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.
National indicators point that 85% of Mexico’s energy production come from fossil fuels. Quintana Roo is the state with the most significant increase on energy consumption with almost 20% from 2010 to 2017. This project carries out a holistic energy analysis approach in three case studies in typical dwellings built with average materials and construction systems under tropical climate conditions. Two validation levels were performed, one with an historical weather data file, and the second one with a costumed weather file corresponding to February 2019. The obtained values of mean bias error on an hourly-based analysis in interior conditions varied with the following ranges: level 1, from 1.57% to 2.11%; in level 2, from 1.17% to 1.74%. On the other hand, it was also found that the first level of simulation predicted the electricity consumption slightly closer to actual values reported for February 2019, with values ranging from 7.56% to 16.63%. However, further analysis with more detailed input data and monitoring of daily consumption is recommended in order to reduce the variation ranges.
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