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

Perera, A. T D; Wickramasinghe, Udaranga; Nik, Vahid M. LU and Scartezzini, Jean-Louis (2017) In Energy Procedia 122. p.187-192
Abstract

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... (More)

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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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Distributed energy systems, electrical hub, multi-objective optimization, surrogate models
in
Energy Procedia
volume
122
pages
6 pages
publisher
Elsevier
external identifiers
  • scopus:85029902789
  • wos:000411783600032
ISSN
1876-6102
DOI
10.1016/j.egypro.2017.07.343
language
English
LU publication?
yes
id
eff67f9b-cb54-469c-a916-d16ad026be3a
date added to LUP
2017-10-10 08:31:33
date last changed
2018-01-16 13:22:16
@article{eff67f9b-cb54-469c-a916-d16ad026be3a,
  abstract     = {<p>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.</p>},
  author       = {Perera, A. T D and Wickramasinghe, Udaranga and Nik, Vahid M. and Scartezzini, Jean-Louis},
  issn         = {1876-6102},
  keyword      = {Distributed energy systems,electrical hub,multi-objective optimization,surrogate models},
  language     = {eng},
  pages        = {187--192},
  publisher    = {Elsevier},
  series       = {Energy Procedia},
  title        = {Optimum design of distributed energy hubs using hybrid surrogate models (HSM)},
  url          = {http://dx.doi.org/10.1016/j.egypro.2017.07.343},
  volume       = {122},
  year         = {2017},
}