Adaptive actions on shading devices in response to local visual stimuli

Haldi, Frédéric; Robinson, Darren

doi:10.1080/19401490903580759

Cited by 182 publications

(153 citation statements)

References 11 publications

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“…One caveat related to this study is that the use of dynamic shading systems has not been addressed thus far even though methods to model the use of movable shading systems have been proposed in the past [Reinhart 2004;Haldi & Robinson 2010;O'Brien et al 2013]. The reason for this shortcoming is that it is doubtful whether students and or in fact any non-expert visiting a space for a single time could possibly predict the implications of a shading device and control situation over a whole year.…”

Section: Open Questionsmentioning

confidence: 83%

Predicting the Daylit Area—A Comparison of Students Assessments and Simulations at Eleven Schools of Architecture

Reinhart

Rakha

Weissman

2014

LEUKOS

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In recent years climate-based metrics, in particular daylight autonomy, have found their way into North American standards and green building rating systems. The authors showed in an earlier pilot study that subjective space evaluations by architecture students correlated well with daylight-autonomy-based daylit area simulations in a single north-facing studio space in Boston. For this manuscript the authors collaborated with educators at 11 schools of architecture and applied the method consistently to 13 spaces within the participating schools. The schools are located in Brazil (2), Canada (1), Egypt (1) and the United States (7). The authors also introduce the concept of a "partially daylight area" metric based on a minimum illuminance threshold for daylight autonomy of 150lux. The two metrics correctly determined in 18 out of 24 cases which parts of the study space are fully or partially daylit. The authors accordingly propose a two-tier evaluation system to rate the daylight availability in spaces.

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Section: Open Questionsmentioning

confidence: 83%

Predicting the Daylit Area—A Comparison of Students Assessments and Simulations at Eleven Schools of Architecture

Reinhart

Rakha

Weissman

2014

LEUKOS

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“…Human behaviour related to shading depends primarily on shortwave radiation and secondarily on indoor air temperature (Raja et al, 2001;Haldi and Robinson, 2010). These meteorological parameters are particularly important in office buildings, whereas in residential buildings nonmeteorological parameters like privacy or security can also influence shading (Vorger, 2014).…”

Section: A4 Shadingmentioning

confidence: 99%

Parametrisation of the variety of human behaviour related to building energy consumption in the Town Energy Balance (SURFEX-TEB v. 8.2)

et al. 2017

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Abstract. The anthropogenic heat flux can be an important part of the urban surface energy balance. Some of it is due to energy consumption inside buildings, which depends on building use and human behaviour, both of which are very heterogeneous in most urban areas. Urban canopy parametrisations (UCP), such as the Town Energy Balance (TEB), parametrise the effect of the buildings on the urban surface energy balance. They contain a simple building energy model. However, the variety of building use and human behaviour at grid point scale has not yet been represented in state of the art UCPs. In this study, we describe how we enhance the Town Energy Balance in order to take fractional building use and human behaviour into account. We describe how we parametrise different behaviours and initialise the model for applications in France. We evaluate the spatio-temporal variability of the simulated building energy consumption for the city of Toulouse. We show that a more detailed description of building use and human behaviour enhances the simulation results. The model developments lay the groundwork for simulations of coupled urban climate and building energy consumption which are relevant for both the urban climate and the climate change mitigation and adaptation communities.

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“…The initial family of models integrated with No-MASS includes models of occupants' activities (Jaboob, 2015), presence and corresponding metabolic heat gains (Page et al, 2008), window interactions (Haldi and Robinson, 2009), shading interactions (Haldi and Robinson, 2010) and lighting interactions (Reinhart, 2004 The outputs from all models are then parsed back to EnergyPlus, which resolves the energy consequences of these interactions when simulating the building's energy flows during the next time step, so that there is no within timestep iteration. This process continues until the end of the simulation period.…”

Section: Alpha Versionmentioning

confidence: 99%

“…The algorithm also predicts blind usage, but this is based on a deterministic solar threshold irradiance of 50W/m 2 . Haldi and Robinson developed two occupant interaction models, one for windows (Haldi and Robinson, 2009) and one for external shading devices (Haldi and Robinson, 2010). The shading model uses a hybrid of Markov chains to predict if they are lowered or raised and a Weibull distribution to predict the opening fraction at arrival or departure.…”

Section: Stochastic Interactions Of Occupantsmentioning

confidence: 99%

See 1 more Smart Citation

On the multi-agent stochastic simulation of occupants in buildings

Chapman

Siebers

Robinson

2018

Journal of Building Performance Simulation

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One of the principle causes for deviations between predicted and simulated performance of buildings relates to the stochastic nature of their occupants: their presence, activities whilst present, activity dependent behaviours and the consequent implications for their perceived comfort. A growing research community is active in the development and validation of stochastic models addressing these issues; and considerable progress has been made. Specifically models in the areas of presence, activities while present, shading devices, window openings and lighting usage.One key outstanding challenge relates to the integration of these prototype models with building simulation in a coherent and generalizable way; meaning that emerging models can be integrated with a range of building simulation software. This thesis describes our proof of concept platform that integrates stochastic occupancy models within a multi agent simulation platform, which communicates directly with building simulation software. The tool is called Nottingham Multi-Agent Stochastic Simulation (No-MASS).No-MASS is tested with a building performance simulation solver to demonstrate the effectiveness of the integrated stochastic models on a residential building and a non-residential building. To account for diversity between occupants No-MASS makes use of archetypical behaviours within the stochastic models of windows, shades and activities. Thus providing designers with means to evaluate the performance of their designs in response to the range of expected behaviours and to evaluate the robustness of their design solutions; which is not possible using current simplistic deterministic representations. No-MASS employs agent machine learning techniques that allow them to learn how to respond to the processes taking place within a building and agents can choose a strategy without the need for context specific rules.Employing these complementary techniques to support the comprehensive simulation of occupants presence and behaviour, integrated within a single platform that can readily interface with a range of building (and urban) energy simulation programs is the key contribution to knowledge from this thesis. Nevertheless, there is significant scope to extend this work to further reduce the performance gap between simulated and real world buildings.

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Adaptive actions on shading devices in response to local visual stimuli

Cited by 182 publications

References 11 publications

Predicting the Daylit Area—A Comparison of Students Assessments and Simulations at Eleven Schools of Architecture

Predicting the Daylit Area—A Comparison of Students Assessments and Simulations at Eleven Schools of Architecture

Parametrisation of the variety of human behaviour related to building energy consumption in the Town Energy Balance (SURFEX-TEB v. 8.2)

On the multi-agent stochastic simulation of occupants in buildings

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