Multi-objective optimization of fenestration design in residential spaces – The case of MKB Greenhouse, Malmö, Sweden : Abstract and oral presentation
(2017) BuildSim-Nordic 2017 Conference- Abstract
- This work presented and optimization scheme for daylighting, heating and thermal comfort objectives in a highly insulated apartment, while varying different geometrical aspects of external windows (number, shape, size, position). To satisfy all objectives simultaneously, a large number of design iterations was evaluated by the use of the SPEA2 genetic algorithm as it is implemented on the Octopus explicit components used in the visual programming environment of Grasshopper. The latter was used to connect the validated simulation engines of EnergyPlus, Daysim and Radiance with the generated designs governed by the optimization algorithm. Overall, it was shown that the use of genetic algorithms can accelerate the optimization process in... (More)
- This work presented and optimization scheme for daylighting, heating and thermal comfort objectives in a highly insulated apartment, while varying different geometrical aspects of external windows (number, shape, size, position). To satisfy all objectives simultaneously, a large number of design iterations was evaluated by the use of the SPEA2 genetic algorithm as it is implemented on the Octopus explicit components used in the visual programming environment of Grasshopper. The latter was used to connect the validated simulation engines of EnergyPlus, Daysim and Radiance with the generated designs governed by the optimization algorithm. Overall, it was shown that the use of genetic algorithms can accelerate the optimization process in building simulation scenarios, while evaluating a representative part of the solution space (total of solutions). The results indicate that the optimization process can lead to a good set of solutions for designers to work with in the initial design stage. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/dcc2c874-756f-4dfa-b123-c0b30d3fdb67
- author
- Bournas, Iason LU and Haav, Ludvig
- organization
- publishing date
- 2017
- type
- Contribution to conference
- publication status
- published
- subject
- keywords
- Building simulation, Daylight, Thermal comfort, Optimization algorithms
- conference name
- BuildSim-Nordic 2017 Conference
- conference location
- Lund, Sweden
- conference dates
- 2017-09-21 - 2017-09-22
- language
- English
- LU publication?
- yes
- id
- dcc2c874-756f-4dfa-b123-c0b30d3fdb67
- date added to LUP
- 2019-05-20 12:13:08
- date last changed
- 2019-05-28 09:20:32
@misc{dcc2c874-756f-4dfa-b123-c0b30d3fdb67,
abstract = {{This work presented and optimization scheme for daylighting, heating and thermal comfort objectives in a highly insulated apartment, while varying different geometrical aspects of external windows (number, shape, size, position). To satisfy all objectives simultaneously, a large number of design iterations was evaluated by the use of the SPEA2 genetic algorithm as it is implemented on the Octopus explicit components used in the visual programming environment of Grasshopper. The latter was used to connect the validated simulation engines of EnergyPlus, Daysim and Radiance with the generated designs governed by the optimization algorithm. Overall, it was shown that the use of genetic algorithms can accelerate the optimization process in building simulation scenarios, while evaluating a representative part of the solution space (total of solutions). The results indicate that the optimization process can lead to a good set of solutions for designers to work with in the initial design stage.}},
author = {{Bournas, Iason and Haav, Ludvig}},
keywords = {{Building simulation; Daylight; Thermal comfort; Optimization algorithms}},
language = {{eng}},
title = {{Multi-objective optimization of fenestration design in residential spaces – The case of MKB Greenhouse, Malmö, Sweden : Abstract and oral presentation}},
year = {{2017}},
}