IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i7p1863-d158374.html
   My bibliography  Save this article

Multi-Objective Optimisation of the Energy Performance of Lightweight Constructions Combining Evolutionary Algorithms and Life Cycle Cost

Author

Listed:
  • Rui Oliveira

    (RISCO-Department of Civil Engineering University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal)

  • António Figueiredo

    (RISCO-Department of Civil Engineering University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal)

  • Romeu Vicente

    (RISCO-Department of Civil Engineering University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal)

  • Ricardo M. S. F. Almeida

    (Polytechnic Institute of Viseu, Department of Civil Engineering, Campus Politécnico, 3504-510 Viseu, Portugal
    CONSTRUCT-LFC, Faculty of Engineering (FEUP), University of Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal)

Abstract

This paper discusses the thermal and energy performance of a detached lightweight building. The building was monitored with hygrothermal sensors to collect data for building energy model calibration. The calibration was performed using a dynamic simulation through EnergyPlus ® (EP) (Version 8.5, United States Department of Energy (DOE), Washington, DC, USA) with a hybrid evolutionary algorithm to minimise the root mean square error of the differences between the predicted and real recorded data. The results attained reveal a good agreement between predicted and real data with a goodness of fit below the limits imposed by the guidelines. Then, the evolutionary algorithm was used to meet the compliance criteria defined by the Passive House standard for different regions in Portugal’s mainland using different approaches in the overheating evaluation. The multi-objective optimisation was developed to study the interaction between annual heating demand and overheating rate objectives to assess their trade-offs, tracing the Pareto front solution for different climate regions throughout the whole of Portugal. However, the overheating issue is present, and numerous best solutions from multi-objective optimisation were determined, hindering the selection of a single best option. Hence, the life cycle cost of the Pareto solutions was determined, using the life cycle cost as the final criterion to single out the optimal solution or a combination of parameters.

Suggested Citation

  • Rui Oliveira & António Figueiredo & Romeu Vicente & Ricardo M. S. F. Almeida, 2018. "Multi-Objective Optimisation of the Energy Performance of Lightweight Constructions Combining Evolutionary Algorithms and Life Cycle Cost," Energies, MDPI, vol. 11(7), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1863-:d:158374
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/7/1863/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/7/1863/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shorrock, LD & Dunster, JE, 1997. "The physically-based model BREHOMES and its use in deriving scenarios for the energy use and carbon dioxide emissions of the UK housing stock," Energy Policy, Elsevier, vol. 25(12), pages 1027-1037, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mengqi Zhao & Xiaoling Wang & Jia Yu & Lei Bi & Yao Xiao & Jun Zhang, 2020. "Optimization of Construction Duration and Schedule Robustness Based on Hybrid Grey Wolf Optimizer with Sine Cosine Algorithm," Energies, MDPI, vol. 13(1), pages 1-17, January.
    2. Dalbem, Renata & Grala da Cunha, Eduardo & Vicente, Romeu & Figueiredo, Antonio & Oliveira, Rui & Silva, Antonio César Silveira Baptista da, 2019. "Optimisation of a social housing for south of Brazil: From basic performance standard to passive house concept," Energy, Elsevier, vol. 167(C), pages 1278-1296.
    3. António Figueiredo & Filipe Rebelo & Rui Alexandre Castanho & Rui Oliveira & Sérgio Lousada & Romeu Vicente & Victor M. Ferreira, 2020. "Implementation and Challenges of the Passive House Concept in Portugal: Lessons Learnt from Successful Experience," Sustainability, MDPI, vol. 12(21), pages 1-20, October.
    4. Krzysztof Grygierek & Joanna Ferdyn-Grygierek & Anna Gumińska & Łukasz Baran & Magdalena Barwa & Kamila Czerw & Paulina Gowik & Klaudia Makselan & Klaudia Potyka & Agnes Psikuta, 2020. "Energy and Environmental Analysis of Single-Family Houses Located in Poland," Energies, MDPI, vol. 13(11), pages 1-25, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Scott Kelly, 2011. "Do homes that are more energy efficient consume less energy?: A structural equation model for England's residential sector," Working Papers EPRG 1117, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    2. Pereira, Iraci Miranda & Assis, Eleonora Sad de, 2013. "Urban energy consumption mapping for energy management," Energy Policy, Elsevier, vol. 59(C), pages 257-269.
    3. Triana, Maria Andrea & Lamberts, Roberto & Sassi, Paola, 2015. "Characterisation of representative building typologies for social housing projects in Brazil and its energy performance," Energy Policy, Elsevier, vol. 87(C), pages 524-541.
    4. Natarajan, Sukumar & Levermore, Geoffrey J., 2007. "Predicting future UK housing stock and carbon emissions," Energy Policy, Elsevier, vol. 35(11), pages 5719-5727, November.
    5. Younghoon Kwak & Jeonga Kang & Sun-Hye Mun & Young-Sun Jeong & Jung-Ho Huh, 2020. "Development and Application of a Flexible Modeling Approach to Reference Buildings for Energy Analysis," Energies, MDPI, vol. 13(21), pages 1-22, November.
    6. Walker, Sara Louise & Hope, Alex & Bentley, Edward, 2014. "Modelling steady state performance of a local electricity distribution system under UK 2050 carbon pathway scenarios," Energy, Elsevier, vol. 78(C), pages 604-621.
    7. McCallum, Peter & Jenkins, David P. & Peacock, Andrew D. & Patidar, Sandhya & Andoni, Merlinda & Flynn, David & Robu, Valentin, 2019. "A multi-sectoral approach to modelling community energy demand of the built environment," Energy Policy, Elsevier, vol. 132(C), pages 865-875.
    8. Lee, Timothy & Yao, Runming & Coker, Phil, 2014. "An analysis of UK policies for domestic energy reduction using an agent based tool," Energy Policy, Elsevier, vol. 66(C), pages 267-279.
    9. Chitnis, Mona & Sorrell, Steve & Druckman, Angela & Firth, Steven K. & Jackson, Tim, 2013. "Turning lights into flights: Estimating direct and indirect rebound effects for UK households," Energy Policy, Elsevier, vol. 55(C), pages 234-250.
    10. Lee, Timothy & Yao, Runming, 2013. "Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis," Energy Policy, Elsevier, vol. 52(C), pages 363-372.
    11. Natarajan, Sukumar & Levermore, Geoffrey J., 2007. "Domestic futures--Which way to a low-carbon housing stock?," Energy Policy, Elsevier, vol. 35(11), pages 5728-5736, November.
    12. Gordon Mitchell & Anthony Hargreaves & Anil Namdeo & Marcial Echenique, 2011. "Land Use, Transport, and Carbon Futures: The Impact of Spatial Form Strategies in Three UK Urban Regions," Environment and Planning A, , vol. 43(9), pages 2143-2163, September.
    13. Dodds, Paul E., 2014. "Integrating housing stock and energy system models as a strategy to improve heat decarbonisation assessments," Applied Energy, Elsevier, vol. 132(C), pages 358-369.
    14. Theofano Fotiou & Alessia de Vita & Pantelis Capros, 2019. "Economic-Engineering Modelling of the Buildings Sector to Study the Transition towards Deep Decarbonisation in the EU," Energies, MDPI, vol. 12(14), pages 1-28, July.
    15. Ren, Zhengen & Paevere, Phillip & McNamara, Cheryl, 2012. "A local-community-level, physically-based model of end-use energy consumption by Australian housing stock," Energy Policy, Elsevier, vol. 49(C), pages 586-596.
    16. Kannan, Ramachandran & Strachan, Neil, 2009. "Modelling the UK residential energy sector under long-term decarbonisation scenarios: Comparison between energy systems and sectoral modelling approaches," Applied Energy, Elsevier, vol. 86(4), pages 416-428, April.
    17. Buso, Tiziana & Corgnati, Stefano Paolo, 2017. "A customized modelling approach for multi-functional buildings – Application to an Italian Reference Hotel," Applied Energy, Elsevier, vol. 190(C), pages 1302-1315.
    18. Shorrock, L. D., 2000. "Identifying the individual components of United Kingdom domestic sector carbon emission changes between 1990 and 2000," Energy Policy, Elsevier, vol. 28(3), pages 193-200, March.
    19. Keirstead, James, 2006. "Evaluating the applicability of integrated domestic energy consumption frameworks in the UK," Energy Policy, Elsevier, vol. 34(17), pages 3065-3077, November.
    20. Hargreaves, Anthony & Cheng, Vicky & Deshmukh, Sandip & Leach, Matthew & Steemers, Koen, 2017. "Forecasting how residential urban form affects the regional carbon savings and costs of retrofitting and decentralized energy supply," Applied Energy, Elsevier, vol. 186(P3), pages 549-561.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1863-:d:158374. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.