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.
(Less)
- author
- Perera, A. T D
; Wickramasinghe, Udaranga
; Nik, Vahid M.
LU
and Scartezzini, Jean-Louis
- organization
- publishing date
- 2017
- 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
-
- wos:000411783600032
- scopus:85029902789
- 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
- 2024-05-12 22:30:25
@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}},
keywords = {{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}},
doi = {{10.1016/j.egypro.2017.07.343}},
volume = {{122}},
year = {{2017}},
}