steps and energy system sizing optimization can take several days to complete. This time must be shortened in order to make it easier to optimize the multi-energy hubs connected to multi energy grids where there is a strong coupling among energy hubs and network. This study introduces a novel optimization algorithm, coupling an existing energy hub model with a hybrid surrogate model in order to reduce computational time in the optimization process.

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Type
conference paper
DOI
10.1016/j.egypro.2017.07.343
Web of Science ID

WOS:000411783600032

Author(s)
Perera, A.T.D.  
Wickramasinghe, Pamuditha Udaranga  
Nik, Vahid M.  
Scartezzini, Jean-Louis  
Date Issued

2017

Publisher

Elsevier

Publisher place

Amsterdam

Published in
Energy Procedia - CISBAT 2017 International Conference Future Buildings & Districts - Energy Efficiency from Nano to Urban Scale
Total of pages

6

Series title/Series vol.

Energy Procedia; 122

Start page

187

End page

192

Subjects

Distributed energy systems

•

electrical hub

•

surrogate models

•

multi-objective optimization

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LESO-PB  
Event nameEvent placeEvent date
CISBAT 2017 International Conference

Lausanne, Switzerland

6-8 September 2017

Available on Infoscience
November 3, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/141792
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