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Article

Analysis of Energy and Environmental Indicators for Sustainable Operation of Mexican Hotels in Tropical Climate Aided by Artificial Intelligence

by
S. G. Mengual Torres
1,
O. May Tzuc
2,*,
K. M. Aguilar-Castro
3,
Margarita Castillo Téllez
2,
J. Ovando Sierra
2,
Andrea del Rosario Cruz-y Cruz
2 and
Francisco Javier Barrera-Lao
2
1
Estudiante de Posgrado, Facultad de Ingeniería, Universidad Autónoma de Campeche, Campus V, Av. Humberto Lanz, Col. Ex Hacienda Kalá, San Francisco de Campeche 24085, Campeche, Mexico
2
Facultad de Ingeniería, Universidad Autónoma de Campeche, Campus V, Av. Humberto Lanz, Col. Ex Hacienda Kalá, San Francisco de Campeche 24085, Campeche, Mexico
3
División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Carret. Cunduacán-Jalpa de Méndez Km. 1, Unidad Chontalpa, Cunduacán 86690, Tabasco, Mexico
*
Author to whom correspondence should be addressed.
Buildings 2022, 12(8), 1155; https://doi.org/10.3390/buildings12081155
Submission received: 10 June 2022 / Revised: 7 July 2022 / Accepted: 21 July 2022 / Published: 3 August 2022
(This article belongs to the Special Issue Building Energy Consumption and Urban Energy Planning)
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Abstract

This study assessed the energy-use index and carbon-footprint performance of nine medium-category Mexican hotels (two–four stars) located in tropical-climate regions. The consumption of electrical and thermal energies of each hotel was collected during audits. Based on this, various scenarios of the partial replacement of the most energy-consuming devices were evaluated and synthesized in an expert model based on artificial neural networks. The artificial-intelligence model was designed to simultaneously associate the energy-consumption indicators, environmental impact, and economic savings of hotels based on their category, location, room number, number of existing electrical or thermal devices, and their percentage of substitution with more energy-efficient technologies. The model was used to compare the various partial-technology-substitution alternatives in each hotel that could reduce energy consumption and CO2 emissions based on the current values reported by the energy-use and environmental-impact indicators. The results of the proposed approach showed that even without making total replacements of equipment such as interior and exterior lighting or air conditioners, it was possible to identify configurations that could reduce the hotels’ energy use per room-year by 9–12%. In the environmental case, using more efficient technologies could reduce environmental mitigation. The proposed methodology represents an attractive option to facilitate the analyses and the decision making of administrators according to the needs of the type of hotel to improve its performance, which also affects the reduction in operating costs.
Keywords: artificial neural networks; building sustainability; digital twins; energy efficiency; intensity use of energy; CO2 reduction; hotel management artificial neural networks; building sustainability; digital twins; energy efficiency; intensity use of energy; CO2 reduction; hotel management

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MDPI and ACS Style

Mengual Torres, S.G.; May Tzuc, O.; Aguilar-Castro, K.M.; Castillo Téllez, M.; Ovando Sierra, J.; Cruz-y Cruz, A.d.R.; Barrera-Lao, F.J. Analysis of Energy and Environmental Indicators for Sustainable Operation of Mexican Hotels in Tropical Climate Aided by Artificial Intelligence. Buildings 2022, 12, 1155. https://doi.org/10.3390/buildings12081155

AMA Style

Mengual Torres SG, May Tzuc O, Aguilar-Castro KM, Castillo Téllez M, Ovando Sierra J, Cruz-y Cruz AdR, Barrera-Lao FJ. Analysis of Energy and Environmental Indicators for Sustainable Operation of Mexican Hotels in Tropical Climate Aided by Artificial Intelligence. Buildings. 2022; 12(8):1155. https://doi.org/10.3390/buildings12081155

Chicago/Turabian Style

Mengual Torres, S. G., O. May Tzuc, K. M. Aguilar-Castro, Margarita Castillo Téllez, J. Ovando Sierra, Andrea del Rosario Cruz-y Cruz, and Francisco Javier Barrera-Lao. 2022. "Analysis of Energy and Environmental Indicators for Sustainable Operation of Mexican Hotels in Tropical Climate Aided by Artificial Intelligence" Buildings 12, no. 8: 1155. https://doi.org/10.3390/buildings12081155

APA Style

Mengual Torres, S. G., May Tzuc, O., Aguilar-Castro, K. M., Castillo Téllez, M., Ovando Sierra, J., Cruz-y Cruz, A. d. R., & Barrera-Lao, F. J. (2022). Analysis of Energy and Environmental Indicators for Sustainable Operation of Mexican Hotels in Tropical Climate Aided by Artificial Intelligence. Buildings, 12(8), 1155. https://doi.org/10.3390/buildings12081155

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