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, 15:34:28 CEST

 
Only Sessions at Location/Venue 
 
 
Session Overview
Location: Concert Hall - Artiestenfoyer
't Zand 34, Bruges
Date: Wednesday, 01/Sept/2021
10:30 - 12:00Session W1.2: Student Modelling Competition: Can we build a building without HVAC and achieve good comfort in Belgium (like 2226 in Austria)?
Location: Concert Hall - Artiestenfoyer
Session Chair: Elisa Van Kenhove, Ghent University

The aim of the student modelling challenge & competition is to facilitate wider participation in the conference by providing a competitive forum for MSc and PhD students to explore the use of building performance simulation.

In this special edition of the IBPSA student challenge & competition, we have encouraged participants to use the IBPSA network to share information, ask questions and provide solutions as well as to collaborate and learn from each other. The subject of the study is the low-tech building 2226 of Baumslager & Eberle in Lustenau. Out of all participating teams, two finalists are selected that will present their work in this session.

20 minutes: Presentation of finalist 1: Bergische Universität Wuppertal, Germany

  • Karl Walther
  • Isıl Kalpkirmaz Rizaoglu
  • Hale Tugçin Kirant-Mitic
  • Ghadeer Derbas

 20 minutes: Presentation of finalist 2: CEPT University, India

  • Divya Mullick
  • Priyanka K Raman
  • Sakshi Nathani
  • Shivangi Singh
  • Shreya Nigam
  • Sujitha Subbiah

Questions from student modelling competition panel and audience.

13:00 - 14:30Session W2.2: Ensuring high quality building simulations
Location: Concert Hall - Artiestenfoyer
Session Chair: Laura Carnieletto, University of Padova
Session Chair: Frederik Maertens, boydens engineering
 
13:00 - 13:18

Heat and moisture transport through a living wall system designated for greywater treatment

Hayder Alsaad, Conrad Voelker

Bauhaus-University Weimar, Germany

Aim and Approach

(max 200 words)

Façade greening systems designated for remediating greywater can help to relieve the water treatment centres while saving on irrigation water (Prodanovic et al. 2017). This study aims to numerically investigate the heat and moisture transport in such systems. As most heat and moisture simulation models cannot simulate the complex impact of vegetation on the simulated parameters, this study was conducted by coupling two simulation tools: ENVI-Met and Delphin. ENVI-Met is a high-resolution meteorological model that can simulate the interaction between urban geometry, vegetation, and the outdoor environment (Bruse and Fleer 1998). Delphin, on the other hand, is a simulation package for coupled heat and moisture transport in porous building materials (Grunewald 2000). In the present study, ENVI-Met was used to calculate the influence of the plants on air temperature, velocity, relative humidity, wind direction, and radiation (long wave and short wave) on the façade. Subsequently, the calculated parameters were then imposed on the façade in Delphin. Thus, ENVI-Met was used to determine the local climate conditions on the façade, which were used to conduct the hygrothermal simulations with Delphin. The hygrothermal simulations had a duration of four years to reach the equilibrium moisture content in the construction.

Scientific Innovation and Relevance

(max 200 words)

With the continuously increasing levels of pollution in cities and rising temperatures due to the urban heat islands, living walls have been growingly investigated because of their promising potential in improving the urban environment. In addition, these systems can have a significant impact on the performance of the walls on which they are mounted. The literature indicates that façade greening can improve the heating demand of the building (Tudiwer and Korjenic 2017). Yet, due to evaporation from the substrate and transpiration from the plants, the relative humidity on the façade can increase (Capener and Sikander 2015). Moreover, as the greening system investigated in this study is meant for greywater treatment, it involves continuous water flow in the substrate of up to 50-75 L/d. An increase in humidity can damage the building material and reduce the energy efficiency of the building by increasing the heat conductivity of the wall layers. As hygrothermal simulations of living walls designated for greywater treatment is not reported in the literature, this study aims to investigate the impact of relatively high exposure to moisture on façades.

Preliminary Results and Conclusions

(max 200 words)

To evaluate the impact of the living wall, two simulation models were created: a façade covered with a living wall and a reference facade with no greening. Both facades had a generic brick structure with a total thickness of 420 mm. The simulations showed that while the living wall was emitting water vapour, it did not increase the humidity content in the structure because of the ventilated air gap between the greening and the façade. In fact, the facade greening protected the wall from wind-driven rain and thus had a 16% less humidity content in the fourth simulation year in comparison to the reference case. The relative humidity of the interior surface of the wall was almost similar in both cases (58.3% with greening and 59.8% without greening). In the summer months (21 June – 21 September), the living wall cooled the façade's surface temperature due to shading, the thermal mass of the substrate, and the passive cooling of the plants. The maximum surface temperature behind the greening was 25°C compared to 40.6°C without greening. In the winter, the greening increased the minimum interior surface temperature by 1.2 K, which indicates an improvement in the thermal resistance of the construction.

Main References

(max 200 words)

Bruse, Michael; Fleer, Heribert (1998): Simulating surface–plant–air interactions inside urban environments with a three dimensional numerical model. In Environmental Modelling & Software 13 (3-4), pp. 373–384. DOI: 10.1016/S1364-8152(98)00042-5.

Capener, Carl-Magnus; Sikander, Eva (2015): Green Building Envelopes – Moisture Safety in Ventilated Light-weight Building Envelopes. In Energy Procedia 78, pp. 3458–3464. DOI: 10.1016/j.egypro.2015.11.179.

Grunewald, John (2000): Documentation of the Numerical Simulation Program DIM3.1", Volume 2: User's Guide. Insitute of Building Climatology, Faculty of Architecture, Univesity of Technology Dresden.

Prodanovic, Veljko; Hatt, Belinda; McCarthy, David; Zhang, Kefeng; Deletic, Ana (2017): Green walls for greywater reuse. Understanding the role of media on pollutant removal. In Ecological Engineering 102, pp. 625–635. DOI: 10.1016/j.ecoleng.2017.02.045.

Tudiwer, David; Korjenic, Azra (2017): The effect of living wall systems on the thermal resistance of the façade. In Energy and Buildings 135, pp. 10–19. DOI: 10.1016/j.enbuild.2016.11.023.



13:18 - 13:36

A convolutional neural network for the hygrothermal assessment of timber frame walls

Astrid Tijskens, Staf Roels

KU Leuven, Belgium

Aim and Approach

(max 200 words)

Timber frame walls typically consist of a wind barrier at the cold exterior side and a vapour barrier at the warm interior side. In cold climates, the vapour barrier must have a higher vapour resistance than the wind barrier, to ensure vapour that entered the construction at the inside can dry out towards outside. However, there are no general guidelines available as to which combinations of wind and vapour barrier are safe in a specific context. Sometimes, a rule of thumb is used, which requires the ratio between the vapour resistances of vapour and wind barrier to be between 5 and 15 or even higher. This rule, however, does not take into account moisture buffering capacity of the structure nor specific climatic aspects, and hence does not guarantee an optimal solution. Because a hygrothermal simulation for every case would be too time-intensive, a metamodel is proposed in the current study, which allows quickly determining adequate combinations of wind and vapour barrier under given conditions. A convolutional neural network for time series is used to replace the hygrothermal simulations, thus allowing flexibility in the desired post-processing.

Scientific Innovation and Relevance

(max 200 words)

The use of neural networks for time series predictions is a fairly novel metamodelling strategy in the field of building physics. When evaluating the hygrothermal performance of a building component in a probabilistic framework, metamodelling strategies have in the past been applied to predict specific and single-valued performance indicators. This approach provides little flexibility and might not provide sufficient information for decision-making. Instead, a metamodel predicting hygrothermal time series, as calculated by the original hygrothermal model, provides more information and allows the user to post-process the output as desired. In [1-2], the authors proved the applicability of convolutional neural networks for hygrothermal calculations of massive brick walls. The current study explores the models to predict the hygrothermal response of timber frame walls.

Preliminary Results and Conclusions

(max 200 words)

First results show that it is possible to replace the time-consuming hygrothermal model with a much faster convolutional neural network, while maintaining high accuracy. Since material properties, such as (humidity dependent) vapour resistance and moisture buffering capacity, play a significant role in the hygrothermal response, the network requires additional input on this, compared to the network from [1-2], resulting in a slightly different network architecture.

Main References

(max 200 words)

[1] A. Tijskens, S. Roels, and H. Janssen, “Neural networks for metamodelling the hygrothermal behaviour of building components,” Building and Environment, vol. 162, no. June, p. 106282, 2019.

[2] A. Tijskens, H. Janssen, and S. Roels, “Optimising Convolutional Neural Networks to Predict the Hygrothermal Performance of Building Components,” Energies, vol. 12, no. 20, p. 3966, 2019.



13:36 - 13:54

Besos: a python library that links energyplus with energy hub, optimization and machine learning tools.

Theodor Victor Christiaanse1,2, Paul Westermann1,2, Will Beckett1,2, Gaelle Faure1,2, Ralph Evins1,2

1Energy in Cities group, Department of Civil Engineering, University of Victoria, BritishColumbia, Canada; 2Institute for Integrated Energy Systems, University of Victoria, British Columbia, Canada

Aim and Approach

(max 200 words)

The goal of the BESOS library is to create an easy way for academics start building modelling experiments that involve linking EnergyPlus with optimization, energy system design and machine learning techniques. The Building and Energy Simulation, Optimization and Surrogate-modelling (besos) library provides a Python-based software bridge between EnergyPlus and various other environments. Furthermore, software abstractions are specifically setup such that building energy modellers can quickly create numerous model variations using parametric definitions. These include optimizing the building design and energy systems, and integration of the modeling results with machine learning techniques. Accompanying the Python library, a web platform (BESOS) [1] is freely accessible for academics to use the software, learning through our extensive library of examples and developing new software extensions on top of the existing software paradigms.

Scientific Innovation and Relevance

(max 200 words)

The optimal exploration of building design and operation requires the use of many software tools. Among them, EnergyPlus (E+) is a commonly used physics-based building energy simulation tool. The use of machine learning (ML) is finding adoption among engineers in the field and may have a huge impact on the speed and breath of modelling experiments. ML techniques can perform different tasks that could inform building design and operation such as; (i) capture the dynamics of a physics-based models in a fast and accurate surrogate model [2] reducing the cost of expensive exploration, (ii) large building datasets of E+ or real timeseries data can be analysis on a building-by-building level using ML techniques [3], (iii) retrofit measures may be identified by understanding the timeseries sensor data through black box techniques [4], (iv) forecasting future energy performance of the building stock using ML for forecasting [5].

The potential of these techniques ML techniques is evident. The integration between these new Python-based libraries and physics-based modelling tools used for energy modelling was limited. Our software library gives modellers the ability to create building models that work in E+ and manipulate the inputs and outputs of the E+ model within a Python environment.

Preliminary Results and Conclusions

(max 200 words)

The Python environment allows for the integration with these new novel machine learning libraries such as TensorFlow and Scikit-learn. Furthermore, we have also included links to powerful optimization solvers and energy system design tool Energy Hub. These three tools provide numerous options for energy modelers to combine multivariant data sets and E+ models to create experiments that stack many different techniques into a single interface.

We will discuss the challenges and successes we have had building the software library besos and BESOS platform. A demo of the software capabilities will be shown and demonstration how multi-model ecologies can be built are presented. A list of recent projects and papers that are would not be possible without the platform [2-5]. Finally, we will share how we continue to improve the underlying software for the next possible versions by partnering with computer scientists and making innovative technologies available to the building modelling domain.

Main References

(max 200 words)

[1] Faure G, Christiaanse T, Evins R, Baasch GM. BESOS: a Collaborative Building and Energy Simulation Platform. In Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation 2019 Nov 13 (pp. 350-351).

[2] Westermann P, Evins R. Surrogate modelling for sustainable building design–A review. Energy and Buildings. 2019 Sep 1;198:170-86.

[3] Baasch G, Wicikowski A, Faure G, Evins R. Comparing gray box methods to derive building properties from smart thermostat data. In Proceedings of the 6th ACM international conference on systems for energy-efficient buildings, cities, and transportation 2019 Nov 13 (pp. 223-232).

[4] Westermann P, Deb C, Schlueter A, Evins R. Unsupervised learning of energy signatures to identify the heating system and building type using smart meter data. Applied Energy. 2020 Apr 15;264:114715.

[5] Westermann P, Braun J, Murphy E, Grieco J, Evins R. Insight Into Predictive Models: On The Joint Use Of Clustering And Classification By Association (CBA) On Building Time Series. In Rome, Italy; [cited 2020 Jul 16]. p. 1564–71. Available from: http://www.ibpsa.org/proceedings/BS2019/BS2019_211236.pdf



13:54 - 14:12

Data-driven black box model of building dynamics

Sophie Bernard1,2, Valery Ann Jacobs1, Bert Belmans1,3, Arjen Mentens1, Filip Descamps1,4, John Lataire1

1Vrije Universiteit Brussel, Belgium; 2Université libre de Bruxelles, Belgium; 3Universiteit Antwerpen, Belgium; 4Daidalos Peutz, Belgium

Aim and Approach

(max 200 words)

In this research a modelling tool is presented to derive surrogate models of thermal energy transfers in buildings, to support the development and testing of smart control algorithms.

A data-driven approach was used to identify a model able to predict the indoor temperature in a case-study building when an electric heater was turned on. The data about the system was generated by EnergyPlus simulations, which resolve the heat balance equations to simulate the thermal response of a building. The model structure that was selected is a second-order ARMAX transfer function whose parameters were identified with a Least Squares optimization criterion. The model inputs were limited to the heater’s power, the global horizontal solar radiation and the outdoor dry-bulb temperature.

Scientific Innovation and Relevance

(max 200 words)

Buildings account for one-third of the global energy consumption in the world, which is more than the industry sector or the transport sector. For environmental and economic reasons, it is thus important to reduce their energy consumption, while preserving a comfortable environment for their occupants. In this context, computer-aided control techniques for building comfort systems can be a valuable asset. Advanced control techniques, such as model predictive control, require supporting system models for development and testing. However, detailed physical models that carefully take system dynamics into account are too computationally intensive for practical applications. This is why surrogate models of low complexity are highly relevant.

The innovative element is that a frequency domain modelling approach is used. This allows to conveniently select the frequency band of interest. Namely, the dynamics are mostly important at low frequencies. Discarding the high frequencies implicitly removes a significant amount of noise.

Also, the use of a data-driven approach implicitly takes into account influences which, in a first principles approach, might have been neglected. That is, the model is validated on the data rather than on physical insight.

Preliminary Results and Conclusions

(max 200 words)

Simulation experiments have been conducted where random binary sequences (a sequence of step inputs) have been applied as the heater's input, and historical weather conditions have been used for the solar radiation and the outside air temperature.

A transfer function model was obtained, describing the relation between the inputs (heater and weather conditions) and the resulting ambient temperature in the room. A data set corresponding to the month of July was used for the identification, and the resulting model was then validated on a data set of the month of December.

It was demonstrated that the model was able to predict fairly accurately the indoor temperature when the building was subject to winter or summer weather conditions. Further improvements and refinements will be carried out, including taking into account the difference in time constants of the heater and the weather conditions.

Main References

(max 200 words)

P. Abrahams et al., Method for Building Model Calibration to Assess Overheating Risk in a Passive House in Summer, Proceedings of the 16th IBPSA conference, Rome, Italy, Sept. 2-4, 2019, DOI 10.26868/25222708.2019.210768

S. Mostafavi et al., Model Development for Robust Optimal Control of Building HVAC, Proceedings of the 16th IBPSA conference, Rome, Italy, Sept. 2-4, 2019, DOI 10.26868/25222708.2019.211331

S. Royer, Energy and Buildings, Volume 78, pg. 231-237, A procedure for modeling buildings and their thermal zones using co-simulation and system identification, 2014. DOI 10.1016/j.enbuild.2014.04.013

S. Royer et al., IFAC Proceedings Volumes, Volume 47, Issue 3, Pages 10850-10855, Black-box modeling of buildings thermal behavior using system identification, 2014. DOI 10.3182/20140824-6-ZA-1003.01519

R. Pintelon and J. Schoukens. System Identification: A Frequency Domain Approach. John Wiley, 2nd edition, 2012.



14:12 - 14:30

Summer passive strategies assessment based on calibrated building model using on site measurement data

Obaidullah Yaqubi1,2,3, Auline Rodler1,2, Sihem Guernouti1,2,3, Marjorie Musy1,2,3

1Equipe de recherche BPE, Cerma Ouest, Nantes, France; 2Institut de Recherche en Sciences et Techniques de la Ville (IRSTV) , Nantes, France; 3CNRS UMR 6183, GeM, Université de Nantes, France

Aim and Approach

(max 200 words)

With the changes in worldwide climate conditions, extreme summer heat events will become more frequent and severe rendering buildings uncomfortable. This paper in this context, presents the application of co-simulation on practical design issues of mixed mode ventilated buildings. It is based on a 2-months field study measurement of outdoor and indoor air temperatures and window operation of an existing residential building during the hottest season of the year in Nantes (France) in 2018.

The aim of this study is first to use measured indoor temperature to calibrate a building co-simulation model and second to evaluate how openness ratio of windows and operation of window shutters affect the indoor thermal comfort during summer.

Scientific Innovation and Relevance

(max 200 words)

Two modelling tools, Contam and Trnsys, were coupled to simultaneously simulate airflow and temperature dynamics of the whole building. Since each of the five storeys had similar thermo-physical features, it was decided to consider only the last storey for the purpose of the present study because it is the most sensitive to outdoor conditions. Each piece in the apartment i.e. bedroom, living room, and bathroom was treated as a separate zone. The time step of the simulation has been set to 15 min.The agreement between measured and simulated indoor temperature values at every hour was evaluated with the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) and Mean Absolute error (MAE).

For assessing the thermal comfort, international adaptive comfort standard methodologies such as EN 16798 and ASHRAE 55 as well as PMV were used to measure and to compare indoor comfort in the apartments.

Preliminary Results and Conclusions

(max 200 words)

After making necessary adjustments to the model, the co-simulation model was calibrated to the lowest (CV(RMSE)) values, between 3 and 5%, on indoor temperatures in the living rooms of 3 apartments and stairwell. Analysing indoor temperature of calibrated simulation building with adaptive thermal comfort indices showed that apartments and stairwell in the last floor of the building experienced higher temperatures than the maximum allowable operative temperature for category I and II of EN 16798 and ASHRAE 55 category of acceptability of 80 and 90% up to 5% of the studied period. Passive strategies such as adjusting the openness ratio of windows at night and day (natural ventilation) and closing window shutters to 0.9 i.e. ratio of no-transparent area during the day proved to reduce overheating risks for category I and II of EN 16798 and ASHRAE 55 acceptability category of 80% but not enough for acceptability category of 90%. The latter may need to use mechanical means to reduce overheating risks.

Main References

(max 200 words)

Dols, W.S., and Polidoro, B.J. (2015). CONTAM User Guide and Program Documentation Version 3.2 (Na-tional Institute of Standards and Technology)

ASHRAE-55-2017, «Thermal Environmental Conditions for human occupancy,» Atlanta, 2017.

Bienvenido-Huertas, D., Sánchez-García, D., Rubio-Bellido, C., and Oliveira, M.J. (2020). Influence of adap-tive energy saving techniques on office buildings located in cities of the Iberian Peninsula. Sustain. Cities Soc. 53, 101944

 
14:40 - 16:10Session W3.2: Ensuring high quality building simulations
Location: Concert Hall - Artiestenfoyer
Session Chair: Steffen Petersen, Aarhus University
Session Chair: Kristof Vlieghe, Viessmann
 
14:40 - 14:58

Characterised sun path patches as a way to design better shading

Andrew Corney1, Vladimir Bajic2

1Trimble SketchUp, United Kingdom; 2Trimble SketchUp, USA

Aim and Approach

(max 200 words)

Interviews and surveys identified that a large proportion of architects use shadow analysis as the primary (and often only) way of designing shading systems.

The aim of this project was to find ways to enhance this natural workflow by providing low friction ways to get a better understanding about sun quality. The aim is to improve shading outcomes by providing better information in established workflows.

The concepts were developed and studied as part of a beta program with 190 participants, mostly archtiects. The beta program started with a range of surveys and interviews asking participants about if and how they design shading systems.

A beta application with the proposed workflow was then developed, firstly as a web-app, and then as a SketchUp extension.

Scientific Innovation and Relevance

(max 200 words)

Understanding sun path diagrams and shadows are incredibly important and included in most architectural design courses.

However in most climates the time of day and time of year, the cloudiness of the sky, intensity of the sun and outside temperature as well as the nature of the building affect whether or not shading is really useful or not. Annual simulations with analysis tools are outside the capabilities of most architects and even where they are available, the use is sporadic because it does not fit neatly in the architect's design workflow.

A key reason identified in our research (over years) is that any friction in the architectural design process drastically reduces the effectiveness of building simulation. The work here sought to provide a defensible and useful improvement to the information used, while minimising the level of friction added to the design process and we feel this is very relevant.

Preliminary Results and Conclusions

(max 200 words)

So far in the beta program research has shown that a very large proportion of participants (mostly architects, all SketchUp users) use the shadow functionality in SketchUp to design shading systems without using any other hourly simulation input.

Although many participants reported not remembering how to use sun path diagrams, most were able to pass straightforward tests on what the information presented is. This meant that the division of the sun path into 3 types of characterised "patches" (overheating, warming or passive) could also be interpreted and applied to inform design.

We used reverse shadow projections for shading strategies onto sun path diagrams to create visual explanations as to the effectiveness of different shading approaches. These could be generated quickly and easily while using SketchUp and provided a way to dynamically see how important and effective shading devices are, without the need to take the model into dedicated simulation.

We hope results from prototypes being made available for design use will also be presentable at the conference.

Main References

(max 200 words)

Interviews and Discussions with architects and specialists participating in our beta program from the United States and Europe.

Sun, Wind and Light: Architectural Design Strategies, M, DeKay, GZ Brown



14:58 - 15:16

Modelling solar shadings with metallic slats for optimal daylighting. What parameters should we focus on?

Bertrand Deroisy1, Marshal Maskarenj2, Sergio Altomonte2

1Belgian Building Research Institute, Brussels, Belgium; 2Université Catholique de Louvain, Louvain-la-Neuve, Belgium

Aim and Approach

(max 200 words)

Designing high performance buildings requires a proper consideration of solar exposures and indoor climate conditions. In the current context of the climate change it must be possible to guarantee adequate thermal and visual comfort even with future climate conditions. Overheating is obviously an increasing risk factor for the occupants, especially in urban settings due to heat island effect. Meanwhile daylight, other than providing suitable conditions for vision, affects our physiological and psychological health. Solar shading systems with tilting metallic slats are commonly used to control daylight provision and energy transfer to the interior space. However, a precise characterization of their performance has to include many parameters, which are not always available. Very often, component level metrics are used to compare solutions, but these are neither consistently related to a specific context nor they are reliable for more complex building envelope assemblies. This study identifies the factors that most relevantly impact on the robustness of performance outcomes of daylighting simulations. It focuses specifically on the scattering properties of metallic surfaces and the shape of the slat profile on simulation results.

Scientific Innovation and Relevance

(max 200 words)

The main solar shading systems used in Europe include roller blinds and venetian blinds, consisting of stacked and guided metallic slats. Standardized methods for characterizing solar-optical properties of regular transparent materials are well established, but robust methods do not exist yet for light scattering, shading and daylighting systems, such as venetian blinds, which have specific angle-dependent properties. Simulations of daylight provision and thermal radiative transfer through complex building envelopes needs to integrate the spatial distribution aspects from the materials and surfaces finishes used in the models. A comparison of standard methods, up-to date building level simulation techniques and advanced optical simulation tools was done in this study. Exact geometrical models of the slats and the possibility to integrate measured BSDF data to describe the scattering properties of the slat surface were used in advanced optical simulations techniques. A detailed analysis of the sensitivity of a set of input parameters (sky model, optical properties, slat design, glazing type) on the global performance of the solar shading systems was done. The results of this study allow to identify the simulation and modelling parameters that should be primarily considered when evaluating the daylighting performance of a building envelope with solar shading systems.

Preliminary Results and Conclusions

(max 200 words)

Out of the four simulation parameters considered, the factor that has the largest effect on the consistency of simulation outcomes is represented by the tilt angle of the slats. An adequate and accurate setting of the tilt angle, based on solar altitudes and internal requirements, is essential to guarantee comfortable conditions for the building occupants at any time. The light scattering properties of the slat surfaces have a non-negligeable impact on daylight provision. Real slats are often relatively specular. Modelling them as diffuse surfaces generally underestimate transmittance ratios when the system is in a relatively open position. The shape of the slats can also have a significant influence when special profiles are used. However the difference between a flat slat and a typical curved slat is not detectable with advanced optical simulation techniques. The current building simulation applications do not allow to accurately estimate the impact of special slat profile shapes on daylighting performance. Large differences were observed between the two simulation based methods for medium sun angles. In general, more precise models are required whenever relatively specular surfaces, or special slat profiles, are used in shading systems.

Main References

(max 200 words)

Capperucci, Loonen R., Hensen J.L.M, Rosemann A.L.P. (2018). Angle-dependent optical properties of advanced fenestration systems - Finding a right balance between model complexity and prediction error. Building simulation 12, 113–127.

Inanici M., Hashemloo A. (2017). An investigation of the daylighting simulation techniques and sky modeling practices for occupant centric evaluations. Building and Environment 113, 220-231.

Konis T., Lee E.S. (2015). Measured daylighting potential of a static optical louver system underreal sun and sky conditions. Building and Environment 92, 347-359.

Kuhn T., (2017). State of the art of advanced solar control devices for buildings. Solar Energy 154, 112-133.

Nilsson A., Jonsson J. (2010). Light-scattering properties of a Venetian blind slat used for daylighting applications. Solar Energy 84, 2103-2111.

Tzempelikos A., Chan Y-C. (2016) Estimating detailed optical properties of window shades from basic available data and modeling implications on daylighting and visual comfort, Energy and Buildings 126, 396-407.

Uribe D., Vera S., Bustamante W., McNeil A., Flamant G. (2019). Impact of different control strategies of perforated curved louvers on the visual comfort and energy consumption of office buildings in different climates, Solar Energy 2019, 495-510.



15:16 - 15:34

A spectral model for longwave radiant heat transfer: influence of new generation polymers in BES

Edouard Walther, Antoine Hubert

AREP L'hypercube, France

Aim and Approach

(max 200 words)

In Building Energy Simulation (BES), the modeling of radiation relies on a dual-band model: longwave, infra-red radiant heat transfer is linearised and computed separately from shortwave, solar radiation. This robust technique originates from the optical properties of glass, the latter being opaque to longwave radiation.

In the recent year, the use of polymer materials such as ETFE or LDPE has become popular in stations, greenhouses or leisure halls (Giuliano et al. 2010). In comparison with glass, they exhibit attractive features such as a reduced weight or higher visible transmittance.

The dual-band model is consistent for standard glass but appears to be unadapted to the aforementioned materials. Indeed, they are partially transparent to longwave radiation, with transmissivities ranging from 20 to 80% depending on the wavelength, which particularly affects the “greenhouse effect”.

The present work aims at creating a spectral model for radiation transfer in multiple bandwidths and evaluating the influence of the new generation polymer materials on the greenhouse effect. Determining the ability of classical BES models for the simulation of radiant heat transfer through polymers depending on their cutoff wavelength in the infra-red domain is also an objective of this work.

Scientific Innovation and Relevance

(max 200 words)

A few references mention applications using ETFE (Cremers & Marx 2016), (Hu et al. 2016), (Cremers & Marx 2017), however, to the best of the authors’ knowledge, the effect of longwave transmissivity on indoor/outdoor radiation seems to be ignored. In the consulted literature, only (Poirazis et al. 2009) point out the lack of information about transmissivity in the longwave domain for polymers like ETFE and highlight the need for an extensive radiative model with experimental validation.

It hence appears interesting to explore the actual influence of such optical properties on heat transfer within buildings, which a spectral model reliably takes into account. Indeed, depending on the value of transmissivity in the infra-red range, this phenomenon may possibly be negligible as suggested in (Poirazis et al. 2009).

Preliminary Results and Conclusions

(max 200 words)

A single-room, “shoebox” house serves as a test case. The window transmittance model follows (Curcija et al. 2018) and the wall model is built after a 4R3C scheme (Fraisse et al. 2002). In order to confirm the accuracy of the building model, a cross-validation is led using the EnergyPlus software with mere glass on transparent the southern walls. The results obtained show that the spectral model compares well with the dual-band model of EnergyPlus.

Preliminary results have demonstrated that ETFE does not filter the infrared radiations as efficiently as glass does, which is beneficial for longwave radiant cooling, however, given the higher transmittance in the solar spectrum, the temperature in buildings with ETFE may exceed the glazed building's temperature.

A comparison of the ETFE with LDPE, which transmissivity is even higher in the longwave range is currently explored. The differences obtained are in favour of a spectral model for BES of buildings with longwave transparent polymers.

Main References

(max 200 words)

Vox, Giuliano & Teitel, M. & Pardossi, Alberto & Minuto, A. & Tinivella, F. & Schettini, Evelia. (2010). Sustainable greenhouse systems. Sustainable Agriculture: Technology, Planning and Management. 1-80.

Poirazis, H., Kragh, M., & Hogg, C. (2009, July). Energy modelling of ETFE membranes in building applications. In 11th International IBPSA Conference, Glasgow, Scotland (Vol. 144).

Curcija, C., Vidanovic, S., Hart, R., Jonsson, J., & Mitchell, R. (2018). WINDOW Technical Documentation. Lawrence Berkeley National Laboratory.

Cremers, J., & Marx, H. (2016). Comparative study of a new IR-absorbing film to improve solar shading and thermal comfort for ETFE structures. Procedia Engineering

Cremers J, Marx H. A new printed and spatially transformed ETFE foil provides shading and improves natural light and thermal comfort for membrane structures'. PLEA 2017.

Poirazis H, Kragh M, Hogg C. Energy modelling of ETFE membranes in building applications. In11th International IBPSA Conference, Glasgow, Scotland 2009

Hu J, Chen W, Qiu Z, Zhao B, Zhou J, Qu Y. Thermal performances of ETFE cushion roof integrated amorphous silicon photovoltaic. Energy Conversion and Management. 2015

Fraisse G, Viardot C, Lafabrie O, Achard G. Development of a simplified and accurate building model based on electrical analogy. Energy and buildings. 2002



15:34 - 15:52

Modelling naturally ventilated double skin facade in Modelica

Alessandro Dama1, Jaime Varas del Ser1, Ettore Zanetti1, Francesco Casella1, Olena Kalyanova Larsen2

1Politecnico di Milano, Italy; 2Aalborg University, Denmark

Aim and Approach

(max 200 words)

In recent decades, Double Skin Facades (DSF) and their thermal performance have been subject of numerous studies in literature. Despite this, the availability of rapid, robust and accurate tools for evaluating the performance of naturally ventilated double skin facades is still very limited, since only few published models have been accompanied by a complete experimental validation under variable boundary conditions, i.e. temperatures, solar irradiance and wind. Furthermore, the integration and/or coupling of such models within building energy simulation tools remains a complex task due to the multiple functionalities of the transparent and ventilated façade interacting with the building environment.

To this purpose this paper presents the implementation and validation of a model for naturally ventilated DSF in Modelica. The aim is to provide an open and robust tool easily integrable in the recent development of Modelica building libraries. Modelica, in fact, is an object oriented and open source programming language that has gained attention in the last decade, thanks to its ability to standardize and simplify modelling and thanks to its high potential when working with multi-domain systems.

Scientific Innovation and Relevance

(max 200 words)

An ongoing international cooperation, under IBPSA Project 1, aim at creating a freely accessible, editable, documented and validated Modelica simulation library to support the design and operation of buildings and districts [1]. This work would contribute to the building library developments.

Validations of the selected model for naturally ventilated DSF was already presented in [2] and [3]. The further advantage of its implementation in Modelica is, thanks to its modularity, the possibility to perform again the model validation under different choices of the boundary conditions, isolating different model domains. Moreover, in this study the validation was extended to the simulation of a building module with the south facing DSF, giving a proof o the integration of the DSF model with the zone thermal model in Modelica. The experimental database used was provided by a field study on a full scale DSF "The Cube" carried out in Aalborg, Denmark [4].

Finally, a sensitivity analysis was performed on the convection in the ventilated channel, on the glazing solar absorptions and on the thermal capacities. It gave insight on the most relevant choices for the model parameters.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results of the DSF model implementation in Modelica had confirmed its capability to predict the variability of the mass flow rate, mainly due to the variable wind conditions, and improved its accuracy in predicting the outlet temperature and the inward heat flux. Such improvements are likely due to a better coupling in Modelica of the thermal and fluid-dynamic problems. The sensitivity analysis shows the importance of an accurate and detailed optical characterization of the window system and the role of the correlation adopted for the convection inside the ventilated channel. Otherwise, thermal capacity of glazing does not influence significantly the prediction even using a simulation timestep of fifteen minutes.

Main References

(max 200 words)

[1] https://ibpsa.github.io/project1/

[2] A. Dama, D. Angeli, O. K. Larsen, Naturally ventilated double-skin facade in modeling and experiments, Energy and Buildings 144 (2017) 17–29

[3] A. Dama, M. Dopudi, O. K. Larsen, Experimental Validation of a Model for Naturally Ventilated Double-Skin Facades in proceedings of 7th International Building Physic Conference, IBPC 2018, Syracuse, NY, USA

[4] O. Kalyanova, Empirical Validation of Building Simulation Software: Modelling of Double Facades Final Report Technical Report IEA ECBCS Annex43/SHC Task 34 Validation of Building Energy Simulation Tools Subtask E



15:52 - 16:10

Open-source photovoltaic model for early building planning processes: Modeling, application and validation

Laura Maier1, Michael Kratz1,2, Christian Vering1, Philipp Mehrfeld1, Dirk Müller1

1RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Aachen, Germany; 2currently studying at ETH, Zurich, Switzerland

Aim and Approach

(max 200 words)

Within buildings, a great potential to reduce CO2 emissions exists. One common solution is to integrate renewable energy sources (RES) into BESs which are called interconnected systems. In this regard, PV systems are a promising technology as they enable sector coupling on the one hand and support local electricity generation on the other hand.

In order to exploit the full potential of PV systems, they have to be systematically integrated into the local control system. In this context, the proper sizing of PV modules plays an important role. This decision is made at an early planning stage. However, the optimum sizing of PV systems is challenging due to dynamic boundary conditions such as weather and its interdependencies with the whole BES, i.e. mounting’s influence. In this context, simulation models facilitate the process of estimating future operation of PV modules.

We contribute to a more simplified planning process by applying the following steps:

1. We develop an open-source Modelica PV model for wafer-based cells, which is based on manufacturer data only and is suitable for early stage design.

2. We validate the model with measured data to prove mounting’s influence.

Scientific Innovation and Relevance

(max 200 words)

None of the researched Modelica PV models cover all of the following aspects:

• Open-source access

• Parameters based on manufacturer data only

• Integration of the mounting´s influence

• Validation based on measurement data

In addition, we quantify the influence of ohmic losses on the DC power output.

Preliminary Results and Conclusions

(max 200 words)

In order to evaluate the model accuracy, we compare the simulated electrical energy of selected days with the measured one. The simulation mostly overestimates the electricity generation. This is caused by effects such as ageing, ohmic losses (OL) or staining, which are neglected within the model. Apart from that, the highest relative error is observed for the roof system at around 16 %.

To understand higher model errors for some days, we analyze the DC power output of the roof system in more detail. Here, we compare the simulated and the measured power on the day with the highest model error. The absolute difference between the data sets increases with raising power output. When also taking into account the OL, the model error is decreased to 7 %. Here, we estimate the OL using the simulated cell temperature and measured current.

For a simulative OLs estimation, the detailed interconnection of the implemented PV modules has to be known. This information is not necessarily given at an early planning stage and complicates the parameterization tremendously. As this contradicts the model’s aim to be simple and used at an early stage of planning, OLs are neglected.

Main References

(max 200 words)

Batzelis, E., Papathanassiou, S.. A Method for the Analytical Extraction of the Single-Diode PV Model Parameters (2016). IEEE Transactions on Sustainable Energy 7, 504-512.

Boyd, M. (2015). High-Speed Monitoring of Multiple Grid-Connected Photovoltaic Array Configurations.

Boyd, M. (2017). Performance Data from the NIST Photovoltaic Arrays and Weather Station. Journal of Research of the NIST 122.

Duffie, J.A., Beckman, W.A. (edited by). (2013). Solar engineering of thermal processes. Fourth edition. Wiley. Hoboken, NJ (USA).

King, D.L., Boyson, W.E., Kratochvill, J.A. (edited by). (2005). SANDIA REPORT SAND 2004-3535 Unlimited Release Printed December 2004 Photovoltaic Array Performance Model.” (2005).

Müller, D., Lauster, M., Constantin, A., Fuchs, M., Remmen, P. (2016) AIXLIB- An open-source Modelica library within the IEA-EBC Annex 60 Framework. Proceedings from BauSIM2016. Dresden (Germany), 14-16 September.

 

 
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