[en] The present paper aims to show a mathematical understanding of the effect of ventilation
rate over building energy consumption. Moreover, as a case study to show this methodology,
a proposal was analyzed of modifying the teaching period to reach a maximum increase of air changes in school buildings, to allow adherence to the COVID-19 pandemic requirements in the Galicia region,with lower energy consumption. In this sense, to analyze the energetic implication of this proposal, the building construction was defined, modeled in accordance with the ISO Standard 13790 and implemented in accordance with the Monte Carlo method. Results showed the probability of energy consumption as a Weibull model. Furthermore, a map of different Weibull models in accordance with different ventilation rates was developed. The constants of the Weibull models allow to identify normal distributions of the probability density functions of energy consumption, especially the ones with lower energy consumption. As a consequence, these constants are a better parameter to identify the optimal ventilation rate for each season in search of a healthy indoor ambience, which is of interest for a future design guide. Finally, the main results showed a reduction of energy consumption at a higher ventilation rate in the summer season. As a consequence, the necessity of modifying teachings periods, as an adequate procedure to prevent more COVID infections, is concluded.
Research center :
LEMA UEE - Urban and Environmental Engineering - ULiège Lepur : Centre de Recherche sur la Ville, le Territoire et le Milieu rural - ULiège
Disciplines :
Energy Architecture
Author, co-author :
Orosa, José A.; University of A Coruña
Kameni Nematchoua, Modeste ; Université de Liège - ULiège > Département ArGEnCo > Urbanisme et aménagement du territoire
Reiter, Sigrid ; Université de Liège - ULiège > Département ArGEnCo > Urbanisme et aménagement du territoire
Language :
English
Title :
Air Changes for Healthy Indoor Ambiences under Pandemic Conditions and Its Energetic Implications: A Galician Case Study
Orosa, J.A.; Oliveira, A.C. An indoor air perception method to detect fungi growth in flats. Expert Syst. Appl. 2012, 39, 3740–3746. [CrossRef]
ASHRAE Indications Reoupening Schools and Universities. Available online: https://www.ashrae.org/technical-resources/reopening-of-schools-and-universities (accessed on 22 September 2020).
REHVA CO2 Sensor. Available online: https://www.rehva.eu/fileadmin/user_upload/REHVA_COVID-19_ guidance:document_V3_03082020.pdf (accessed on 22 September 2020).
How Covid Travels in Classrooms. Available online: https://cse.umn.edu/college/news/new-study-explores-how-coronavirus-travels-indoors (accessed on 22 September 2020).
WHO. World Health Organization. Schools. Available online: https://www.who.int/publications/m/item/key-messages-and-actions-for-covid-19-prevention-and-control-in-schools (accessed on 22 September 2020).
Nematchoua, M.K.; Mempouo, B.; Tchinda, R.; Costa, A.M.; Orosa, J.A.; Raminosoa, C.R.R.; Mamiharijaona, R. Resource potential and energy efficiency in the buildings of Cameroon: A review. Renew. Sustain. Energy Rev. 2015, 50, 835–846.
Nematchoua, M.K.; Tchinda, R.; Orosa, J.A. Thermal comfort and energy consumption in modern versus traditional buildings in Cameroon: A questionnaire-based statistical study. Appl. Energy 2014, 114, 687–699. [CrossRef]
Peng, L.L.H.; Jim, C.Y. Green-Roof Effects on Neighborhood Microclimate and Human Thermal Sensation. Energies 2013, 6, 598–618. [CrossRef]
Jim, C.Y. Thermal performance of climber greenwalls: Effects of solar irradiance and orientation. Appl. Energy 2015, 154, 631–643. [CrossRef]
Setiawan, A.F.; Tzu-Ling, H.; Chun-Ta, T.; Chi-Ming, L. The Effects of Envelope Design Alternatives on the Energy Consumption of Residential Houses in Indonesia. Energies 2015, 8, 2788–2802. [CrossRef]
Parra, J.; Guardo, A.; Egusquiza, E.; Alavedra, P. Thermal Performance of Ventilated Double Skin Façades with Venetian Blinds. Energies 2015, 8, 4882–4898. [CrossRef]
ASHRAE Handbook: HVAC Fundamentals; Spanish Edition, Editorial Index; ASHRAE: Atlanta, GA, USA, 2013; pp. 1–197.
ISO 13790. Thermal Performance of Buildings-Calculation of Energy Use for Space Heating and Cooling; ISO/DIS 13790:2008; International Organization for Standardization: Geneva, Switzerland, 2008.
International Energy Agency (IEA). Welcome to the International Energy Agency’s Energy in Buildings and Communities Programme. Available online: https://www.iea-ebc.org (accessed on 8 October 2020).
Haarhoff, J.; Mathews, E.H. A Monte Carlo method for thermal building simulation. Energy Build. 2006, 38, 1395–1399. [CrossRef]
Keirstead, J.; Shah, N. Calculating minimum energy urban layouts with mathematical programming and Monte Carlo analysis techniques. Comput. Environ. Urban Syst. 2011, 35, 368–377. [CrossRef]
Mavrotas, G.; Florios, K.; Vlachou, D. Energy planning of a hospital using Mathematical Programming and Monte Carlo simulation for dealing with uncertainty in the economic parameters. Energy Convers. Manag. 2010, 51, 722–731. [CrossRef]
Gang, W.; Wang, S.; Shan, K.; Gao, D. Impacts of cooling load calculation uncertainties on the design optimization of building cooling systems. Energy Build. 2015, 94, 1–9. [CrossRef]
Ren, X.; Yan, D.; Wang, C. Air-conditioning usage conditional probability model for residential buildings. Build. Environ. 2014, 81, 172–182. [CrossRef]
Lu, Y.; Huang, Z.; Zhang, T. Method and case study of quantitative uncertainty analysis in building energy consumption inventories. Energy Build. 2013, 57, 193–198. [CrossRef]
Srinivasa Rao, A.S.R. On joint Weibull probability density functions. Appl. Math. Lett. 2005, 18, 1224–1227. [CrossRef]
Prabhakar Murthy, D.N.; Bulmer, M.; Eccleston, J.A. Weibull model selection for reliability modelling. Reliab. Eng. Syst. Safe 2004, 86, 257–267. [CrossRef]
MeteoGalicia. Anuario Climatolóxico de Galicia. Consellería de Medio Ambiente. Xunta de Galicia. Available online: https://www.meteogalicia.gal/observacion/informesclima/informesIndex.action?request_locale=es (accessed on 13 October 2020).
Orosa, J.A.; Oliveira, A.C. Implementation of a method in EN ISO 13790 for calculating the utilisation factor taking into account different permeability levels of internal coverings. Energy Build. 2010, 42, 598–604. [CrossRef]
Orosa, J.A.; García-Bustelo, E.J. Permeable coverings as a sustainable solution for indoor air thermal comfort and energy saving. Energy Edu. Sci. Technol. A 2012, 29, 583–596.
Masdias-Bonome, A.E.; Orosa, J.A.; Vergara, D. A New Methodology for Decision-Making in Buildings Energy Optimization. Appl. Sci. 2020, 10, 4558. [CrossRef]
Šadauskienė, J.; Paukštys, V.; Šeduikytė, L.; Banionis, K. Impact of Air Tightness on the Evaluation of Building Energy Performance in Lithuania. Energies 2014, 7, 4972–4987. [CrossRef]
Fei, F.; Zhou, S.; Mai, J.D.; Li, W.J. Development of an Indoor Airflow Energy Harvesting System for Building Environment Monitoring. Energies 2014, 7, 2985–3003. [CrossRef]
Nematchoua, M.K.; Tchinda, R.; Orosa, J.A.; Andreasi, W.A. Effect of wall construction materials over indoor air quality in humid and hot climate. J. Build. Eng. 2015, 3, 16–23. [CrossRef]
Karlsson, F.; Fahlén, P. Impact of design and thermal inertia on the energy saving potential of capacity controlled heat pump heating systems. Int. J. Refrig. 2008, 31, 1094–1103. [CrossRef]
Mazarrón, F.R.; Cid-Falceto, J.; Cañas, I. Ground Thermal Inertia for Energy Efficient Building Design: A Case Study on Food Industry. Energies 2012, 5, 227–242. [CrossRef]
Orosa, J.A. Thermal inertia and ISO 13790—Have its effects on future energy consumption been fully considered? Energy Edu. Sci. Technol. 2012, 29, 339–352.
Orosa, J.A.; Oliveira, A.C. A field study on building inertia and its effects on indoor thermal environment. Renew. Energy 2012, 37, 89–96. [CrossRef]
MeteoGalicia. Xunta de Galicia. Consellería de Medio ambiente Teorritorio e Vivenda. Available online: https://www.meteogalicia.gal/datosred/infoweb/clima/informes/estacions/anuais/2019_es.pdf (accessed on 22 September 2020).
