Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States

A carefully chosen indoor comfort temperature as the thermostat set-point is the key to optimizing building energy use and occupants’ comfort and well-being. ASHRAE Standard 55 or ISO Standard 7730 uses the PMV-PPD model or the adaptive comfort model that is based on small-sized or outdated sample data, which raises questions on whether and how ranges of occupant thermal comfort temperature should be revised using more recent larger-sized dataset. In this paper, a Bayesian inference approach has been used to derive new occupant comfort temperature ranges for U.S. office buildings using the ASHRAE Global Thermal Comfort Database. Bayesian inference can express uncertainty and incorporate prior knowledge. The comfort temperatures were found to be higher and less variable at cooling mode than at heating mode, and with significant overlapped variation ranges between the two modes. The comfort operative temperature of occupants varies between 21.9 and 25.4 °C for the cooling mode with a median of 23.7 °C, and between 20.5 and 24.9 °C for the heating mode with a median of 22.7 °C. These comfort temperature ranges are similar to the current ASHRAE standard 55 in the heating mode but 2–3 °C lower in the cooling mode. The results of this study could be adopted as more realistic thermostat set-points in building design, operation, control optimization, energy performance analysis, and policymaking

The role of a building’s thermal properties on pupils’ thermal comfort in junior school classrooms as determined in field studies

Recent thermal comfort research in a light-weight junior school building showed that children were more sensitive to higher temperatures than adults and subsequently that current thermal comfort standards were not appropriate for the assessment of their thermal environment. This paper presents a comparison of these survey results to those from a survey conducted in a medium-weight school building, in order to evaluate the role of the construction type on the results. Both surveys followed the same methodology, including thermal comfort questionnaires and measurements of indoor environmental variables. A total of 2990 responses were gathered. The buildings had an average difference in air temperature of 2.7oC during occupied hours in the period of investigation (June and July 2012), with the medium-weight building being cooler than the light-weight building. However, the different construction type and the cooler overall thermal environment in the medium-weight school building had little impact on the pupils’ overall thermal sensitivity. The comparison showed a general agreement on the pupils’ warm thermal sensation trends, interpersonal variation and undeveloped adaptive behaviour. The results further support the finding that current thermal comfort criteria lead to an underestimation of pupils’ thermal sensation during summer

Revisiting individual and group differences in thermal comfort based on ASHRAE database

Different thermal demands and preferences between individuals lead to a low occupant satisfaction rate, despite the high energy consumption by HVAC system. This study aims to quantify the difference in thermal demands, and to compare the influential factors which might lead to those differences. With the recently released ASHRAE Database, we quantitatively answered the following two research questions: which factors would lead to marked individual difference, and what the magnitude of this difference is. Linear regression has been applied to describe the macro-trend of how people feel thermally under different temperatures. Three types of factors which might lead to different thermal demands have been studied and compared in this study, i.e. individual factors, building characteristics and geographical factors. It was found that the local climate has the most marked impact on the neutral temperature, with an effect size of 3.5 °C; followed by country, HVAC operation mode and body built, which lead to a difference of more than 1 °C. In terms of the thermal sensitivity, building type and local climate are the most influential factors. Subjects in residential buildings or coming from Dry climate zone could accept 2.5 °C wider temperature range than those in office, education buildings or from Continental climate zone. The findings of this research could help thermal comfort researchers and designers to identify influential factors that might lead to individual difference, and could shed light on the feature selection for the development of personal comfort models

How subjective and non-physical parameters affect occupants’ environmental comfort perception

Employees’ wellbeing and comfort perception demonstrated to largely influence their productivity and tolerability of slight thermal discomfort conditions in the working spaces. Their whole comfort perception indeed depends on several parameters related to physical boundary conditions but also to the adaptation capability of occupants themselves and other personal, difficult to measure, variables. According to the available standards and regulations, only physical and measurable environmental parameters must be considered to evaluate occupants’ comfort conditions. Therefore, non-measurable factors such as socio-psychological, physiological, medical ones are currently not systematically considered. The present work aims to identify possible benefits in terms of occupants’ comfort perception due to non-physical strategies aimed at improving the work-environment quality and livability. To this aim, the environmental multi-physics and multi-domain performance of a mixed industry-office building is investigated through coupled in-field microclimate monitoring and questionnaires campaigns. The experimental microclimate monitoring and survey campaign were carried out to understand (i) the realistic indoor environmental conditions in terms of physical and measurable parameters and (ii) the personal perceptions and attitudes of the occupants with respect to those same ambient parameters, including also acoustic, lighting and medical investigation. Moreover, the collected experimental data were used to determine occupants’ comfort level through the classic comfort models, to be compared to the identified role of non-physical parameters on occupants’ final perception about the indoor environment. The main results show that non-measurable factors induced by virtuous company policy to improve employees’ working environment are effectively able to positively influence their whole-comfort perception even if the majority of workers do not have the opportunity to control their working environment. In fact, the consolidated comfort theories underestimate people satisfaction, as demonstrated by more than the 80% employees, who declared to be positively influenced by the pleasant aesthetics and livability of the workplace. The year-round experimental campaign demonstrated the need to further investigate the key role of non-physical parameters for possible incorporation into whole-comfort prediction models and standards. The role of such strategies could therefore be realistically considered as energy saving opportunities since they make building occupants much more open to tolerate slight uncomfortable conditions

Advances to ASHRAE Standard 55 to encourage more effective building practice

ASHRAE Standard 55 has been evolving in recent years to encourage more sustainable building designs and operational practices. A series of changes address issues for which past design practice has been deficient or overly constrained. Some of the changes were enabled by findings from field studies of comfort and energy-efficiency, and others by new developments in the design- and building-management professions.  The changes have been influencing practice and spurring follow-on research.The Standard now addresses effects of elevated air movement, solar gain on the occupant, and draft at the ankles, each with several impacts on energy-efficient design and operation. It also addresses the most important source of discomfort in modern buildings, the large inter- and intra-personal variability in thermal comfort requirements, by classifying the occupants’ personal control and adaptive options in a form that can be used in building rating systems. In order to facilitate design, new computer tools extend the use of the standard toward direct use in designers’ workflow. The standard also includes provisions for monitoring and evaluating buildings in operation. This paper summarizes these developments and their underlying research, and attempts to look ahead

Thermal performance of a naturally ventilated building using a combined algorithm of probabilistic occupant behaviour and deterministic heat and mass balance models

This study explores the role of occupant behaviour in relation to natural ventilation and its effects on summer thermal performance of naturally ventillated buildings. We develop a behavioural algorithm (the Yun algorithm) representing probablistic occupant behaviour and implement this within a dynamic energy simulation tool. A core of this algorithm is the use of Markov chain and Monte Carlo methods in order to integrate probablistic window use models into dynamic energy simulation procedures. The comparison between predicted and monitored window use patterns shows good agreement. Performance of the Yn algorithm is demonstrated for active, medium and passive window users and a range of office constructions. Results indicate, for example, that in some cases, the temperature of an office occupied by the active window user in summer is up to 2.6ºC lower than that for the passive window user. A comparison is made with results from an alernative bahavioural algorithm developed by Humphreys [H.B. Rijal, P. Tuohy, M.A. Humphreys, J.F. Nicol, A. Samual, J. Clarke, Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings, Energy and Buildings 39(7)(2007) 823-836.]. In general, the two algorithms lead to similar predictions, but the results suggest that the Yun algorithm better reflects the observed time of day effects on window use (i.e. the increased probability of action on arrival)

Predicting adaptive responses - simulating occupied environments

Simulation of building performance is increasingly being used in design practice to predict comfort of occupants in finished buildings. This is an area of great uncertainty: what actions does a person take when too warm or suffering from glare; how is comfort measured; how do groups of people interact to control environmental conditions, etc? An increasing attention to model these issues is evident in current research. Two issues are covered in this paper: how comfort can be assessed and what actions occupants are likely to make to achieve and maintain a comfortable status. The former issue describes the implementation of existing codes within a computational framework. This is non-trivial as information on local air velocities, radiant temperature and air temperature and relative humidity have to be predicted as they evolve over time in response to changing environmental conditions. This paper also presents a nascent algorithm for modelling occupant behaviour with respect to operable windows. The algorithm is based on results of several field studies which show the influence of internal and external temperatures on decision making in this respect. The derivation and implementation of the algorithm is discussed, highlighting areas where further effort could be of benefit

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare