Parametric Approach for Multi-Objective Optimization for Daylighting and Energy Consumption in Early Stage Design of Office Tower in New Administrative Capital City of Egypt
Article Sidebar
Submitted
February 7, 2019
Published
February 7, 2019
Keywords:
-
Parametric Optimization, Genetic Algorithm, Daylighting, Energy Simulation, Early Stage Design
Abstract
In the last few years, great improvements have been achieved in building optimization methods. Mustapha Sadeghipour Roudasri and others found new tools ” Ladybug, Honeybee and Butterfly” which could gather many simulation engines and visualization tools ” Energyplus, OpenStudio, Radiance, Daysim, CFD, OpenFOAM, etc ”. Consequently, These simulation engines will integrate with parametric modeling in Grasshopper and multiobjective optimization through Octopus plug-in to form an early stage parametric optimization framework in one canvas. This paper aims at finding the suitable plane shape and building configurations for multi-objective optimization to the daylighting levels and energy consumption of office tower building in the new administrative capital city in Egypt through parametric based optimization method. One of the most commonly used plan shapes of these types of buildings was studied. This shape and many building configurations ”WWR, window material, wall material and shading devices” were parametrically modeled. These Parameters will form many tradeoffs which will be simulated and optimized by the previous framework. Spatial Daylight Autonomy ”SDA300/50%” is examined to optimize Daylighting while Energy Use Intensity ” EUI” is used for energy consumption optimization. Multi-Objective Optimization was performed by genetic algorithms via Octopus plug-in. The near optimum design for plan shape and building configuration to balance between daylighting and energy consumption is achieved and will be a reference model for office tower buildings in this zone in Egypt which is under rapid development. The framework used in this study will guide designers to find effective solutions for early-stage design of office building in one canvas without any conflict between several engines and scripts.
Full text article
Generated from XML file
References
1. Baumgartner, U., Baumgartner, U., Magele, C., Magele, C., Renhart, W., & Renhart, W. (2004). Pareto
Optimality and Particle Swarm Optimization. IEEE TRANSACTIONS ON MAGNETICS, 40(2), 1172–1175. https://doi.org/10.1109/TMAG.2004.825430
2. El Daly, H. M. T. (2014). Automated fenestration allocation as complying with LEED rating system. Alexandria Engineering Journal, 53(4), 883–890. https://doi.org/10.1016/j.aej.2014.09.011
3. Elghazi, Y., Wagdy, A., Mohamed, S., & Hassan, A. (2014). DAYLIGHTING DRIVEN DESIGN : OPTIMIZING KALEIDOCYCLE FACADE FOR HOT ARID CLIMATE. In Fifth German-Austrian IBPSA Conference RWTH Aachen University (pp. 314–321). Aachen.
4. Konis, K., Gamas, A., & Kensek, K. (2016). Passive performance and building form: An optimization
framework for early-stage design support. Solar Energy, 125, 161–179. https://doi.org/10.1016/j.solener.2015.12.020
5. Lin, S. H. E., & Gerber, D. J. (2014). Designing-in performance: A framework for evolutionary energy
performance feedback in early stage design. Automation in Construction, 38, 59–73. https://doi.org/10.1016/j.autcon.2013.10.007
6. Musleh, M. A. M. (2012). Parametric Design Optimization in Sustainable Urban Design : In Hot Climate.
7. Nguyen, A.-T., Reiter, S., & Rigo, P. (2014). A review of simulation-based optimization methods applied to building performance analysis. Applied Energy, 113, 1043–1058. https://doi.org/10.1016/j.apenergy.2013.08.061
8. Østergard, T., Jensen, R. L., & Maagaard, S. E. (2016). Building simulations supporting decision making in early design - A review. Renewable and Sustainable Energy Reviews, 61, 187–201. https://doi.org/10.1016/j.rser.2016.03.045
9. Qingsong, M., & Fukuda, H. (2016). Parametric Office Building for Daylight and Energy Analysis in the
Early Design Stages. Procedia - Social and Behavioral Sciences, 216, 818–828. https://doi.org/10.1016/j.sbspro.2015.12.079
10. Roudsari, M. S., Pak, M., Smith, A., & Gordon Gill Architecture. (2013). Ladybug: a Parametric Environmental Plugin for Grasshopper To Help Designers Create an Environmentally-Conscious Design. 13th Conference of International Building Performance Simulation Association, 3129–3135. Retrieved from http://www.ibpsa.org/proceedings/bs2013/p 2499.pdf
11. SIS. (2017). New Administrative Capital. Retrieved August 20, 2017, from http://www.sis.gov.eg/section/352/5238?lang=en-us
12. Suyoto, W., Indraprastha, A., & Purbo, H. W. (2015). Parametric Approach as a Tool for Decision-making
in Planning and Design Process. Case study: Office Tower in Kebayoran Lama. Procedia - Social and
Behavioral Sciences, 184(August 2014), 328–337. https://doi.org/10.1016/j.sbspro.2015.05.098
13. Turrin, M., Von Buelow, P., Kilian, A., & Stouffs, R. (2012). Performative skins for passive climatic comfort: A parametric design process. Automation in Construction, 22(May), 36–50. https://doi.org/10.1016/j.autcon.2011.08.001
14. USGBC, L. (2013). US Green Building Council. Retrieved August 28, 2017, from https://www.usgbc.org/leed
15. Vierlinger, R., Zimmel, C., & Schneider, G. (2013). Octopus, Version 0.1. Retrieved May 1, 2013, from www.grasshopper3d.com/group/octopu
16. Wagdy, A., & Fathy, F. (2015). A parametric approach for achieving optimum daylighting performance
through solar screens in desert climates. Journal of Building Engineering, 3, 155–170. https://doi.org/10.1016/j.jobe.2015.07.007
Optimality and Particle Swarm Optimization. IEEE TRANSACTIONS ON MAGNETICS, 40(2), 1172–1175. https://doi.org/10.1109/TMAG.2004.825430
2. El Daly, H. M. T. (2014). Automated fenestration allocation as complying with LEED rating system. Alexandria Engineering Journal, 53(4), 883–890. https://doi.org/10.1016/j.aej.2014.09.011
3. Elghazi, Y., Wagdy, A., Mohamed, S., & Hassan, A. (2014). DAYLIGHTING DRIVEN DESIGN : OPTIMIZING KALEIDOCYCLE FACADE FOR HOT ARID CLIMATE. In Fifth German-Austrian IBPSA Conference RWTH Aachen University (pp. 314–321). Aachen.
4. Konis, K., Gamas, A., & Kensek, K. (2016). Passive performance and building form: An optimization
framework for early-stage design support. Solar Energy, 125, 161–179. https://doi.org/10.1016/j.solener.2015.12.020
5. Lin, S. H. E., & Gerber, D. J. (2014). Designing-in performance: A framework for evolutionary energy
performance feedback in early stage design. Automation in Construction, 38, 59–73. https://doi.org/10.1016/j.autcon.2013.10.007
6. Musleh, M. A. M. (2012). Parametric Design Optimization in Sustainable Urban Design : In Hot Climate.
7. Nguyen, A.-T., Reiter, S., & Rigo, P. (2014). A review of simulation-based optimization methods applied to building performance analysis. Applied Energy, 113, 1043–1058. https://doi.org/10.1016/j.apenergy.2013.08.061
8. Østergard, T., Jensen, R. L., & Maagaard, S. E. (2016). Building simulations supporting decision making in early design - A review. Renewable and Sustainable Energy Reviews, 61, 187–201. https://doi.org/10.1016/j.rser.2016.03.045
9. Qingsong, M., & Fukuda, H. (2016). Parametric Office Building for Daylight and Energy Analysis in the
Early Design Stages. Procedia - Social and Behavioral Sciences, 216, 818–828. https://doi.org/10.1016/j.sbspro.2015.12.079
10. Roudsari, M. S., Pak, M., Smith, A., & Gordon Gill Architecture. (2013). Ladybug: a Parametric Environmental Plugin for Grasshopper To Help Designers Create an Environmentally-Conscious Design. 13th Conference of International Building Performance Simulation Association, 3129–3135. Retrieved from http://www.ibpsa.org/proceedings/bs2013/p 2499.pdf
11. SIS. (2017). New Administrative Capital. Retrieved August 20, 2017, from http://www.sis.gov.eg/section/352/5238?lang=en-us
12. Suyoto, W., Indraprastha, A., & Purbo, H. W. (2015). Parametric Approach as a Tool for Decision-making
in Planning and Design Process. Case study: Office Tower in Kebayoran Lama. Procedia - Social and
Behavioral Sciences, 184(August 2014), 328–337. https://doi.org/10.1016/j.sbspro.2015.05.098
13. Turrin, M., Von Buelow, P., Kilian, A., & Stouffs, R. (2012). Performative skins for passive climatic comfort: A parametric design process. Automation in Construction, 22(May), 36–50. https://doi.org/10.1016/j.autcon.2011.08.001
14. USGBC, L. (2013). US Green Building Council. Retrieved August 28, 2017, from https://www.usgbc.org/leed
15. Vierlinger, R., Zimmel, C., & Schneider, G. (2013). Octopus, Version 0.1. Retrieved May 1, 2013, from www.grasshopper3d.com/group/octopu
16. Wagdy, A., & Fathy, F. (2015). A parametric approach for achieving optimum daylighting performance
through solar screens in desert climates. Journal of Building Engineering, 3, 155–170. https://doi.org/10.1016/j.jobe.2015.07.007
Authors
Toutou, A. M. Y. (2019). Parametric Approach for Multi-Objective Optimization for Daylighting and Energy Consumption in Early Stage Design of Office Tower in New Administrative Capital City of Egypt. The Academic Research Community Publication, 3(1), 1–13. https://doi.org/10.21625/archive.v3i1.426
- The Author shall grant to the Publisher and its agents the nonexclusive perpetual right and license to publish, archive, and make accessible the Work in whole or in part in all forms of media now or hereafter known under a Creative Commons Attribution 4.0 License or its equivalent, which, for the avoidance of doubt, allows others to copy, distribute, and transmit the Work under the following conditions:
- Attribution: other users must attribute the Work in the manner specified by the author as indicated on the journal Web site;
With the understanding that the above condition can be waived with permission from the Author and that where the Work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license.
- The Author is able to enter into separate, additional contractual arrangements for the nonexclusive distribution of the journal's published version of the Work (e.g., post it to an institutional repository or publish it in a book), as long as there is provided in the document an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post online a pre-publication manuscript (but not the Publisher's final formatted PDF version of the Work) in institutional repositories or on their Websites prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (see The Effect of Open Access). Any such posting made before acceptance and publication of the Work shall be updated upon publication to include a reference to the Publisher-assigned DOI (Digital Object Identifier) and a link to the online abstract for the final published Work in the Journal.
- Upon Publisher's request, the Author agrees to furnish promptly to Publisher, at the Author's own expense, written evidence of the permissions, licenses, and consents for use of third-party material included within the Work, except as determined by Publisher to be covered by the principles of Fair Use.
- The Author represents and warrants that:
- The Work is the Author's original work;
- The Author has not transferred, and will not transfer, exclusive rights in the Work to any third party;
- The Work is not pending review or under consideration by another publisher;
- The Work has not previously been published;
- The Work contains no misrepresentation or infringement of the Work or property of other authors or third parties; and
- The Work contains no libel, invasion of privacy, or other unlawful matter.
- The Author agrees to indemnify and hold Publisher harmless from Author's breach of the representations and warranties contained in Paragraph 7 above, as well as any claim or proceeding relating to Publisher's use and publication of any content contained in the Work, including third-party content.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Article Details
