1,720,969 research outputs found
Main physical environmental drivers of occupant behaviour with regard to space heating energy demand
No full textSeveral studies have highlighted the significant gap between the predicted energy performance of buildings and their measured actual performance. Uncertainties regarding behaviour of building occupants are one of the key factors limiting the ability of energy simulation tools to accurately predict real building energy requirements .
The paper focuses on the particular topics of space heating energy demand related to the occupants habits of adjusting heating set-points. The parameters influencing the user interaction with the heating control system are analyzed in literature for residential buildings, and the resulted influencing factors are illustrated.
Statistical analysis of data coming from measurement carried out in Danish dwellings are performed to infer the probability of adjusting the thermostatic radiators valves and to determine the relationship between the (indoor and outdoor) environmental conditions and the occupants’ heating set-point preferences. The paper aims at providing a reliable basis for a more accurate description of control action models in performance simulation applications
Influence of user behaviour on indoor environmental quality and heating energy consumptions in danish dwellings
No full textModels of occupants’ interactions with heating controls based on measurements were implemented in a simulation program. Simulation results were given as probability distributions of energy consumption and indoor environmental quality depending on user behaviour. Heating set-point behaviour of 13 Danish dwellings were analysed by means of logistic regression to infer the probability of adjusting the set-point of TRVs. Three different models of occupant’s interactions with heating controls were obtained and implemented in a building simulation tool. They were used to investigate how different probabilistic user patterns influence indoor climate quality and energy consumptions. The aim was to compare the obtained results with an actual/deterministic use of the simulation program. Since comfort categories are related to users’ expectations and the users’ impact is crucial on determining the energy consumption, findings highlight the influence of comfort categories on energy consumption. The probabilistic methodology can be applied in all aspects of user interactions with building controls such as window openings, shading devices, etc. to achieve more realistic predictions of energy consumptions
Window opening behaviour: simulations of occupant behaviour in residential buildings using models based on a field survey
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Influence of occupant's heating set-point preferences on indoor environmental quality and heating demand in residential buildings
No full textThe aim of this study was to switch from a deterministic approach of building energy simulation toward a probabilistic one that takes into account the occupants interactions with the building controls. A probabilistic approach is proposed and applied to simulate occupant behavior realistically. The methodology was based on probabilistic evaluation of both input and output variables of building energy simulations. The developed methodology can be applied in all aspects of occupant's interactions with building controls, such as window openings, shading devices, etc., to achieve more realistic predictions of energy consumption. The aim was to compare the obtained results with a traditional deterministic use of the simulation program. Based on heating set-point behavior of 13 Danish dwellings, logistic regression was used to infer the probability of adjusting the set-point of thermostatic radiator valves. Three different models of occupant's interactions with heating controls were obtained and implemented in a building simulation tool. The models of occupant's behavior patterns were used to investigate how different behavior patterns influence indoor climate quality and energy consumption. Simulation results were given as probability distributions of energy consumption and indoor environmental quality depending on occupant's behavior. Copyright © 2013 Crown copyright
Main physical environmental variables driving occupant behaviour with regard to natural ventilation
Full text linkEnergy consumption in buildings is influenced by building properties, building controls and the way that these are used by the occupants of the building. This paper focuses on natural ventilation concerning the occupants' habits of opening/closing the windows in residential buildings. Preeminent variables influencing the occupants' use of windows are investigated and the main results of a literature review are highlighted. Statistical analysis of data coming from measurements of occupants' window opening, conducted in 15 dwellings in Denmark, are developed to infer the probability of opening and closing windows and to determine relationships between environmental conditions and the occupants' window opening behaviour. The main physical environmental variables that have been found to be important drivers in determining the action to open or close windows are defined on the basis of the measurements. The ultimate goal is to provide more accurate information about driving forces related to the window opening and closing behaviou
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Validation of models of users' window opening behaviour in residential buildings
Full text linkThe characterisation of window opening behaviour is crucial for suitable prediction of building performance (energy consumption, indoor environmental quality, etc.) by means of simulations. In this paper, data from a measurement campaign was used to validate three models of window opening behaviour. Data from the measurement campaign was used as input in the models to calculate the probability of opening and closing windows. Afterwards, the validation was carried out by comparing the predicted probabilities with the actual measured state of the windows in the dwellings
Influence Of Window Opening And Closing Behaviour and Heating Set-Point Adjustments on Heating Energy Consumption in Dwellings
No full textEnergy building simulations are key tools to be used in each design phase of the building . Actually, the ability of building energy simulation programs to evaluate real energy use is undermined by a poor representation of the stochastic variables entering the calculation: among these, the ones relate human interactions with the control of the indoor environment are crucial.One of the reason of the discrepancy between simulated and real energy use in buildings lies in the fact that simulation tools are only able to describe control actions modelling deterministically and following predefined and fixed schedules. Indeed models of human behaviour are generally described by statistical algorithms that predict the probability of an action occurs.. Moreover, building energy simulation programs are not currently able to adequately evaluate different scenarios explaining occupant behaviour's influence. The efforts described in this paper are defining realistic user profiles to implement in most of the buildings simulation tools. This work mainly focused on the investigation on how different probabilistic user patterns (adjusting thermostat set-point and window opening behaviour) influenced energy consumption with the aim to compare the obtained results with a regular use of the simulation program. Models of human behaviour based on measurements were implemented and simulations results given as probabilistic distribution of values of energy consumption were calculated, depending on different levels of users' behavio
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