Development of a Cost-Comfort Optimisation Indicator (CCOI) for Early-Stage Building Envelope Design Evaluation
DOI:
https://doi.org/10.25034/ijcua.2026.v10n1-8Keywords:
Building envelope, Cost-Comfort Optimisation Indicator (CCOI), Parametric simulation, Thermal comfort, Early-stage designAbstract
Building envelope decisions made during early design stages strongly affect construction expenditure, operational energy demand, and occupant comfort, yet available evaluation tools often treat these criteria separately. This study addresses the lack of a simple cost-sensitive decision-support metric for prioritising envelope alternatives before detailed design. It develops a Cost-Comfort Optimisation Indicator (CCOI) and tests it through DesignBuilder v2025 parametric simulations for a two-storey 750 m² office shoebox model in New Delhi’s composite climate. A one-variable-at-a-time approach assessed four wall assemblies, five glazing types, and eleven window-to-wall ratios from 20% to 70%, using annual comfort hours, cooling energy, and envelope construction cost as inputs. Results show that the super-insulated wall assembly achieved the highest wall-category performance, with 7,677.5 comfort hours, 157,210 kWh cooling energy, INR 3,318,800 envelope cost, and CCOI of 0.864. Double grey argon glazing ranked highest among glazing options, reaching 7,688 comfort hours, 163,942 kWh, and CCOI of 0.856. Most WWR increases above the 30% baseline produced negative CCOI values, indicating inefficient cost-performance trade-offs. The framework supports cost-conscious envelope selection, improves infrastructure efficiency, reduces energy-related operating burdens, and strengthens urban economic resilience through better resource allocation in growing cities.
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Achour-Younsi, S., Chabchoub, A., Jouini, N. E. H., & Kharrat, F. (2022). A Proposal to Mitigate Energy Consumption through the Sustainable Design Process in Tunis. Journal of Contemporary Urban Affairs, 6(2), 193-205. https://doi.org/10.25034/ijcua.2022.v6n2-6
Ahmed, A. E., Suwaed, M. S., Shakir, A. M., & Ghareeb, A. (2025). The impact of window orientation, glazing, and window-to-wall ratio on the heating and cooling energy of an office building: The case of hot and semi-arid climate. Journal of Engineering Research, 13(1), 409–422. https://doi.org/10.1016/j.jer.2023.10.034
Albatayneh, A. (2021). Sensitivity analysis optimisation of building envelope parameters in a sub-humid Mediterranean climate zone. Energy Exploration and Exploitation, 39(6), 2155–2180. https://doi.org/10.1177/01445987211020432
Altun, M. F. (2022). Determination of optimum building envelope parameters of a room concerning window-to-wall ratio, orientation, insulation thickness and window type. Buildings, 12(3), 383. https://doi.org/10.3390/buildings12030383
Ascione, F., Bianco, N., De Masi, R. F., Mauro, G. M., & Vanoli, G. P. (2017). Energy retrofit of educational buildings: Transient energy simulations, economic assessments, multi-criteria and multi-objective optimisation towards the nZEB target. Energy and Buildings, 144, 303–319. https://doi.org/10.1016/j.enbuild.2017.03.056.
ASHRAE (2023). Standard method of test for the evaluation of building energy analysis computer programs (ANSI/ASHRAE Standard 140-2023).
American Society of Heating, Refrigerating and Air-Conditioning Engineers. (2023). Thermal environmental conditions for human occupancy (ANSI/ASHRAE Standard 55-2023).
Aste, N., Leonforte, F., Manfren, M., & Mazzon, M. (2015). Thermal inertia and energy efficiency – Parametric simulation assessment on a calibrated case study. Applied Energy, 145, 111–123. https://doi.org/10.1016/j.apenergy.2015.01.084
Attia, S., Lioure, R., & Declaude, Q. (2020). Future trends and main concepts of adaptive facade systems. Energy Science & Engineering, 8(11), 4155–4172. https://doi.org/10.1002/ese3.725
Bano, F., Sehgal, V., & Tahseen, M. (2020). Early-stage design guidelines for net-zero-energy office buildings in tropical climate. 2020 International Conference on Contemporary Computing and Applications (IC3A), 143–149. https://doi.org/10.1109/IC3A48958.2020.233286
Biswas, M. H. A., Dey, P. R., Islam, M. S., & Mandal, S. (2022). Mathematical model applied to green building concept for sustainable cities under climate change. Journal of Contemporary Urban Affairs, 6(1), 36–50. https://doi.org/10.25034/ijcua.2022.v6n1-4
Bureau of Indian Standards. (2016). National Building Code of India 2016 (Vol. 1-2). Manak Bhavan, New Delhi: BIS.
Chaturvedi, P. K., Kumar, N., & Lamba, R. (2025). Multi-objective optimisation for visual, thermal, and cooling energy performance of building envelope design in the composite climate of Jaipur (India). Energy & Environment, 36(7), 3545–3569. https://doi.org/10.1177/0958305X241228513
Chaudhary, G. Q., Hu, Z., He, S., Ali, M., Ullah, S., Azam, M. W., Usman, M., Qin, N., & Gao, M. 2026). Analysis of building-integrated solar desiccant air cooling systems considering the dynamic sensible and latent cooling loads. International Journal of Refrigeration. 181 (2026) 111-125. https://doi.org/10.1016/j.ijrefrig.2025.10.007
Central Public Works Department (CPWD). (2023). Delhi schedule of rates (DSR) 2023. Government of India.
Central Public Works Department (CPWD). (2025). Plinth area rates (PAR) 2025. Government of India
Diakaki, C., Grigoroudis, E., & Kolokotsa, D. (2008). Towards a multi-objective optimization approach for improving energy efficiency in buildings. Energy and Buildings, 40(9), 1747–1754. https://doi.org/10.1016/j.enbuild.2008.03.002
Goia, F., Haase, M., & Perino, M. (2013). Optimizing the configuration of a façade module for office buildings by means of integrated thermal and lighting simulations in a total energy perspective. Applied Energy, 108, 515–527. https://doi.org/10.1016/j.apenergy.2013.02.063
Hamdy, M., Hasan, A., & Siren, K. (2013). A multi-stage optimisation method for cost-optimal and nearly-zero-energy building solutions in line with the EPBD-recast 2010. Energy and Buildings, 56, 189–203. https://doi.org/10.1016/j.enbuild.2012.08.023
Heiselberg, P., Brohus, H., Hesselholt, A., Rasmussen, H., Seinre, E., & Thomas, S. (2009). Application of sensitivity analysis in design of sustainable buildings. Renewable Energy, 34(9), 2030–2036. https://doi.org/10.1016/j.renene.2009.02.016
Hernández, G., Cetina-Quiñones, A. J., Bassam, A., & Carrillo, J. G. (2024). Passive strategies towards energy efficient social housing: A parametric case study and decision-making framework in the Mexican tropical climate. Journal of Building Engineering, 82, Article 108282. https://doi.org/10.1016/j.jobe.2023.108282
Hopfe, C. J., & Hensen, J. L. M. (2011). Uncertainty analysis in building performance simulation for design support. Energy and Buildings, 43(10), 2798–2805. https://doi.org/10.1016/j.enbuild.2011.06.034
Ihm, P., & Krarti, M. (2012). Design optimization of energy efficient residential buildings in Tunisia. Building and Environment, 58, 81–90. https://doi.org/10.1016/j.buildenv.2012.06.012
Kaynakli, O. (2012). A review of the economical and optimum thermal insulation thickness for building applications. Renewable and Sustainable Energy Reviews, 16(1), 415–425. https://doi.org/10.1016/j.rser.2011.08.006
Lam, J. C., Wan, K. K. W., Lam, T. N. T., & Wong, S. L. (2010). An analysis of future building energy use in subtropical Hong Kong. Energy, 35(3), 1482–1490. https://doi.org/10.1016/j.energy.2009.12.005
Lapisa, R., Arwizet, Kurniawan, A., Krismadinata, Rahman, H., & Romani, Z. (2022). Optimized design of residential building envelope in tropical climate region: Thermal comfort and cost efficiency in an Indonesian case study. Journal of Architectural Engineering, 28(2). https://doi.org/10.1061/(asce)ae.1943-5568.0000529
Manu, S., Shukla, Y., Rawal, R., Thomas, L. E., & de Dear, R. (2016). Field studies of thermal comfort across multiple climate zones for the subcontinent: India Model for Adaptive Comfort (IMAC). Building and Environment, 98, 55–70. https://doi.org/10.1016/j.buildenv.2015.12.019
Mirrahimi, S., Mohamed, M. F., Haw, L. C., Ibrahim, N. L. N., Yusoff, W. F. M., & Aflaki, A. (2016). The effect of building envelope on the thermal comfort and energy saving for high-rise buildings in hot–humid climate. Renewable and Sustainable Energy Reviews, 53, 1508–1519. https://doi.org/10.1016/j.rser.2015.09.055
Mohamadi, Y., Çelik, T., & Celik, T. (2024). Optimising building envelope and insulation materials for energy efficiency and life-cycle cost in Cypriot residences. Architectural Engineering and Design Management, 20(4), 1–19. https://doi.org/10.1080/17452007.2024.2325539
Nicol, J. F., & Humphreys, M. A. (2002). Adaptive thermal comfort and sustainable thermal standards for buildings. Energy and Buildings, 34(6), 563–572. https://doi.org/10.1016/S0378-7788(02)00006-3
Rahbarianyazd, R., & Raswol, L. (2018). Evaluating energy consumption in terms of climatic factors: A case study of Karakol residential apartments, Famagusta, North Cyprus. Journal of Contemporary Urban Affairs, 2(1), 45–54. https://doi.org/10.25034/ijcua.2018.3658
Singh, M. K., Mahapatra, S., & Atreya, S. K. (2018). A bioclimatic approach to develop spatial zoning maps for comfort, passive heating and cooling strategies within a composite zone of India. Building and Environment, 128, 190–215. https://doi.org/10.1016/j.buildenv.2017.11.029
Talaei, M., & Sangin, H. (2024). Multi-objective optimization of energy and daylight performance for school envelopes in desert, semi-arid, and mediterranean climates of Iran. Building and Environment, 255, Article 111424. https://doi.org/10.1016/j.buildenv.2024.111424
Tian, Z. C., Chen, W. Q., Tang, P., Wang, J. G., & Shi, X. (2015). Building energy optimization tools and their applicability in architectural conceptual design stage. Energy Procedia, 78, 2572–2577. https://doi.org/10.1016/j.egypro.2015.11.288
Wang, W., Zmeureanu, R., & Rivard, H. (2005). Applying multi-objective genetic algorithms in green building design optimization. Building and Environment, 40(11), 1512–1525. https://doi.org/10.1016/j.buildenv.2004.11.017
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