Application of different methods for energy performance prediction of buildings: the influence of tool selection during the initial design phase

a influência de escolha da ferramenta durante a etapa inicial de projeto

Authors

DOI:

https://doi.org/10.46421/encac.v17i1.4063

Keywords:

Energy efficiency in buildings, Computer simulation, Metamodel, DEO platform

Abstract

The objective of this study is to address the impact of the choice of assessment tool for predicting the thermal load of buildings during the initial stages of the design process. To do so, reference models were defined as 5 archetypes developed based on the INI-C method with predicted evaluation for the climatic context of bioclimatic zones 1, 3, and 8. The assessment was carried out through three energy consumption estimation tools: computer simulation with EnergyPlus software, metamodel, and DEO platform. The results showed greater similarity between the first two methods and greater disparity in the results obtained using the DEO platform. In addition, it can be observed that there is a need for further research on the feasibility of a realistic simulation process in the early stages of design and that the prediction of building performance can vary depending on numerous factors, including the evaluation method and the representativeness of the input data used for this prediction.

Author Biographies

Thalita dos Santos Maciel, Universidade Federal de Santa Catarina

Master's in Architecture and Urbanism from the Federal University of Pelotas. Currently a Ph.D. student in Civil Engineering at the Federal University of Santa Catarina (Florianópolis - SC, Brazil).

Matheus Soares Geraldi, Universidade Federal de Santa Catarina

PhD in Civil Engineering from the Federal University of Santa Catarina. Research fellow at the Federal University of Santa Catarina (Florianópolis - SC, Brazil).

Ana Paula Melo, Universidade Federal de Santa Catarina

PhD in Civil Engineering from the Federal University of Santa Catarina. Professor in the Department of Civil Engineering at the Federal University of Santa Catarina (Florianópolis - SC, Brazil).

Roberto Lamberts, Universidade Federal de Santa Catarina

PhD in Civil Engineering from the University of Leeds. Professor at the Department of Civil Engineering at the Federal University of Santa Catarina (Florianópolis - SC, Brazil).

References

ABNT – ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 15220-3: Desempenho térmico de edificações – Parte 3: Zoneamento bioclimático brasileiro e diretrizes construtivas para habitações unifamiliares de interesse social. Rio de Janeiro, 2005a.

ASCIONE et al. A real industrial building: Modeling, calibration and Pareto optimization of energy retrofit. Journal of Building Engineering, v. 29, 2020.

BRASIL. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMETRO). Portaria nº 42, de 24 de fevereiro de 2021. Aprova a Instrução Normativa Inmetro para a Classificação de Eficiência Energética de Edificações Comerciais, de Serviços e Públicas (INI-C) que aperfeiçoa os Requisitos Técnicos da Qualidade para o Nível de Eficiência Energética de Edifícios Comerciais, de Serviços e Públicos (RTQ-C), especificando os critérios e os métodos para a classificação de edificações comerciais, de serviços e públicas quanto à sua eficiência energética. Diário Oficial da União, Brasília, DF, 09 mar. 2021. Seção 1, p. 55.

BRE, F.; ROMAN, N.; FACHINOTTI, V. D. An efficient metamodel-based method to carry out multi-objective building performance optimizations. Energy and Buildings, v. 206, p. 109576, 2020.

CB3E. CENTRO BRASILEIRO DE EFICIÊNCIA ENERGÉTICA EM EDIFICAÇÕES. Relatório interno: desenvolvimento do metamodelo v.3, 2022.

CBCS. CONSELHO BRASILEIRO DE CONSTRUÇÃO SUSTENTÁVEL. DEO: Plataforma de Cálculos de Benchmarking de Energia. Disponível em: https://plataformadeo.cbcs.org.br/ Acesso em: 13 abr. 2023.

COAKLEY, D.; RAFTERY, P.; KEANE, M. A review of methods to match building energy simulation models to measured data. Renewable and sustainable energy reviews, v.37, p.123-141, 2014.

FERRARA, M. et al. EDeSSOpt – Energy Demand and Supply Simultaneous Optimization for cost-optimized design: Application to a multi-family building. Applied Energy, v. 236, p. 1231-1248, 2019.

GBC BRASIL. GREEN BUILDING COUNCIL BRASIL. Referencial GBC Brasil Casa e Condomínio. São Paulo: GBC Brasil, 2019.

GOU, S. et al. Passive design optimization of newly-built residential buildings in Shanghai for improving indoor thermal comfort while reducing building energy demand. Energy and Buildings, v. 169, p. 484-506, 2018.

HAMDY, M.; NGUYEN, A.; HENSEN, J. L. M. A performance comparison of multiobjective optimization algorithms for solving nearly-zero-energy-building design problems. Energy and Buildings, v. 121, p. 57-71, 2016.

IPCC - Intergovernmental Panel on Climate Change, 2018. Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty.

MME. MINISTÉRIO DE MINAS E ENERGIA. Guia Prático para Eficiência Energética em Edifícios. Brasília: Secretaria de Planejamento e Desenvolvimento Energético, 2019.

OLU-AJAYI, R. et al. Building energy consumption prediction for residential buildings using deep learning and other machine learning techniques, Journal of Building Engineering, v. 45, 2022.

UNITED STATES DEPARTMENT OF ENERGY – DOE. EnergyPlus Documentation: Input Output References. US Department of Energy, 2022.

WBCSD. World Business Council for Sustainable Development. Transforming the Built Environment. Disponível em: https://www.wbcsd.org/Programs/Cities-and-Mobility/Sustainable-Cities/Transforming-the-Built-Environment. Acesso em: 19 abr. 2023.

ZALUSKI, P. R. da S.; DANTAS, M. J. P. Application of simulation softwares in engineering education: a report of successful international experiences in modeling and system simulation courses. Brazilian Applied Science Review, v. 2, n. 1, p. 170-181, 2018.

Published

2023-10-26

How to Cite

MACIEL, Thalita dos Santos; GERALDI, Matheus Soares; MELO, Ana Paula; LAMBERTS, Roberto. Application of different methods for energy performance prediction of buildings: the influence of tool selection during the initial design phase: a influência de escolha da ferramenta durante a etapa inicial de projeto. In: ENCONTRO NACIONAL DE CONFORTO NO AMBIENTE CONSTRUÍDO, 17., 2023. Anais [...]. [S. l.], 2023. p. 1–9. DOI: 10.46421/encac.v17i1.4063. Disponível em: https://eventos.antac.org.br/index.php/encac/article/view/4063. Acesso em: 21 nov. 2024.

Issue

Section

5. Eficiência Energética

Most read articles by the same author(s)

1 2 3 > >>