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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
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    References listed on IDEAS

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    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.
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    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.

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