Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 5th July 2022, 15:03:26 CEST

 
Only Sessions at Location/Venue 
 
 
Session Overview
Location: Concert Hall - Kamermuziekzaal
't Zand 34, Bruges
Date: Wednesday, 01/Sept/2021
10:30 - 12:00Session W1.5: The role of occupants
Location: Concert Hall - Kamermuziekzaal
Session Chair: Fabian Ochs, University of Innsbruck
Session Chair: Valentin Gavan, ENGIE Lab CRIGEN
 
10:30 - 10:48

Influence of the hydronic loop configuration on the energy performance of a CO2 heat pump for domestic hot water production in a multi-family building

Matteo Dongellini, Claudia Naldi, Gian Luca Morini

Department of Industrial Engineering, University of Bologna, Italy

Aim and Approach

(max 200 words)

Nowadays the impact of domestic hot water (DHW) production on the overall energy consumption of a building is significantly increasing. In fact, a strong effort has been made to improve the building envelope insulation properties and the efficiency of HVAC systems for space heating and cooling, while, on the contrary, a lower attention has been focused on the reduction of the energy need related to DHW preparation. Although it accounts for about the 19% of the total energy demand of European Union residential sector [1], this percentage is expected to increase up to 50% in the next years [2]. CO2 heat pumps are promising solutions to achieve significant energy savings for DHW production; furthermore, CO2 is characterized by a low GWP value, is economic and environmentally sustainable [3]. In this paper the annual energy performance of a centralized plant for DHW production in a multi-family building located in Bologna (Italy) and based on an air-to-water CO2 transcritical heat pump has been assessed by means of TRNSYS and compared with the results of a monitoring campaign performed for three months during the winter season of 2017-2018.

Scientific Innovation and Relevance

(max 200 words)

The multi-family residential building considered in this work is composed by 7 stories and 27 flats, for a total useful surface of about 3850 square meters. A particular effort has been made to determine the hot water tap profile of the whole building: the method presented in Reference [4] has been used and adapted to the selected application. A hourly draw-off profile which takes into account the contemporaneity factor of the hot water request among all the apartments has been defined for both workdays and weekends. Moreover, the dynamic model of the CO2 heat pump has been developed with the cooperation of the heat pump manufacturer, who provided the performance data of the unit and its control logic. In order to decrease the temperature of the fresh water entering the heat pump, two water storages are connected in series with the unit. This work allows to evaluate the influence of the hydronic loop configuration on the energy performance of a CO2 heat pump: dynamic simulations evidenced that the configuration initially adopted for the DHW distribution was not able to exploit the maximum energy saving potential of this kind of heat pump units.

Preliminary Results and Conclusions

(max 200 words)

The comparison between experimental and numerical results showed that the CO2 heat pump effective energy performance were much lower than that expected if the heat pump had been conducted in an optimal way. More in detail, the measured average heat pump performance factor (SPF) during the monitored period was 1.66, while, on the other hand, the unit energy performance calculated with dynamic simulations for the same interval could reach values close to 4.70. The analysis pointed out that this strong reduction of the heat pump performance was caused by the configuration of the DHW loop: with the adopted solution, thermal stratification within the storage was not obtained and the temperature of the water at the inlet of the heat pump was very high. For this reason, the unit efficiency dramatically decreases. Experimental data confirms this hypothesis: the temperature of the water stream entering the heat pump was around 40°C, almost 25 K higher than fresh water temperature introduced in the thermal storage vessel from the aqueduct. The results obtained in this work highlight how the energy performance of CO2 heat pumps is significantly influenced by the configuration of the DHW loop and especially by the layout of the thermal storages.

Main References

(max 200 words)

[1] T. Kitzberger, D. Kilian, J Cotik, T. Proll, Comprehensive analysis of the performance and intrinsic energy losses of centralized Domestic hot Water (DHW) systems in commercial (educational) buildings, Energy and Buildings 195 (2019), 126-138.

[2] A. Bertrand, A. Mastrucci, N. Schuler, R. Aggoune, F. Maréchal. Characterisation of domestic hot water end-uses for integrated urban thermal energy assessment and optimization, Applied Energy 186 (2017), 152-166.

[3] k. Visser, Transcritical CO2 refrigeration systems for building cooling and heating reduce energy and cooling water consumption, emissions and the legionella danger, Proceedings of the 8th International Conference on Advances in Applied Science and Environmental Engineering (ASEE 2018), 3-4 February 2018, Kuala Lumpur, Malaysia.

[4] K. Ahmed, P. Pylsy, J. Kurnitski, Hourly Consumption profiles of domestic hot water for different occupant groups in dwellings, Solar Energy 137 (2016), 516-530.



10:48 - 11:06

Methods for determining occupant behavioural models for energy-efficient retrofitting of 20th-century buildings

Antonella Mastrorilli1, Roberta Zarcone2, Chenafi Sabrina1, Colonneau Téva1

1Laboratoire LACTH, Ecole Nationale Supérieure d’Architecture et de Paysage de Lille, 2 Rue Verte, 59650 Villeneuve-d'Ascq, France; 2Laboratoire GSA, Ecole Nationale Supérieure d’Architecture Paris-Malaquais, 14 rue Bonaparte, 75006 Paris

Aim and Approach

(max 200 words)

A study carried out within the project "Rethinking innovation. Know and manage the legacies of experiment and innovative social housing from the decade 1968-78” funded by the French Ministry of Cultural, is presented in this paper. The objective of this research is to highlight the influence of the variable occupancy in an energy renovation scenario.

We present the methodology developed for the construction of a "detailed" inhabitant profile on a case study of the social housing “Residence Salamandre” in Villeneuve d'Ascq.

By using an interoperable work, we produced a digital model informed by BIM methods, combining the sharing of information tasks of existing construction and site conditions.

From the typo-morphological analysis of the housing modules, a phase of data collection on the lifestyles of different occupants of the residence was developed. The balance sheet of energy consumed by year (provide by inhabitants) and anonymous surveys made it possible to link the aspect of daily consumption to the question of lifestyles.

In this paper, we present the impact of internal contributions on energy performance by comparing the results with those resulting from the application of usage scenarios in accordance with the French RT2012 standard.

Scientific Innovation and Relevance

(max 200 words)

Today, the influence of occupants’ behaviour is oversimplified during the analysis phases prior to energy renovation operations.

Amongst other variables, the lifestyles of the occupants remains one of the most difficult to control. However, it seems to play a decisive role because it represents one of the main factors of discrepancy between the phases of energy renovation and the actual functioning of a building.

Assessing energy needs and performance of existing buildings therefore, requires calculation tools able to produce results that are closest to reality. However, the different energy simulation softwares show many disparities which often leads to different results. In addition, the application of thermal regulations requires the use of referenced conventional calculation methods (DPE, TH BCE Method), certifying a level of energy performance to reach, by combining the analysis of "real" data with those of predetermined data, from hypothetical use scenarios.

This research attempted to develop dynamic energy simulation methods, offering the most realistic representation of energy needs in use conditions. We have defined a "fine" analysis methodology which allowed to take into account the variable of occupancy in housing. This will make us quantify its impact on energy needs and prefigure the most appropriate energy intervention.

Preliminary Results and Conclusions

(max 200 words)

According to the simulations carried out through numerical modelling and the characterisation of a "detailed" user profile - for a family of three people - the first results obtained have demonstrated the impact of Inhabitants users in the calculation of consumption needs.

In fact, in the case of the “detailed” user profile, the internal contributions cover a total of 40% of the home's heating needs, i.e. 10% more than the results obtained considering the conventional profile from the French standard RT2012.

The results then highlighted a striking observation: Through dynamic energy building simulation, the occupancy variable in “detailed” user profile shows more efficient alternative than the intervention in external over-insulation of the Salamandre residence, with a strong aesthetic and constructive impact as a whole. Resorting to a "fine" analysis on a case-by-case basis - provide by actual measurements of occupancy variables in the dwelling - might then be more appropriate, in order to preserve the original aesthic and material qualities of building heritage objects.

Therefore, the conceptual and technical results obtained in this research aim to generalize this analysis methodology prior to each energy renovation project for existing buildings.

Main References

(max 200 words)

Fabi V, Andersen RV, Corgnati SP, Olesen BW. A methodology for modelling energy-related human behaviour: application to window opening behaviour in residential buildings. Build Simul 2013 6:415

Andersen RV, Toftum J, Andersen KK, Olesen BW (2009), “Survey of occupant behaviour and control of indoor environment”, Danish dwellings. Energy and Buildings, 41: 11–16

Andersen RV (2012), “The influence of occupants’ behaviour on energy consumption investigated in 290 identical dwellings and in 35 apartments”, Proceedings of Healthy Buildings 2012, Brisbane, Australia.

Brundrett GW (1997), “Ventilation: A behavioural approach”, International Journal of Energy Research, 1: 289–298. Emery AF, Kippenhan CJ (2006), “A long term of residential home heating consumption and the effect of occupant behavior on homes in the Pacific Northwest constructed according to improved thermal standards”, Energy, 31: 677-693.

Geslin F., Le bâti ancien appelle des solutions non standardisées, Les cahiers techniques du bâtiment, (https://www.cahiers-techniques-batiment. fr/article/le-bati-ancien-appelle-des-solutions-non standardisees.32324, consulté le 28/03/2017).

Nicol JF, Humphreys MA (2004), “A stochastic approach to thermal comfort-occupant behaviour and energy use in buildings”, ASHRAE Transactions, 110(2): 554–68.



11:06 - 11:24

Human in the Loop: perceived based control as the key to enhance buildings’ performance

Davide Calì, Christian Ankerstjerne Thilker, Sebastian Arcos Specht, Jaume Palmer Real, Henrik Madsen, Bjarne W. Olesen

DTU, Denmark

Aim and Approach

(max 200 words)

The performance gap of existing and new buildings [1], both in terms of energy and occupants’ comfort, jeopardizes the effort to reach deep decarbonization target. One of the main issues causing high CO2 emissions of buildings is related to VOLATILITY. Buildings are mostly planned and controlled based on assumptions and fixed schedules which might were valid in the Sixties. However, our society evolved: For example, residential buildings where family lives are often empty during the day while both parents go to work and children stay until afternoon at schools; in parallel, work-from-home became reality, also several times a week. Moreover, not only the demand for comfort is volatile: to minimize buildings’ impact on climate change, we have to maximize the use of renewable energy sources. As a consequence, the production of energy is non-projectable. Matching the volatile usage of buildings with intermittent energy production can help both enhancing personal comfort and reducing CO2 emissions caused by the existing building stock. In this work, we propose a Human-in-the-Loop approach, where occupants are traced within a building, and, when they desire it, can provide feedback about their perceived comfort in specific rooms: this feedback is then used to control the building.

Scientific Innovation and Relevance

(max 200 words)

The provision of flexibility services to the energy grids became more popular in the last decade. However, too often flexibility projects have a strong focus on the quality of the services provided to the grid, and do not actively consider real occupants needs. Eventually, flexibility services are connected to a deficit of indoor comfort (e.g. accepting lower indoor temperature or lower air change per hour). Through the use of our tracing and feedback app “FEEDME” and a network of IoT sensors connected to our vendor-neutral monitoring platform CLIMIFY [2], we gather information regarding the number of occupants within a room, their live feedback on the indoor climate, and their past preferences at given indoor conditions. This information can be used to:

1. Simplify the way buildings are controlled: instead of asking the occupants to choose set points, we ask how she/he feels, and control the building accordingly

2. Take into account the diversity of occupants’ needs, and also the way those needs change during the day in the control of buildings - Mediate among different needs in a democratic way;

3. Optimize energy use, CO2 emissions and indoor climate in buildings through model predictive control and AI.

Preliminary Results and Conclusions

(max 200 words)

FEEDME and CLIMIFY are currently being tested in a school with 13 classrooms, located in Denmark (a second demonstration office building is under arrangement). In the school, we gathered the feedback of occupants on their perceived thermal comfort (using a 5-steps scale) for a period of 6 weeks. In a first 3-week period, the set-point of smart thermostats was for all classrooms set to 22°C: 51% of the occupants were fully satisfied with the indoor climate, while over 10% were completely dissatisfied. In the second 3-week period, the set points of each classroom were manually adjusted accordingly to the received feedback of the previous 3 weeks. As a result, over 63% of occupants were fully satisfied, only 6% was fully unsatisfied [5]. In this first experiment, we only adjusted the set-point once, and accordingly to the location were the feedback was given only. A real time optimization, considering the exact occupants in each classroom and adjusting also other set-points, such as ventilation and blinds, could further enhance occupants experience in buildings. FEEDME keeps the occupants in the middle of the control loop but minimizes human errors. Moreover, the indoor climate enhancement is reflected into higher productivity [4, 5].

Main References

(max 200 words)

[1] D Calì, T Osterhage, R Streblow, D Müller, Energy performance gap in refurbished German dwellings: Lesson learned from a field test - Energy and buildings, 127 (2016), 1146-1158. https://doi.org/10.1016/j.enbuild.2016.05.020

[2] Calì, D., Kindler, E., Ebrahimy, R., Bacher, P., Hu, K. S., Østrup, M. L., Bachalarz, M., & Madsen, H. (2019). climify.org: an online solution for easy control and monitoring of the indoor environment. E3S Web of Conferences, 111. https://doi.org/10.1051/e3sconf/201911105006

[3] D. Calì, Results of data analysis and optimization algorithms - Technical Report, DTU, 2020.

[4] P. Wargocki, J.A. Porras-Salazar, S. Contreras-Espinoza, The relationship between classroom temperature and children’s performance in school, Build. Environ. 157 (2019) 197–204. https://doi:10.1016/j.buildenv.2019.04.046

[5] P. Wargocki, J.A. Porras-Salazar, S. Contreras-Espinoza, W. Bahnfleth, The relationships between classroom air quality and children’s performance in school, Build. Environ. 173 (2020). https://doi:10.1016/j.buildenv.2020.106749



11:24 - 11:42

A simulation workflow for exposure characterisation of daylit spaces based on occupant gaze orientation

Mandana Sarey Khanie1, Mikkel Kofod Pedersen1, Trine Illum1, Rasmus Nielsen1, Thorbjøn Asmussen2

1Technical University of Denamrk, Denmark; 2VELUX A/S, Hoersholm, Denmark

Aim and Approach

(max 200 words)

This paper represents a simulation workflow for characterization of spectral exposure depending on occupants’ position and gaze behavior in buildings. The project uses existing gaze movement database as well as occupant-tracking data obtained in a pilot study for its development. The existing database has been obtained at a daylight lab at Freiburg, Germany, in a user-assessment study where eye-tracking systems were used to record visual responses to the luminous environment [1]. The pilot study was done over a period of 2 months where occupants’ orientations were tracked using an image-based sensors recoding dwells and movements of occupant. The dwell and track data from the pilot study were used to define exposure ranges to spectral effectiveness of the space. Using the two databases , a Grasshopper3D tool was developed to demonstrate gaze behavior[1], [2], exposure to illumination levels, and the exposure to spectral lighting, thus allows for exposure characterization of the space at the eye level at each given position. The latter was processed using Lark Spectral Lighting tool [3] to account for photopic, Rea[4] and Lucas [5]circadian illuminance. Using the tool, a simulation study was done and the results as well as the work flow are presented here.

Scientific Innovation and Relevance

(max 200 words)

Despite different existing wavelength-dependent models to predict spectral-effectiveness of light[6], [7], these methods can only predict the health potentials in a space with assumption of static building occupants on fixed pre-defined points[8]. With great benefits on our well-being [9], [10], an exposure characterization of space for daylight, based on dynamic occupant behavior is a step forward. This step allows for better understanding occupant well-being indoors based on actual occupant’s position and orientation. The dynamic human behavior to light exposure has been addressed in fewer studies where photometric measurements and eye-tracking methods were coupled for observations of gaze or eye responses to light [1], [11]. Building up on these exiting methodologies, here the occupant light-driven behavior is used to predict the exposure to spectral lighting and illumination levels in space. In addition, data gathered by the sensors are processed to show the actual exposure levels in real time. The developed tool and processing method can be used in design phases to introduce interventions, e.g. change of interior layout, for optimal lighting solutions.

Preliminary Results and Conclusions

(max 200 words)

The simulation study provided a clear demonstration of visual patterns and exposure patterns at different points in space based on the dynamic occupant behavior. The health potential of the selected dominant gaze orientation was evaluated at each position. From the Lark tool [6], the values had to be converted as the selected threshold values used the units Circadian Stimulus (CS) and Equivalent Melanopic Lux (EML). The threshold value CS explained the optimal stimulus throughout the working day, where specific values are given for each hour, while the threshold value EML gave a fixed value over all hours. While most positions in the models showed satisfactory during summer time and under sunny conditions, only fewer positions would reach the thresholds under overcasts skies. Hence, optimized use of such areas in certain climatic regions proves to be essential. Moreover, as in north façade and lack of visual discomfort allows for orienting towards windows, higher health potentials can be achieved. It can therefore be concluded that the orientation in space is crucial for the vertical illuminance measured at the eye, but it is still important that the visual comfort is maintained.

Main References

(max 200 words)

1. Sarey Khanie, M., et.al. Gaze and discomfort glare, Part 1: Development of a gaze-driven photometry. Light. Res. Technol. (2016)

2.Sarey Khanie, M. et al. A Gaze Visualizer tool for Grasshopper3d. in SimBuild – USA, (2018)

3. Inanici, M., et.al. Spectral daylighting simulations, Department of Architecture, Seattle, USA

4. Rea, M. The lumen seen in a new light, Light. Res. Technol. 47, (2015)

5.Lucas, R. et al. Measuring and using light in the melanopsin age. Trends in Neurosciences (2014).

6.Amundadottir,M. et.al. Unified framework to evaluate non-visual spectral effectiveness of light for human health. Light. Res. Technol. 49, (2017)

7. Rea, M., et.al. A new approach to understanding the impact of circadian disruption on human health. J Circadian Rhythm. 6, (2008)

8.Amundadottir, M. et.al. A human-centric approach to assess daylight in buildings for non-visual health potential, visual interest and gaze behavior. Build. Environ. 113, (2017)

9. Lockley, S. Circadian Rhythms: Influence of Light in Humans. Encycl. Neurosci. 2, (2009)

10.Birchler-Pedross, A. et al. Subjective Well-Being Is Modulated by Circadian Phase, Sleep Pressure, Age, and Gender. J. Biol. Rhythms 24, (2009)

11.Lin, Y. et al. Eye movement and pupil size constriction under discomfort glare. Invest. Ophthalmol. Vis. Sci. 56, (2015)



11:42 - 12:00

Quantifying household specific self-consumption of photovoltaic-based power generation in energy efficient buildings – a comprehensive parametric study to increase the reliability of energy consulting

André Müller1,2, Johannes Koert2, Patrick Wörner2

1Institute for Housing and Environment, Germany; 2Institute of Concrete and Masonry Structures, Technische Universität Darmstadt, Germany

Aim and Approach

(max 200 words)

The energy consumption from private households is responsible for a substantial share of the total greenhouse gas emissions in Germany. For this reason, German legislation promotes the climate-neutral operation of buildings until 2050. Consequently, building related power generation from renewable energies can be considered in the calculation of energy performance according to the German Energy Saving Ordinance (EnEV). However, the EnEV calculation rules allow neither for a proper estimation of the amount of renewable energy generated locally from PV nor for the estimation of private electricity consumption. Thus, the assessments of PV systems to be installed on buildings lack reliability and highly depend on the modelling skills of the energy consultant. To overcome this barrier for the implementation of building-related PV an easy applicable matrix of energy generation and private consumption for different locations as well as types of buildings and households is developed. This is achieved by feeding IDA ICE building simulation models with profiles generated by the user behaviour model ‘PeakTime’. Typical user behaviour of certain household types is translated to annual power consumption profiles, added to the load profiles of building archetypes and compared to the electrical power generation profiles from a PV system.

Scientific Innovation and Relevance

(max 200 words)

A variety of studies already exist on the self-consumption of power production from building related PV systems. However, most of these narrowed research down to a single or respectively a few real or typical households’ electricity consumption. Thus, the results allow for a plausible estimation of self-consumption, but not for a detailed prognosis and quantification as the source of reliable energy consulting. The basis of the presented investigation on household-type specific PV self-consumption is a recently developed stochastic user behaviour model, which allows the generation of load profiles for power consumption of various household configurations. Thereby, household specific circumstances, e.g. the co-use of electrical appliances by two or more household members, and their effect on households’ load profiles are reflected. The relevance arises from the fact that, besides calculated standard load profiles for household types, a distribution of self-consumption from PV systems emerges. To allow for a proper comparison of available technologies and energy performance levels, the household load profiles are processed in a parametric study within the building simulation software IDA ICE. The results of these simulations are categorized and summarized to achieve applicability in the context of energy consulting and allow for more profound decisions of building owners.

Preliminary Results and Conclusions

(max 200 words)

The preliminary results illustrate the fact, that power consumption of household types differ dependent on the status of employment household members and the presence of kids, respectively. At the same time, the amount of self-consumption from PV generated power is highly correlated to the user behaviours underlying the household types. While energy performance calculations according to German EnEV calculation rules cannot reflect these variations, the performed parametric study gives reliable values for self-consumption in general as well as ratios of solar coverage of the use cases heating and cooling, hot water demand as well as other electrical appliances of a household. Thereby, the preliminary results build on a reduced number of available household types and represent an intermediate step on the way of making available realistic user behaviour data for energy performance calculations as well as dynamic building simulations.

Main References

(max 200 words)

Yan, Da ; Hong, Tianzhen; Dong, Bing; Mahdavid, Ardeshir; D’Oca, Simona; Gaetanie, Isabella; Fenga, Xiaohang (2017): IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings. Energy and Buildings, Volume 156, Pages 258-270.

Wörner, Patrick (in Press): Einfluss des Nutzerverhaltens auf den Stromverbrauch in Wohngebäuden ‐ Entwicklung eines komplexen Simulationsmodells für energetische Analysen. Dissertation. Institute of Concrete and Masonry Structures, Technische Universität Darmstadt. Graubner, Carl-Alexander (Ed.)

Loga, Tobias; Frank, Milena (2016): Photovoltaic power generation to cover domestic power demand in Passive House: A parameter study. 20th International Passive House Conference 2016: 22th – 23th April 2016, Darmstadt: Proceedings / Passive House Institute. Feist, Wolfgang (Ed.)

https://www.iwu.de/fileadmin/user_upload/dateien/energie/neh_ph/2016_passivhaustagung_LogaFrank_PVEigendeckungImPassivhaus.pdf (German version; English version is available to the author as print version only; last access: 31.07.2020)

Gaetani, Isabella; Hoes, Pieter-Jan; Hensen, Jan L.M. (2018): Estimating the influence of occupant behavior on building heating and cooling energy in one simulation run. Applied Energy, Volume 223, Pages 159-171.

BMUB (2016): Climate Action Plan 2050 – Principles and goals of the German government’s climate policy. Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (Ed.).

https://www.bmu.de/en/publication/climate-action-plan-2050/ (Last access: 31.07.2020)

 
13:00 - 14:30Session W2.6: The role of occupants
Location: Concert Hall - Kamermuziekzaal
Session Chair: Andrea Gasparella, Free University of Bozen - Bolzano
Session Chair: Damien Picard, KU Leuven
 
13:00 - 13:18

Mapping the gap in user-related building performance simulation models

Ardeshir Mahdavi, Veselina Bochukova, Christiane Berger

TU Wien, Austria

Aim and Approach

(max 200 words)

Recently, increasing attention is being paid in the building performance simulation research community to the quality and resolution of representations of building users in simulation models (Mahdavi and Tahmasebi 2019). This is reflected in a host of publications and projects with highly diverse starting points, approaches, and results (Yan et al. 2017, Berger and Mahdavi 2020). Whereas such diversity can be productive and fruitful, it may also involve redundancy and lack of strategic orientation. In this context, it is beneficial to reexamine this subject from two complementary directions. One ontological direction, characterized here as "top-down", pursues the required format and dimensions of a generalized representation of building users that could be distilled down as needed to cater for the informational requirements of specific applications. The second direction, which can be seen as "bottom-up", starts by reverse-engineering the occupant-specific input templates of common performance simulations in view of any existing shared features and structure. We suggest that the pursuit of these two directions reveals a discontinuity or gap, indicating that there is not yet a seamless path leading from occupant-centric ontologies to occupant-related model input requirements of common performance simulation tools.

Scientific Innovation and Relevance

(max 200 words)

The building information modeling research and development community has become increasingly cognizant of the following circumstance: To be truly effective, building information models must go beyond the static representation of buildings' constituent physical components (Mahdavi 2020). Rather, the time-dependent dynamics of processes associated with the design, construction, and operation of buildings must be taken into consideration. A major class of such processes involve the patterns of occupants' presence and behavior in buildings. A comprehensive solution for the respective representational challenges must go beyond ad hoc amendments to existing simulation input routines. Toward this end, a seamless transition from a comprehensive ontology of building users down to specific input schema tailored for individual simulation application would be desirable, but currently hampered to a representational discontinuity. The aforementioned concurrent top-down and bottom-up inquiries can help map this gap and hence suggest approaches to close it.

Preliminary Results and Conclusions

(max 200 words)

The work thus far has led to the definition of a general schema that captures the main dimensions of occupant-related information. These include physical data pertaining to position and movement, physiological data pertaining to state of metabolism and adaptation, cognitive data pertaining to formation of impressions and value attributions, as well as event-based data pertaining to human-building interaction processes. The result suggests that, in order to consistently structure the schema, underlying foundational theories are needed that capture building users' relevant patterns of presence and behavior. Moreover, the bottom-up reverse-engineering of existing simulation applications reveals the potential and challenges toward seamless derivation of locally tailored input information from ontologically structured sources of occupant-related information.

Main References

(max 200 words)

Berger, C., and Mahdavi, A. (2020): Review of current trends in agent-based modeling of building occupants for energy and indoor-environmental performance analysis. Building and Environment, 173; 106726.

Mahdavi, A., and Tahmasebi, F. (2019): People in building performance simulation. Building Performance Simulation for Design and Operation - Expanded Second Edition. Hensen, J., Lamberts, R. (Ed.); Routledge, New York, ISBN: 978-1-138-39219-9; pp. 117 - 145.

Mahdavi, A. (2020): Bringing HIM closer to HER. Keynote. Proceedings of SIMAUD: Symposium on Simulation for Architecture and Urban Design. Vienna (Online), 25-26 May 2020. ISBN: 978-1565553712.

Yan, D., Hong, T., Dong, B., Mahdavi, A., D´Oca, S., Gaetani, I., and Feng, X. (2017): IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings. Energy and Buildings, 156; pp. 258 - 270.



13:18 - 13:36

The impact of occupancy prediction accuracy on the performance of model predictive control (MPC) in buildings

Tao Yang, Fisayo Caleb Sangogboye, Krzysztof Arendt, Konstantin Filonenko, Jonathan Dallaire, Mikkel Baun Kjærgaard, Christian Veje

Center for Energy Informatics, University of Southern Denmark, Denmark

Aim and Approach

(max 200 words)

This paper aims to investigate the impact of occupancy accuracy on the performance of MPC-based building control. As an experimental setup, a grey-box model representing the heating, ventilation, and air conditioning (HVAC) system in a case study building is developed and calibrated. Subsequently, a number of 3D stereo-vision cameras is deployed to obtain accurate occupancy counts. Based on the obtained measurements, a data-driven model for predicting occupancy count in simulation is developed. In the evaluation, two MPC-based building controllers with different occupancy accuracy are compared based on multiple shooting optimization algorithm. The first of the compared models uses occupancy estimates from the deployed camera, while the second uses occupancy prediction from the data-driven model. The two MPC-based building controllers are further compared with a conventional rule-based controller in terms of energy consumption and indoor thermal discomfort.

Scientific Innovation and Relevance

(max 200 words)

Globally, buildings are responsible for nearly 40% of total energy consumption among other sectors [1]. MPC is a promising and widely investigated strategy employed in buildings to reduce energy consumption while maintaining thermal comfort. While there exists a wide range of parameters for MPC-based building controls, the accurate estimation of occupancy in buildings constitute a major factor for achieving considerable ambient comfort and energy saving within buildings [2-5]. This paper goes beyond simple analysis of the occupant presence and applies a data-driven approach to accurately predict occupant count and subsequently studies the impact of occupancy accuracy on MPC performance, which contributes to better analyze relationship between occupancy information and MPC performance in buildings.

Preliminary Results and Conclusions

(max 200 words)

The developed grey-box model yields good accuracy of capturing thermal dynamics of the system. Using occupancy estimates from the deployed cameras, an MPC-based controller in contrast to a rule-based controller demonstrates better indoor thermal comfort and higher energy consumption due to that MPC prioritizes thermal comfort (hard constraint) over energy. Comparing MPC with two different occupancy accuracy, occupancy predictions with low accuracy can lead to lower energy consumption at the expense of thermal comfort violations. When increasing optimization horizon, MPC-based controller with more accurate occupancy prediction shows larger energy consumption and improved thermal comfort. Besides, the negative influence of prediction error can be partially mitigated by adopting longer optimization horizons.

Main References

(max 200 words)

[1] Cao, Xiaodong, Xilei Dai, and Junjie Liu. "Building energy-consumption status worldwide and the state-of-the-art technologies for zero-energy buildings during the past decade." Energy and buildings 128 (2016): 198-213.

[2] Amin Mirakhorli and Bing Dong. Occupancy behavior-based model predictive control for building indoor climate - a critical review. Energy and Buildings, 129: 499–513, 2016.

[3] Justin R Dobbs and Brandon M Hencey. Model predictive hvac control with online occupancy model. Energy and Buildings, 82: 675–684, 2014.

[4] Frauke Oldewurtel, David Sturzenegger, and Manfred Morari. Importance of occupancy information for building climate control. Applied energy, 101: 521–532, 2013.

[5] Siddharth Goyal, Herbert A Ingley, and Prabir Barooah. Occupancy-based zone climate control for energy-efficient buildings: Complexity vs. performance. Applied Energy, 106: 209–221, 2013.

[6] K. Arendt and C. Veje, “MShoot: an Open Source Framework for Multiple Shooting MPC in Buildings,” in 16th IBPSA International Conference and Exhibition Building Simulation 2019, Rome, 2-4 September, 2019, 2019.

[7] Antoine Garnier, Julien Eynard, Matthieu Caussanel, and Stéphane Grieu. Predictive control of multizone heating, ventilation and air-conditioning systems in non-residential buildings. Applied Soft Computing, 37: 847–862, 2015.



13:36 - 13:54

Consequences-based graphical model for contextualized occupants’ activities estimation in connected buildings

Huynh Phan1, Thomas Recht1, Laurent Mora1, Stéphane Ploix2

1I2M Bordeaux, University of Bordeaux, CNRS, Arts et Metiers Institute of Technology, Bordeaux INP, F-33400 Talence, France; 2G-SCOP, Grenoble Institute of Technology, UMR CNRS 5272, 46 Avenue Felix Viallet, 38031 Grenoble Cedex 1, France

Aim and Approach

(max 200 words)

Occupants' activities are addressed as important factors resulting in the discrepancy between simulated and actual energy consumptions in residential buildings. Many models with statistical data are proposed to better estimate the activities of occupants than conventional approaches. However, these models are hybrid of the statistical data, which contains the information of many dwellings with different habits and characteristics, and not entirely sufficient to represent contextualized activities in a particular household. To solve this problem, data-driven approaches with machine learning techniques are proposed to estimate the activities based on the data measured from on-site sensors. However, they are black-box approaches and difficult to understand. It is preferable to propose an understandable model, which is able to estimate and evaluate the contextualized activities in a particular household. In this contribution, a general approach model taking into account a particular context is proposed to estimate and predict the occupants’ activities in a specific household. Specifically, many sensors (CO2, temperature, motions, etc.) are installed to capture the data in the household. Then, combining with the context information, the necessary features are extracted from measured data and are used to build a consequences-based Bayesian Network, which is understandable, and flexible for the contextualized activities estimation.

Scientific Innovation and Relevance

(max 200 words)

Recently, statistical approach is the most popular approach for occupants’ activities estimation in buildings. [1,6] used statistical models to estimate the activities using the characteristics of both buildings and households. Though, their models are hybrid of statistical data of different dwellings and not sufficient to estimate and evaluate the contextualized activities in a particular household. To deal with it, [2,7] applied data-based models with machine learning techniques to estimate activities using the measurement data. However, they do not provide understandable outputs and are not adaptable to context’s changes. Otherwise, [3,4] proposed agent-based models to simulate the activities of windows/doors. An agent perceives the space’s conditions and executes activities to achieve its predefined comfort. However, agent-based models are too complex with many agents. Besides, [5] built Bayesian Network (BN) to estimate the activities of doors based on the measurement data and expert knowledge. BN is an understandable, easy adaptable model for activities estimation in a particular household. However, all studies focus on simple activities (actions of windows/door, presence, etc.) and the structure of the BN is difficult to define. This study proposes a BN with an expert structure for contextualized activities estimation from measurement data, in a specific household.

Preliminary Results and Conclusions

(max 200 words)

A general approach has been proposed in this contribution to estimate the daily activities in a residential building. Dynamic Time-Series Clustering and expert discretization techniques are used to extract features from variables while Information Gain is used for the necessary features selection. Consequences-based Bayesian Network is used as an estimation model based on an expert structure, which is determined by the consequences of the activities. Finally, cross-validation and F1-score are used to validate the proposed model in the testing data. The proposed model was used to estimate some activities such as cooking breakfast, cooking lunch, washing dishes, etc. The testbed is a detached house in France, which includes 5 household members and 11 rooms. The data was collected from numerous installed sensors of ambient, power, motion, windows/doors contacts, etc. The labels of activities were collected for two months by a self-developed mobile application. In this contribution, the activity cooking lunch in the kitchen is presented. Data set covers 45 weekdays from 09/12/2019 to 30/02/2020 (labels collection period). Results show that cooking lunch is mainly linked to the patterns of the usages of frequently involved appliances (microwave, toaster). Cross-validation is used and F1-score is approximately 91%.

Main References

(max 200 words)

1. Dorien Aerts. 2015. Occupancy and Activity Modelling for Building Energy Demand Simulations, Comparative Feedback and Residential Electricity Demand Characterisation. PhD Thesis, Vrije Universiteit Brussel.

2. Alaa Alhamoud, Pei Xu, Frank Englert, et al. 2015. Extracting Human Behavior Patterns from Appliance-level Power Consumption Data. Wireless Sensor Networks, Springer International Publishing, 52–67.

3. Yoon Soo Lee and Ali M. Malkawi. 2014. Simulating multiple occupant behaviors in buildings: An agent-based modeling approach. Energy and Buildings 69: 407–416.

4. Khadija Tijani, Ayesha Kashif, Stéphane Ploix, Benjamin Haas, and Julie Dugdale. 2015. Comparison between purely statistical and multi-agent based ap-proaches for occupant behaviour modeling in buildings. arXiv:1510.02225 [cs].

5. Khadija Tijani, Quoc Dung Ngo, Stéphane Ploix, Benjamin Haas, and Julie Dugdale. 2015. Towards a General Framework for an Observation and Knowledge based Model of Occupant Behaviour in Office Buildings. Energy Procedia 78: 609–614.

6. Urs Wilke. 2013. Probabilistic Bottom-up Modelling of Occupancy and Activities to Predict Electricity Demand in Residential Buildings. .

7. Suyang Zhou, Zhi Wu, Jianing Li, and Xiao-ping Zhang. 2014. Real-time Energy Control Approach for Smart Home Energy Management System. Electric Power Components and Systems 42, 3–4: 315–326.



13:54 - 14:12

Multi-Agent based simulation of human activity for building and urban scale assessment of residential load curves and energy use

Mathieu Schumann1,5, Quentin Reynaud2, Nicolas Sabouret3, François Sempé6, Benoit Charrier1,5, Jérémy Albouys1,3,4,5, Yvon Haradji1, Christian Inard4,5

1EDF R&D, Palaiseau, France; 2QRCI, Clermont-Ferrand, France; 3LIMSI-CNRS, Univ. Paris-Sud, Univ. Paris-Saclay, Orsay, France; 4LaSIE, CNRS, La Rochelle Université, La Rochelle, France; 54evLab, EDF R&D, CNRS, LaSIE, La Rochelle Université, La Rochelle, France; 6FSCI, Paris, France

Aim and Approach

(max 200 words)

Because of the crucial impact of human activity on energy consumption (Janda, 2011), many building and urban energy models integrate human activity modeling. An increasing number of research works use Time Use Surveys (Chenu et al, 2006) and stochastic person-based approaches to generate occupancy profiles, window uses, or activity chronograms (Baetens et al, 2016). The goal of this paper is twofold: 1/ to discuss the limits of the existing state-of-the-art approaches on human activity modeling, and 2/ to present our modeling approach: an agent-based, individual-centered simulation of human activity, taking individual decisions and interactions between individuals into account to produce activity diagrams that are consistent at the household scale. Associated with a population generator, and by linking the simulated activity with appliance use, one of the main applications is the calculation of residential households load curves.

Our work puts the simulation of human activity and everyday life decision-making processes at the center of energy consumption, thermal comfort or indoor air quality assessments in households. This approach has its roots in ergonomics studies, which demonstrated the ability of multi-agent systems to simulate a realistic human activity, using innovative validation methodologies such as participatory simulations with real households (Haradji et al, 2012).

Scientific Innovation and Relevance

(max 200 words)

The analyzed approaches appear to be insufficient to account for the dynamics of individual and collective activity and its impact on energy consumption (Happle, 2018), particularly as households and energy communities become more actively integrated in smart grids and involved in flexibility, collective self-consumption or energy exchange schemes. Such configurations involve individual and collective decision-making, as well as the management of new appliances such as electric vehicles.

We suggest that the co-simulation of autonomous agents, whose activities are built upon statistical data (e.g. Time Use Surveys), with building and appliance models (Plessis, 2014) can effectively tackle these new challenges. We propose a fine-grained, 1 minute time step household simulation, able to perform population-wide yearly simulations. Our agent-based model can reach a satisfying level of diversity in human activities, and it supports interactions between autonomous agents and a changing environment (e.g. activity priorities, incentives, energy prices). This model accounts for emerging, reactive, adaptive, and collective behaviors. Moreover, it allows to deal with many human behavioral aspects (e.g. presence, heating adjustment, housing ventilation) within the same decisional process, bringing consistency to the role of occupant in energy assessments.

Preliminary Results and Conclusions

(max 200 words)

We present the agent-based SMACH platform (SiMulation of human Activity and Consumption in Households) (Haradji et al, 2018). We show how the modeling of occupants as intelligent autonomous agents accounts for the individual and collective dynamics of daily life and the related energy consumption, modeled as the result of the interactions between agents and the household’s electrical appliances. We demonstrate how the latest developments of the SMACH simulation platform, combining population synthesis, simulation of individual and collective activities as well as electric mobility, answer some of the challenges related to the role of occupants in energy consumption (Happle, 2018). Especially, we show that multi-agent modeling offers a high degree of modularity due to the internal capabilities of the agents to organize themselves, plan their day, or react to events or changes in the environment. This approach is also explicit, and makes it possible to explain why, when, how and with whom the simulated energy consumption is performed. We illustrate the validation approaches and variety of uses of this model in energy questions and engineering applications such as load curve calculation, at an individual household scale as well as at the population scale.

Main References

(max 200 words)

Janda, Kathryn B. (2011). Buildings Don’t Use Energy: People Do. Architectural Science Review 54 (1): 15–22

Chenu, A. and Lesnard L. (2006) Time Use Surveys: A Review of Their Aims, Methods, and Results. European Journal of Sociology 47 (3): 335–59.

Baetens, R. and Dirk S. (2016). Modelling Uncertainty in District Energy Simulations by Stochastic Residential Occupant Behaviour. Journal of Building Performance Simulation 9 (4)

Haradji Y., Poizat G., Sempé F (2012) Human Activity and social simulation. Proceedings of the 4th Advances in Human Factors and Ergonomics Conference, San Francisco, California, USA

Plessis, G., Edouard A., Haradji, Y. (2014). Coupling Occupant Behaviour with a Building Energy Model - A FMI Application. 10th International Modelica Conference 96:321–26 Lund, Sweden

Haradji Y. et al, (2018) From modeling human activity to modeling for social simulation: between realism and technological innovation. Activités 15-1

Happle G., Fonseca J. A. and Schlueter A. (2018) A review on occupant behavior in urban building energy models. Energy and Buildings, vol. 174. Elsevier Ltd, pp. 276–292



14:12 - 14:30

The formulation of a reference load curve to measure energy flexibility

Muhammad Salman Shahid1, Benoît Delinchant1, Béatrice Roussillon2, Frédéric Wurtz1, Daniel Llerena2

1G2Elab, 21 Rue des Martyrs, CS 90624, 38031 Grenoble CEDEX 1, France; 2GAEL, 1241 Rue des Résidences, 38400 Saint-Martin-d'Hères, France

Aim and Approach

(max 200 words)

Energy consumers have a degree of choice to implement indirect energy flexibility to mitigate network congestion during the intermittence of renewable production. It is essential to measure the impact of each alert for each consumer. This abstract presents a study performed to compare the different methods for formulating a reference load curve for the residential energy consumers. Hypothetically, this reference load curve gives the habitual energy consumption pattern of residential consumer. The aim of creating a reference load curve is to visualize and measure the degree of deviation of consumption load curve from habitual energy consumption load curve of a consumer. The image of reference load curve superposed on consumption load curve is sent to the consumers as part of the feedback, so that they can watch the impact of their efforts as well. For this purpose, certain statistical methods (mean, Kernel Density Distribution) and naïve methods are explored, whereas the advanced methods (RF regression, Neural networks) are in the process of study. The so forth studied methods are analyzed through an indicator that verifies the under-estimation or over-estimation of the reference load curve (to be discussed in detail in the proposed paper).

Scientific Innovation and Relevance

(max 200 words)

Hypothetically, the habitual energy consumption pattern of a residential customer can be visualized in the form of a load curve (hereafter referred as reference load curve) for a standard day. For a particular day, the deviation of consumption load curve from reference load curve gives the measure of the effort made by the residential consumer to implement indirect flexibility. In case of peak shaving, a good effort can be observed if the consumption load curve is under reference load curve. The result should be opposite in the case of load shifting for the period of time to which the load is shifted. For the purpose of experiment, two types of alerts are defined. Orange alert demands the households to implement peak shaving between 6 PM and 8 PM on alert day. Green alert demands the households to implement load shifting from evening to afternoon (between noon and 3 PM). The reference load curve is used to measure the impact of nudge signal on each household for each alert. This in consequence measures the effectiveness of nudge tool to implement indirect energy flexibility in residential sector.

Preliminary Results and Conclusions

(max 200 words)

For half-hourly sampled consumption load curve, one method is to take the mean of historical data for each of the 48 timestamps of day. Another statistical method is to take the peak value of the Kernel density estimation for each of the 48 timestamps of the day. Hypothetically, this peak value is the most probable value of energy consumption for the given half hour timestamp. However, these methods are highly susceptible to season variation and therefore gives less accurate reference load curve.

One naïve method is to take an average of the consumption load curve of day "D-1" with the consumption load curve having maximum energy consumption among the curves of days "D-2" and "D-5" (only weekdays). This reference load curve is used for orange alerts. The vice versa of this method is also formulated for green alerts. Both these reference curve keeps the effect of the near past historical consumption, therefore maintaining the effect of temperature and seasonality. These naive methods are devised to introduce a bias, so that it nudges the households makes a better effort in future. The advanced methods are still in the process of study.

Main References

(max 200 words)

Albadi, M. H., and E. F. El-Saadany. 2007. “Demand Response in Electricity Markets: An Overview.” In 2007 IEEE Power Engineering Society General Meeting, 1–5.

Bivas, Pierre. 2011. “La production d’effacement : comment offrir des économies d’électricité à des millions de foyers.” Le journal de l’ecole de Paris du management n°90 (4): 8–14.

Hatton, Leslie, and Philippe Charpentier. 2014. “Système électrique français : estimation de l’effacement des clients résidentiels,” 14.

Lesgards, Valérie, and Laure Frachet. 2012. “La Gestion de La Demande Résidentielle d’électricité: Retour Sur 30 Ans d’expérimentations Mondiales.” La Gestion de La Demande Résidentielle d’électricité: Retour Sur 30 Ans d’expérimentations Mondiales, no. 607: 162, 164, 192-210 [21 p.].

Neenan, B. 2009. “Residential Electricity Use Feedback: A Research Synthesis and Economic Framework,” 126.

Thaler, Richard H., and Cass R. Sunstein. 2008. Nudge: Improving Decisions about Health, Wealth, and Happiness. Nudge: Improving Decisions about Health, Wealth, and Happiness. New Haven, CT, US: Yale University Press.

 
14:40 - 16:10Session W3.5: Improving indoor environmental quality
Location: Concert Hall - Kamermuziekzaal
Session Chair: Natalia Giraldo Vasquez, Federal University of Santa Catarina
Session Chair: Jean-Baptiste BOUVENOT, INSA Strasbourg/ICube Laboratory
 
14:40 - 14:58

The impact of light distribution and furniture layout on meeting light exposure objectives in an office - a simulation case study

Megan Danell1, Steffen Hartmeyer1, Lisa Petterson2, Robert Davis3, Marilyne Andersen1, Siobhan Rockcastle4

1Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland; 2SRG Partnership, Portland, OR United States of America; 3Pacific Northwest National Lab, Portland, OR, United States of America; 4University of Oregon, Eugene, OR United States of America

Aim and Approach

(max 200 words)

While the building industry is beginning to embrace the impact of light on non-visual responses that drive human health, there are limited design guidelines for how to implement effective light distribution and achieve recommended circadian light exposure. Human-centric factors that impact eye-level light exposure in a private office include the seating location, view direction, and eye level of an occupant, which interact with the light distribution, intensity, and spectrum of any given light source. This study presents a simulation-based study that compares various light distribution patterns, furniture configurations, and seating/standing positions to illustrate the impacts on human health potential from a non-visual health perspective.

The space used in our case study is an existing architectural office located in Portland, OR. Multiple luminaires and light distribution patterns are compared under different furniture layouts. The ALFA (Adaptive Lighting for Alertness) plug-in for Rhino is used to simulate Equivalent Melanopic Lux (EML) values for a series of hourly and daily time steps [4]. Electric light sources are simulated using industry-standard IES files and results are compared for both seated and standing view positions.

Scientific Innovation and Relevance

(max 200 words)

A number of simulation techniques have emerged in recent years as a means to predict how varying factors within a space affect non-visual light exposure for building occupants. These techniques include the simulation of vertical illuminance values in incremental measurements across one or more view directions [3, 4, 6]. Recent work has also compared the impact of daylight [1, 3, 4, 5] and electric lighting sources [4, 5, 6, 7] on the health of indoor occupants. A recent study compared the impact of various overhead light sources on vertical eye-level exposure and horizontal task-plane illuminance [2]. This paper builds upon these studies by comparing a broader range of occupant-centric and spatial conditions that can impact the lighting design of an office space.

The novelty of our research lies in the comparison of light distribution patterns, furniture layout, and ergonomics within a private office space. Because eye-level light exposure accounts for light reflected off of vertical surfaces, luminaires that distribute light onto vertical surfaces and are located closer to the eye are potential assets for improving healthy lighting conditions. This work has the potential to bridge research with practical lighting design recommendations to improve the health and well-being of occupants located in private offices.

Preliminary Results and Conclusions

(max 200 words)

Our results reveal a variety of intriguing outcomes. Intuitively, the combination of electric light and daylight sources systematically outperforms scenarios that rely exclusively on electric light only. While 36 out of 48 simulated scenarios achieved the minimum threshold for the WELL Building Standard of 150 melanopic lux (assuming continuous exposure between 9am and 1pm), less than half achieved the recommended 250 melanopic lux, despite achieving recommended task-plane illuminance values.

Comparing results from the various light distribution scenarios (direct vs. direct/indirect ceiling-mounted luminaires and wall-wash luminaires), the fixtures that provided a significant wall wash component achieved the highest EML values. This indicates the potential for vertical light distribution to act as a source of healthy light exposure that has not yet been thoroughly studied. A comparison of various ergonomic positions also reveals the variability in EML exposure between standing and seated positions. Further development of this proposal would contribute to the currently limited design guidelines for implementing effective lighting design to achieve circadian light exposure through the use of furniture configurations, eye level, and lighting distributions.

Main References

(max 200 words)

[1] Acosta, I., Leslie, R., & Figueiro, M. (2017). Analysis of circadian stimulus allowed by daylighting in hospital rooms. Lighting Research & Technology, 49(1), 49–61.

[2] Jarboe, C., Snyder, J., & Figueiro, M. (2020). The effectiveness of light-emitting diode lighting for providing circadian stimulus in office spaces while minimizing energy use. Lighting Research & Technology, 52(2), 167–188.

[3] Amundadottir, M., Rockcastle, S., Sarey Khanie, M., & Andersen, M. (2017). A human-centric approach to assess daylight in buildings for non-visual health potential, visual interest and gaze behavior. Building and Environment, 113, 5–21.

[4] Saiedlue, S., Amirazar, A., Hu, J., & Place, W. (2019). Assessing Circadian Stimulus Potential of Lighting Systems in Office Buildings by Simulations. ARCC Conference Repository.

[5] Danell, M., Amundaddottir, M. L., & Rockcastle, S. (2020). Evaluating Temporal and Spatial Light Exposure Profiles for Typical Building Occupants. SimAUD Conference Proceedings.

[6] Dai, Q., Huang, Y., Hao, L., Lin, Y., & Chen, K. (2018). Spatial and spectral illumination design for energy-efficient circadian lighting. Building and Environment, 146, 216–225.

[7] Rockcastle, S., Danell M., Petterson, L., & Amundadottir, M. (2020). The Impact of Behavior on Healhty Circadian Light Exposure Under Daylight and Electric Lighting Simulations. ACEEE Conference Proceedings.



14:58 - 15:16

Evaluating the use of photobiology-driven alertness and health measures for circadian lighting design

Athina Ji-Hae Alight, J. Alstan Jakubiec

University of Toronto, John H. Daniels Faculty of Architecture, Landscape, and Design, Toronto, Canada

Aim and Approach

(max 200 words)

The aim of this project is to evaluate a novel daylighting and electric lighting design workflow that assesses a space based upon light’s impact on human photobiology-driven alertness, and health. The method, being published in a separate submission to the conference, works by translating timeseries spectrally-resolved light simulation data into photobiologically driven measures mediated by the response of intrinsically-photosensitive retinal ganglion cells (ipRGCs) in the human eye. These measures are used as input to a dynamic photobiological framework that accounts for light history, timing, spectrum, and homeostatic body rhythms. These measures are then visualised in a novel manner to communicate the impacts of lighting on space occupants. To demonstrate the value of this process, the predicted non-visual biological effects of six design variables (artificial lighting schedules, artificial light spectrum, occupant location, window spectral transmittance, surface reflectance, and two space designs) are simulated. The design variables are also applied to the frameworks suggested by Mardaljevic et al. (2013), Amundadottir et al. (2017), the WELL standard (2018), and Konis (2019) to test how these models respond to variations in spectrum and light exposure and how they differ in the resulting evaluation of architectural design.

Scientific Innovation and Relevance

(max 200 words)

Several frameworks have been developed to evaluate lighting design for non-visual biological effects, which this paper compares and evaluates. Unlike light for visual tasks, the non-visual/circadian system, is sensitive to the timing of light exposure. The circadian system is also responsive to shorter wavelengths than the visual system. Illuminance that is appropriate to perform visual tasks therefore may not be enough to entrain circadian rhythms or maintain alertness and performance. Insufficient light after waking or excess light before sleep onset disrupts circadian rhythms with harmful health consequences. Furthermore, circadian disruption is cumulative, and depends on circadian entrainment in the recent past. As a result of these complexities, our model takes the history, timing, intensity, and spectrum of light exposure into account. To the best of our knowledge, the workflow presented in this paper is the only one that predicts explicit biological effects of light and spectrum over time rather than circadian light potential. Through implementing our model, we will demonstrate the results of the model and how architectural design can directly impact an occupant’s circadian health. Our comparative analysis will showcase how predicting alertness and health measures differs from previous work and impacts the evaluation of architecture.

Preliminary Results and Conclusions

(max 200 words)

For the six design parameters and using our new model, the following alertness and health photobiological measures are calculated: subjective alertness measured by the Karolina Sleepiness Scale, mean reaction time, attention lapses, and performance at rote tasks, the amount of circadian phase shift per day, the time of peak melatonin concentration, and the percent of total melatonin suppression per day due to acute light exposure.

The comparative analysis with previous models is based on two aspects: (1) comparisons of quantitative lighting units and (2) assessing differences in design evaluation outcomes as positive or negative. A compilation of the circadian calculation and evaluation methods used in existing photobiological lighting design evaluative frameworks (Mardaljevic et al. 2013, Amundadottir 2017, WELL Standard 2018, Konis 2019) are compared in this manner.. Each framework’s responsiveness to lighting types (daylight, electric, or hybrid), evaluation timeframe (instantaneous, daily, or annual), and lighting design interventions is also compared and discussed.

Main References

(max 200 words)

Amundadottir, M. L., Rockcastle, S., Khanie, M. S., & Andersen, M. (2017). A human-centric approach to assess daylight in buildings for non-visual health potential, visual interest and gaze behavior. Building and Environment, 113, 5-21.

Circadian lighting design. (2018). https://standard.wellcertified.com/light/circadian-lighting-design.

International WELL Building Institute, WELL Building Standard Circadian Lighting Design Feature. https://standard.wellcertified.com/light/circadian-lighting-design Last accessed 6/3/2020.

Konis, K. (2019). A circadian design assist tool to evaluate daylight access in buildings for human biological lighting needs. Solar Energy, 191, 449-458.

Mardaljevic, J., Andersen, M., Roy, N., & Christoffersen, J. (2013). A framework for predicting the non-visual effects of daylight–Part II: The simulation model. Lighting Research & Technology, 46(4), 388-406.

Solemma.com. ALFA. https://solemma.com/Alfa.html.

Tekieh, T., Lockey, S. W., Robinson, P. A., McCloskey, S., Zobaer, M. S., & Postnova, S. (2020). Modelling melanopsin-mediated effects of light on circadian phase, melatonin suppression and subjective sleepiness.



15:16 - 15:34

Integrated analysis of daylight and solar access building requirements and performance in urban environments in Estonia

Francesco De Luca, Abel Sepúlveda

Tallinn University of Technology, Tallinn, Estonia

Aim and Approach

(max 200 words)

Daylight and solar access are essential aspects of the indoor environmental quality of buildings. Adequate quantity of daylight helps to perform tasks with ease and its distribution increases architectural quality [1]. Appropriate direct solar access helps the entrainment of the circadian rhythm and the improvement of physiological and psychological well-being of occupants [2]. Thus, in most countries, regulations prescribe minimum quantities of daylight and direct solar access [3, 4].

The new EU standard Daylight in Buildings [5], to be acquired in Estonia, for daylight requires a minimum Daylight Factor (DF) of 0.7% on 95% of the simulation plane and of 2.2% on 50% of the plane closer the window. For solar access in dwellings it requires a minimum of 1.5 hours of exposure to sunlight calculated during one day between February 1st and March 21st.

The present study investigates optimal dwelling room parameters for 1) the fulfillment of both DF and sunlight requirements of the new EU standard in urban environments, where sunlight provision is most critical, and 2) adequate daylight availability. The aim is to help local authorities in the acquisition of the new EU standard and to provide designers with guidelines for the fulfillment of both requirements.

Scientific Innovation and Relevance

(max 200 words)

The new EU standard requires different daylight but same sunlight quantity for the different countries. There are no studies about the relation between the two requirements in Estonia. Additionally, recent studies proved the scarce reliability of the Daylight Factor metric in predicting daylight availability in the country [6,7].

The innovation of the study lies in the integrated analysis of building performance for daylight and solar access at northern latitudes in urban environments. Additionally, it contributes to the assessment of the reliability of the DF requirements through climate based daylight simulations using the metrics of the LM-83-12 method Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE) [8]. The first predicts reliably daylight availability, the latter potential visual discomfort.

The integrated analysis of DF and solar access, DF and sDA, ASE and solar access permits to assess the efficacy of the requirements of the new EU standard for Estonia and to develop guidelines for the design in urban environments.

For the study a parametric model is realized that generate variations of a sidelit room orientation, window size, shading (upper floor balcony) and surrounding environment. The parametric model automates the calculation of solar access and the different daylight simulations at each variation.

Preliminary Results and Conclusions

(max 200 words)

Simulations for 144 room variations, 8 orientations, 9 window sizes and 2 shading states are performed for March 21st without surrounding buildings and in three urban environments in Tallinn.

Without surrounding buildings, DF, that doesn’t depend on orientation, is fulfilled by 66.7% of 18 variations, solar access, sDA and ASE by 62.5%, 49.3% and 56.9% of 144 variations respectively. DF and sunlight together, and sDA and ASE together, as required by the EU standard and by the LM-83-12 method, are fulfilled by 27.8% and 13.9% of all variations respectively.

In the three urban environments, DF is simulated also for the 8 orientations due to the different external obstructions. On average, solar access, DF, sDA and ASE are fulfilled by 51.8%, 20.3%, 17.8% and 68.5%, DF and sunlight, and sDA and ASE together are fulfilled by 14.4% and 3.7% of all variations respectively.

Preliminary results show the different fulfillment of DF and sunlight, the influence of the urban environment and the difficulty to achieve the two pair of performance together, and the daylight overestimation by the DF requirement in Estonia. The paper will present detailed simulation results and parameters necessary to fulfil the different metrics singularly and in pairs as required.

Main References

(max 200 words)

1 - Reinhart, C.F. 2014. Daylighting Handbook I. Fundamentals. Designing with the Sun. Building Technology Press, Cambridge (USA).

2 – Lockley, S.W. 2009. Circadian rhythms: influence of light in humans. In: Squire LR (ed), Encyclopedia of Neuroscience (Vol. 2), Cambridge, MA, USA: Academic Press, 971–988.

3 – Dogan, T. and Park, Y.C. 2019. A critical review of daylighting metrics for residential architecture and a new metric for cold and temperate climates. Lighting Research & Technology, 51, 206–230.

4 – Darula, S., Christoffersen, J. and Malikova, M. 2015. Sunlight and insolation of building interiors. Energy Procedia, 78, 1245–1250.

5 - European Commission 2018. EN 17037:2018 Daylight in Buildings.

6 - De Luca, F., Kiil, M., Simson, R., Kurnitski, J. and Murula, R. 2019. Evaluating daylight factor standard through climate based daylight simulations and overheating regulations in Estonia. Proceedings of 16th IBPSA International Conference and Exhibition (BS2019), 3968-3975.

7 – Sepúlveda, A., De Luca, F., Thalfeldt, M. and Kurnitski, J. 2020. Analyzing the fulfillment of daylight and overheating requirements in residential and office buildings in Estonia. Building and Environment, 180, 107036.

8 - Illuminating Engineering Society 2013. IES LM-83-12 Approved Method: IES Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE).



15:34 - 15:52

Machine learning techniques for the daylight and electric lighting performance predictions

Chantal Basurto, Oliver Paul, Jérôme H. Kämpf

Idiap Research Institute, 1920 Martigny, Switzerland

Aim and Approach

(max 200 words)

Despite the technological advance in the field of energy efficient buildings, the achievement of adequate lighting interior environments it is still a tight corner spot. The latter, due to the complex interplay occurring at different levels of the building performance, involving energy related and occupant’s comfort issues. Such as, achieving a right balance between an increased daylight penetration for the reduction of heating and lighting loads in winter, while minimizing the risk of glare for the occupants. Providing an adequate solar protection while achieving a sufficient daylight provision at task area is a similar quest for summer time. Therefore, in order to undertake the intrinsically linked energy efficiency and occupant’s comfort goals, recent research endeavors involve an integrated assessment of daylight, electric lighting, blinds and lighting controls. Nowadays, such evaluations are mostly performed with the use of computer simulations, which, due to the complexity of the issue, are still highly demanding in terms of computing time and performance capabilities; besides of the human-hours invested on the interaction with distinctive tools and interfaces. In order to improve the response time of daylight and electric lighting performance-predictions, machine learning techniques based on existing daylighting evaluation methods, are employed using surrogate models.

Scientific Innovation and Relevance

(max 200 words)

In order to achieve an optimal control of blinds and electric lighting, a predictor model is employed to evaluate the impact of a blind’s position choice on the work-plane illuminance and of glare in the occupant’s eye. Including the predictor model in a Model Predictive Control (MPC) is the ultimate goal, aiming to obtain a quasi-real-time optimization of the building parameters, to provide visual comfort to the user with less electric lighting. Ubiquity is the main feature of this work, since the predictor model is derived from year-round simulations generated by the RADIANCE based matrix multiplication methods, where all possible blinds positions and weather conditions are considered. Simulation cost is another relevant feature of this work, since, due to the longer time that RADIANCE simulations require to complete, the predictor model is rather based on a statistical surrogate model realized with an Artificial Neural Network (ANN). A database is first produced and employed for the training of the surrogate model. Its input parameters are the weather data (direct and diffuse irradiance), sun and blinds position and electric lighting intensity, while the output data are key performance indicators (average work-plane illuminance and DGP glare index), for specific users.

Preliminary Results and Conclusions

(max 200 words)

The method is applied to an office building located in Martigny, Switzerland, where two specific rooms are modeled and used as a case-study to demonstrate the model’s predictor capabilities. The two models were created using Sketchup, while their material properties (reflectance, transmittance and other physical parameters) were measured using a Minolta Chromameter (CR-200b) and Gloss-meter (GM-060). The models were then calibrated according to on-site illuminance measurements obtained during the summer 2020, where the accuracy was reported as below 20%, providing the target precision for our surrogate model. A nearby weather station is used to gather direct and diffuse irradiance on hourly basis for the whole year under study. The vast amount of data obtained from the year-round RADIANCE simulations was determinant for defining the function between the inputs and outputs. Different ANNs (FFN, LSTM, GRU and CNN) are tested and compared to provide satisfactory precision for both illuminance and DGP, at a negligible simulation cost due to the data obtained beforehand from the RADIANCE simulations. The electric lighting contributions to the illuminance on the work-plane are computed separately, and the potential glare from the luminaires neglected. The developed surrogate model is finally validated against actual RADIANCE simulations and real monitoring.

Main References

(max 200 words)

Ayoub, M., 2020. A review on machine learning algorithms to predict daylighting inside buildings. Solar Energy 202, 249–275. https://doi.org/10.1016/j.solener.2020.03.104

McNeil, A., 2013. The Five-Phase Method for Simulating Complex Fenestration with Radiance (Tutorial). Lawrence Berkeley National Laboratory, Berkeley, CA.

McNeil, A., 2012. A validation of the RADIANCE Three-Phase Simulation Method for Modeling Annual Daylight Performance of Optically Complex Fenestration Systems. Journal of Building Performance Simulation 1–14.

McNeil, A., 2010. The three-phase method for simulating Complex Fenestration with Radiance. Lawrence Berkeley National Laboratory, Berkeley, CA.

Nault, E., Moonen, P., Rey, E., Andersen, M., n.d. Predictive models for assessing the passive solar and daylight potential of neighborhood designs: A comparative proof-of-concept study. Building and Environment 116, 1–16. http://dx-doi.org/10.1016/j.buildenv.2017.01.018

Ward, G., 1985. RADIANCE lighting simulation software.

Wienold, J., Christoffersen, J., 2005. Towards a new daylight glare rating. Presented at the LUX Europa: Lighting for Humans, Berlin, Germany.

Zhaoyang, L., Cheng, S., Qi, D., 2020. A daylight-linked shading strategy for automated blinds based on model-based control and Radial Basis Function (RBF) optimization. Building and Environment 177. https://doi.org/10.1016/j.buildenv.2020.106854



15:52 - 16:10

Luminance distributions in consultancy: Simulations or measurements?

Thijs Willem Kruisselbrink

Peutz BV, Netherlands, The

Aim and Approach

(max 200 words)

The luminance distribution is suitable tool to assess the lit environment in a holisitic manner. The luminance distribution is either simulated or measured. Both approaches have different strenghts and weaknesses. This work presents an analysis of the strenghts and weaknesses of the two approaches in order to find the most suitable approach for specific cases in consultancy.

Scientific Innovation and Relevance

(max 200 words)

The lit environment is an intangible, but rather relevant component of the built environment, impacting performance, comfort, health and well-being. Research has shown that the lit environment has a multidimensional character. Consequently, the lit environment cannot be fully grasped by singular metrics that are often utilized inconsultancy such as the daylight factor (DF). Preferably, multiple metrics, associated to e.g. amount,distribution or directionality of light, are utilized todescribe the lit environment. However, despite significant effort, the research community has not found asatisfactory and holistic metric to capture the lit environment as a whole.

Alternatively, the luminance distribution can be a suitable means to describe the lit environment, as it contains information on the majority of relevant metrics. Nevertheless, practical implementation of the luminance distribution, simulation or measurement, in consultancy is rather limited. In addition to the advantagesof the luminance distribution, multiple limitations areassociated to its use, both for simulations and mea-surements.

Preliminary Results and Conclusions

(max 200 words)

Simulations or measurements of the luminance distributions are suitable for different consultancy cases. Simulations are more suitable to find a optimal solution for the lit environment while measurements are able to assess a problem associated to the lit environment.

Main References

(max 200 words)

Inanici, M. (2006, 6). Evaluation of high dynamicrange photography as a luminance data acquisitionsystem.Lighting Research and Technology 38(2),123–134.

Kruisselbrink, T. (2020, 10).Practical and continu-ous luminance distribution measurements for light-ing quality. Ph. D. thesis, Eindhoven University ofTechnology, Eindhoven.

Kruisselbrink, T., R. Dangol, and A. Rosemann(2018, 6).Photometric measurements of light-ing quality: An overview.Building and Environ-ment 138, 42–52.

Ochoa, C. E., M. B. Aries, and J. L. Hensen (2012, 7).State of the art in lighting simulation for buildingscience: a literature review.Journal of BuildingPerformance Simulation 5(4), 209–233.

Pierson, C., M. Bodart, J. Wienold, and A. Ja-cobs (2017). Luminance maps from High DynamicRange imaging : calibrations and adjustments forvisual comfort assessment. InLux Europa, Ljubl-jana, Slovenia, pp. 147–151.

Reinhard, E., G. Ward, S. Pattanaik, and P. Debevec(2006, 8).High Dynamic Range Imaging: Ac-quisition, Display, and Image-Based Lighting (TheMorgan Kaufmann Series in Computer Graphics).San Fransisco: Morgan Kaufmann Publishers Inc.

Reinhart, C. and O. Walkenhorst (2001). Valida-tion of dynamic RADIANCE-based daylight simu-lations for a test office with external blinds.Energyand Buildings 33(7), 683–697.

Van Den Wymelenberg, K. (2012).Evaluating Hu-man Visual Preference and Performance in an Of-fice Environment Using Luminance-based Metrics.Ph. D. thesis, University of Washington.

 

 
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