Search

Ecuador is a country with several climate zones. However, their behaviour is similar throughout the year, with no peaks of extreme temperatures in the various seasons. This paper is a first approach to study the adaptive comfort behaviour in several areas and populations of the country. Considering the ASHRAE 55-2020 model, energy simulation programmes are applied not just to the current climate scenario but also to the climate change scenarios of 2050 and 2100. The results of locations are analysed and compared to determine their performance. Thanks to their climate characteristics, adaptive comfort models could be applied as a passive strategy, using natural ventilation for building indoor comfort improvement, particularly social dwellings. According to previous studies, some prototypes have not considered the climate determinants in each region. Given the geographic situation of the study areas, the adaptive comfort model could be applied in all cases. Percentages of application of natural ventilation and heating and cooling degree hours have similar behaviours according to the climatic region, with a variation greater than 30% among them. [ABSTRACT FROM AUTHOR]

Since indoor clothing insulation is a key element in thermal comfort models, the aim of the present study is proposing an approach for predicting it, which could assist the occupants of a building in terms of recommendations regarding their ensemble. For that, a systematic analysis of input variables is exposed, and 13 regression and 12 classification machine learning algorithms were developed and compared. The results are based on data from 3352 questionnaires and 21 input variables from a field study in mixed-mode office buildings in Spain. Outdoor temperature at 6 a.m., indoor air temperature, indoor relative humidity, comfort temperature and gender were the most relevant features for predicting clothing insulation. When comparing machine learning algorithms, decision tree-based algorithms with Boosting techniques achieved the best performance. The proposed model provides an efficient method for forecasting the clothing insulation level and its application would entail optimising thermal comfort and energy efficiency. [ABSTRACT FROM AUTHOR]

It has been found in recent years that using setpoint temperatures based on adaptive thermal comfort models is a successful method of energy conservation. Recent studies using adaptive setpoint temperatures incorporate international models from ASHRAE Standard 55 and EN16798-1. This study, however, has instead considered a regional Brazilian adaptive comfort model. This study investigates the energy demand arising from the use of a local Brazilian comfort model in order to assess the energy implications from the use of the worldwide ASHRAE Standard 55 adaptive model and various fixed setpoint temperatures. All of Brazil's climate zones, full air-conditioning, mixed-mode building operating modes, present-day climate change scenarios, and future scenarios—specifically Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 for the years 2050 and 2100—have all been taken into account in building energy simulations. The use of adaptive setpoint temperatures based on the Brazilian local model considering mixed-mode has been found to significantly reduce energy consumption when compared to static setpoint temperatures (average energy-saving values ranging from 52% to 58%) and the ASHRAE 55 adaptive model (average values ranging from 15% to 21%). Considering climate change and the mixed-mode Brazilian model, the overall energy demand for the three groups of climatic zones (annual average outdoor temperatures ≤ 21 °C, > 21 and ≤ 25 °C and > 25 °C) ranged between 2% decrease and 5% increase, 4% and 27% increase, and 13% and 45% increase, respectively. It is concluded as a consequence that setting setpoint temperatures based on the Brazilian local adaptive comfort model is a very efficient energy-saving method. [ABSTRACT FROM AUTHOR]

Ecuador is a country with several climate zones. However, their behaviour is similar throughout the year, with no peaks of extreme temperatures in the various seasons. This paper is a first approach to study the adaptive comfort behaviour in several areas and populations of the country. Considering the ASHRAE 55-2020 model, energy simulation programmes are applied not just to the current climate scenario but also to the climate change scenarios of 2050 and 2100. The results of locations are analysed and compared to determine their performance. Thanks to their climate characteristics, adaptive comfort models could be applied as a passive strategy, using natural ventilation for building indoor comfort improvement, particularly social dwellings. According to previous studies, some prototypes have not considered the climate determinants in each region. Given the geographic situation of the study areas, the adaptive comfort model could be applied in all cases. Percentages of application of natural ventilation and heating and cooling degree hours have similar behaviours according to the climatic region, with a variation greater than 30% among them.