Indoor Temperature Validation of Low-Income Detached Dwellings under Tropical Weather Conditions

• Published in: Climate (Basel) Vol. 7; no. 8; p. 96
• Main Authors: Barrientos-González, R. Alexis, Vega-Azamar, Ricardo E., Cruz-Argüello, Julio C., Oropeza-García, Norma A., Chan-Juárez, Maritza, Trejo-Arroyo, Danna L.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2019
• Subjects: Air conditioning; Calibration; Case studies; Coefficient of variation; Cooling systems; Dwellings; Electricity; Electricity consumption; Energy consumption; Environmental conditions; Environmental factors; Environmental parameters; Error reduction; Houses; Housing; Humidity; Indoor air quality; Indoor environments; indoor temperature; Low income groups; low-income detached dwelling; Mitigation; performance gap; Public housing; Residential areas; Residential buildings; Simulation; simulation model; Temperature; Tropical climate; Tropical climates; tropical weather; Urban areas; urban heat island; Ventilation; Weather; Weather conditions; Mexico
• ISSN: 2225-1154; 2225-1154
• DOI: 10.3390/cli7080096

Urban territorial expansion generated in the last decades has brought a series of consequences, such as the variation between urban and suburban weather conditions affecting indoor temperature and increasing electricity consumption derived from the use of cooling systems. Current approaches of simulation models in residential buildings use indoor environmental data for carrying out validations to propose hygrothermal comfort alternatives for the mitigation of the effects of the external environmental conditions on the interior spaces of dwellings. In this work, an hourly evaluation of both indoor and outdoor environmental parameters of two case studies in a tropical climate was carried out, by means of a whole-building simulation approach tool during a week representative of the warmest period of the year. The integration of the collected environmental data in the theoretical model allowed us to reduce the error range of the estimated indoor temperature with results in normalized mean bias error between 7.10% and −0.74% and in coefficient of variation of the root mean square error between 16.72% and 2.62%, in the different indoor zones of the case studies. At the same time, the energy assessment showed a difference of 33% in Case 1 and −217% in Case 2 for final electricity consumption.