Conference Agenda

Session
Session F4.2: Ensuring high quality building simulations
Time:
Friday, 03/Sept/2021:
15:00 - 16:30

Session Chair: Nils Artiges, Univ. Grenoble Alpes, CNRS, Grenoble INP, G2Elab, F-38000 Grenoble, France
Session Chair: Lien De Backer, Ghent University
Location: Cityhall (Belfry) - Room 2


External Resource: Click here to join the livestream. Only registered participants have received the access code for the livestream.
Presentations
15:00 - 15:18

Carbon-cost efficient retrofit of passive and active systems in residential buildings using genetic algorithm

Negar Mohtashami1,2, Rita Streblow1, Linda Hildebrand2, Dirk Müller1

1Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Germany; 2Chair of Reuse in Architecture, Faculty of Architecture, RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

In the past two decades, improving the energy performance of existing buildings is a major trend to reduce the environmental impacts since existing buildings make up for the largest share compared to new buildings. The energy consumed in a building consists of both embodied and operational form. However, most current conducted energy optimizations only consider operational energy and remain reluctant to the embodied energy invested in building materials and services during the life cycle of a building. This study addresses both types of energy together and considers building as a whole in order to optimize properties of the building envelope and HVAC systems simultaneously.

Scientific Innovation and Relevance

(max 200 words)

The current research uses MOGA (Multi Objective Genetic Algorithm) to minimize CO2 equivalent emissions, and costs in order to find optimal retrofit scenarios for a typical multi-family house (MFH06) according to TABULA building classification for Germany.

Preliminary Results and Conclusions

(max 200 words)

Findings show four clusters of refurbishment scenarios that are mainly categorized based on the amount of insulation materials. it is also perceived that the most optimal carbon-cost retrofit options focus on increasing the thermal energy storage capacity and remain reluctant in insulating the envelope or changing the windows for a typical multi-family house of 70s mainly due to high embodied energy in the insulation materials and devices.

Main References

(max 200 words)

Evins R. A review of computational optimisation methods applied to sustainable building design. Renewable and Sustainable Energy Reviews 2013; 22: 230–45.

Ramesh, T., Prakash, R., & Shukla, K. K. (2010). Life cycle energy analysis of buildings: An overview. Energy and buildings, 42(10), 1592-1600.

Verbeeck G, Hens H. Life Cycle Optimization of Extremely Low Energy Dwellings. Journal of Building Physics 2007; 31(2): 143–77.

Vilches, A., Garcia-Martinez, A., & Sanchez-Montanes, B. (2017). Life cycle assessment (LCA) of building refurbishment: A literature review. Energy and Buildings, 135, 286-301.



15:18 - 15:36

Application of a long-term MPC formulation to hybrid GEOTABS buildings

Iago Cupeiro Figueroa1, Lieve Helsen1,2

1KU Leuven, Belgium; 2Energyville, Belgium

Aim and Approach

(max 200 words)

This research evaluates the benefits of applying a long-term model predictive control (MPC) formulation to hybrid GEOTABS buildings [1], which consist of a ground-source heat pump (GSHP) and a thermally activated building system (TABS) emission system to cover most of the building energy needs, and a secondary but fast-reacting system to assist the primary system during peak periods. To that end, the methodology presented at [2] is applied to a generic modular hybrid GEOTABS building simulation model for different building balance degrees (i.e., heating or cooling dominated), electricity-gas price ratios and borefield sizes. The possibility of active regeneration is also analyzed.

Scientific Innovation and Relevance

(max 200 words)

To ensure an optimal coordination between the components of a hybrid GEOTABS system an MPC methodology can be applied, reducing the energy use and increasing the cost savings of the building while keeping or even improving the indoor comfort [3]. However, MPCs typically optimize the control actions for an horizon that foresights a few days, while the geothermal borefield dynamics last for several years [4]. The contribution of this research is to evaluate in which situations it is beneficial to apply a long-term formulation that foresights a full year of operation. For example, in the case of passive cooling, is it more beneficial to use it as early during the summer season as possible or to save its capacity towards the end of the season?

Preliminary Results and Conclusions

(max 200 words)

A modular model that comprises a typical hybrid GEOTABS configuration is constructed using Modelica. An MPC optimization problem is constructed using TACO [5], which allows the translation and compilation of non-linear problems (NLPs) using Optimica and in a similar fashion as JModelica. The set of models is simulated for a period of 5 years.

Main References

(max 200 words)

[1] Himpe, E., Vercautere, M., Boydens, W., Helsen, L., & Laverge, J. (2018). GEOTABS concept and design: state-of-the-art, challenges and solutions. In REHVA Annual Meeting Conference Low Carbon Technologies in HVAC.

[2]Cupeiro Figueroa, I., Cimmino M., Helsen L. A methodology for Long-term Model Predictive Control of hybrid geothermal systems: theshadow-cost formulation. Under review

[3]Cupeiro Figueroa, I., Cigler, J., & Helsen, L. (2018). Model Predictive control formulation: a review with focus on hybrid geotabs buildings. In https://www. rehvam2018atic. eu/images/workshops/9/Figuereroa. pdf (pp. 1-9). Proceedings of the REHVA Annual Meeting Conference.

[4]Cupeiro Figueroa, I., Picard, D., & Helsen, L. (2020). Short-term modeling of hybrid geothermal systems for Model Predictive Control. Energy and Buildings, 109884.

[5] Jorissen, F., Boydens, W., & Helsen, L. (2019). TACO, an automated toolchain for model predictive control of building systems: implementation and verification. Journal of Building Performance Simulation, 12(2), 180-192.



15:36 - 15:54

Development and validation of radiation-coupled multimodal heat flux boundary condition for incompressible buoyant internal flows in OpenFOAM

Jake Haskell1, Mike Jäger1, Pia Riedel1, Jerell Gill2, Paul Lynch2, Talbot Kingsbury2, Steven Downie2

1Arup, Advanced Building Engineering, Germany; 2Arup, Advanced Digital Engineering, UK

Aim and Approach

(max 200 words)

The open-source CFD code OpenFOAM has been gaining relevance for the investigation of internal flow phenomena for building physics applications over the course of the past decade, but a major limitation to more widespread adoption has the necessity to use more computationally expensive compressible models to effectively calculate the effects of heat transfer. Furthermore radiation coupling with the default boundary conditions is limited at best and poorly documented to date. Most internal flows can be accurately modelled using the Boussinesq approach and more computationally efficient incompressible solvers, however the adequate thermal boundary conditions are not yet implemented for the OpenFOAM incompressible buoyant solvers and the existing compressible thermal boundary conditions are ill-suited for building physics applications. A new thermal boundary condition is developed to close this gap to allow more accurate CFD modelling of thermally driven buoyant internal flows using OpenFOAM.

Scientific Innovation and Relevance

(max 200 words)

This study documents the development and validation of a new thermal boundary condition that offers the user the ability effectively calculate specific and absolute wall heat fluxes as well as the heat flux resulting from the definition of an external temperature and wall thermal resistance. This new boudary condition allows improved CFD approximation of thermally internal flow for building applications and has furthermore been coupled with the DOM and view factor radiation models to further improve the quality of heat transfer modelling using CFD.

Preliminary Results and Conclusions

(max 200 words)

The new boundary condition is developed in C++ first without radiation coupling and tested to ensure adequate calcuation of a heat flux for the three different modes. Following successful implementation and error testing, the boundary condition is tested on a simple L-shaped room case and benchmarked for accuracy against ANSYS CFX. The radiation coupling is then integrated and the boundary condition is verified against the analog case calculated in CFD; the results show very good agreement for air, surface and mean radiant temperatures. Six different parameter configurations using the boundary condition are investigated and the results show maximum deviation of 0.2°C between the two simulation models. The DOM model shows slightly better agreement with regard to the radiation modelling compared the view factors model.

Main References

(max 200 words)

Cid, K. 2016. A Comparative study between thermal radiation models P1 and discrete ordinates using CFD software OpenFOAM, Congresso Internacional de Fluidodinâmica Computacional

Frie, F. 2014. Calculation of radiative losses of solar receivers using viewfactors, OpenFOAM User Conference 2014

Junior et al. 2016. Numerical validation of viewFactor and FVDOM radiation models of OpenFOAM® and application. Revista chilena de ingeria 26, S. 546-556.

Haskell et al. 1994.Boundary Conditions for the Diffusion Equation in

Radiative Transfer. Journal of Optical Society of America 10. S. 2727-2740

Koncar, B. and Koncar L. 2018. Open access peer-reviewed chapter

Use of CFD Codes for Calculation of Radiation Heat Transfer: From Validation to Application. In: Heat Transfer: Models, Methods and Applications. Kingston University London.

Modest, M. 2013. Radiative Heat Transfer, 3rd Edition. Academic Press

Programmers Guide, OpenFOAM v1806, 2018

Vdovin, A. 2009. Radiative Heat Transfer in OpenFOAM, Chalmers University of Technology



15:54 - 16:12

Optimal control of TABS by Sparse MPC

Yasuyuki Shiraishi1, Masaaki Nagahara1, Dirk Saelens2

1The University of Kitakyushu, Japan; 2KU Leuven, Belgium

Aim and Approach

(max 200 words)

In this study, continuous energy use of Thermally Activated Building System (TABS) is minimized by the sparse optimal control that combines MPC and sparse modeling in order to improve the unsteady actual operation performance of TABS. In other words, we propose a method to improve unsteady energy saving performance of TABS and durability of air conditioning equipment. Furthermore, the purpose of this study is to clarify the energy-saving performance and the control performance of indoor environment by introducing the proposed method to TABS based on numerical simulation.

In this analysis, the effectiveness of the proposed method is verified by using a coupled analysis tool [1] of unsteady CFD analysis and MTLAB/Simulink for a general office space with TABS. Specifically, the water flow rate of TABS has been optimized by the combined method of MPC and sparse modeling so that the ceiling surface temperature of TABS reaches the target value is given as an input condition for CFD analysis. The effectiveness of the proposed method is verified through evaluation of control performance and energy saving performance.

As a case study, we will analyze the results of two cases: normal MPC control (Case1) and combined control of MPC and sparse modeling (Case2).

Scientific Innovation and Relevance

(max 200 words)

TABS, which utilizes the building structure to emit and store energy, is becoming increasingly popular. So far, the introduction of TABS has been progressing mainly in Europe [2], but in recent years, the introduction has also been attempted in Japan [3].

As shown in previous studies [2], TABS is expected to have various advantages such as peak shift, reduction of heat source capacity, and cost reduction by utilizing large heat capacity in addition to energy saving and comfort. On the other hand, since the thermal response is slow due to the large heat capacity, control for creating a comfortable indoor thermal environment is important.

For this reason, study on Model Predictive Control (MPC) [4] that determines the current manipulated variable while predicting the behavior of the controlled variable has attracted attention as a new control method that replaces classical control for the operation of TABS. Furthermore, by combining this MPC and sparse modeling [5], it is possible to realize further energy savings while maintaining control performance and improve durability by minimizing the start and stop frequency of air conditioning equipment. However, application of this method to engineering problems has not been reported.

Preliminary Results and Conclusions

(max 200 words)

In both cases, by using MPC, the TABS is activated before the heat load occurs. As a result, the control error of the ceiling surface temperature was reduced throughout the analysis period, and the average control error on each day was less than 0.3℃.

Preliminary results showed that, in Case1, water was often delivered at a low flow rate of 0.5 L/min. On the other hand, in Case2, compared with Case1, the operating time for 5 days on weekdays was reduced by about 14 hours in total. Therefore, the sparseness of the water flow rate (expansion of the time zone when the water flow rate became zero) was confirmed by using both MPC and sparse modeling. Regarding cumulative water flow rate, in Case2, it was possible to reduce by approximately 39% over the entire analysis period compared with Case1.

By controlling the ceiling temperature, the PMV values in the workspace satisfy the comfort zone in both cases, and the distribution in the horizontal plane was extremely small.

From the above, it has been confirmed that by combining MPC and sparse modeling, it is possible to achieve sparseness of the operation amount while satisfying comfort in the workspace.

Main References

(max 200 words)

[1] Y. Ogawa, Y. Shiraishi, Multi-Objective Optimization of Energy Saving and Thermal Comfort in Thermo Active Building System based on Model Predictive Control, 40th AIVC conference Ghent, Belgium, 2019

[2] D. Olsthoorn, F. Haghighat, A. Moreau, and G. Lacroix, Abilities and limitations of thermal mass activation for thermal comfort, peak shifting and shaving: A review, Building and Environment, VoL.118, pp.113-127, 2017

[3] E. Kataoka, Y. Shiraishi, et al., Radiation Cooling and Heating using Building Thermal Storage for Outside Insulation Building -Part 1. The Architectural Summary of the Building and Equipment System and the Report of Piece Model Experiment Result-, SHASE (The Society of Heating, Air-Conditioning and Sanitary Engineers) of Japan, J-30, pp.317-320, 2016(in Japanese)

[4] A. Afram, and F. Janabi-Sharif, Theory and applications of HVAC control systems – A review of model predictive control (MPC), Building and Environment, VoL.72, 2014

[5] M. Nagahara et al.: Maximum hands-off control - a paradigm of control effort minimization-, IEEE Trans. Automatic Control, 61(3), pp.735-747, 2016



16:12 - 16:30

Developing an archetype building stock model for new cities in Egypt

Fady Abdelaziz, Rokia Raslan, Phil Symonds

UCL Institute for Environmental Design and Engineering

Aim and Approach

(max 200 words)

Egypt’s growing population in the last few decades has led to a significant rise in housing demands. This directed the government to initiate a national project with the goal of developing 50 new satellite cities in the arid desert by 2030 to mitigate the high population density in major cities such as Cairo and Giza. The Egyptian building stock comprises around 13.5 million residential buildings, with almost 37 million residential units. More than 50% of these buildings were built in the last two decades. This has resulted in the residential sector accounting for 47% of total electrical energy consumption in Egypt, as well as 5% of the total CO2 emissions. Developing a residential building stock model, based on representative archetypes presents a strong potential for understanding and analyzing the overall energy performance of the stock. In addition, it allows the prediction of future energy demand and CO2 emissions. Existing data in Egypt provides an overview of the most common archetypes of building stock in terms of building height, construction method, and year of construction, however, these databases lack crucial information regarding the building's physical data that can be used in evaluating energy performance.

Scientific Innovation and Relevance

(max 200 words)

This paper presents the development of ENCEM (Egyptian New Cities Energy Model), which is based on a bottom-up model of building stock archetypes for the new cities within the Greater Cairo region. The study develops the framework of the archetypes using data from 201,440 domestic buildings sampled from 9 new city districts that were constructed in Cairo and Giza governorates over the last 30 years. The study is built on data from CAPMAS (Central Agency for Public Mobilization and Statistics) Egyptian Housing Survey and Census. The energy simulation software tool, EnergyPlus is employed in developing this model to generate an hourly energy demand profile for each archetype. This study will provide a more accurate representation of the overall building stock variability in terms of building type, geometric form, building envelope, and overall energy consumption.

Preliminary Results and Conclusions

(max 200 words)

From a bottom-up approach, the resulting model can be generalized to other cities with similar climates and can be studied further to develop a national building stock for Egypt. Developing this model will act as a key tool for governmental decision-makers and stakeholders in Egypt to be informed with the energy use and the energy-saving potential of the building stock, and will also help policy developers and building scientists to identify replacement or retrofit measures for the various categories of Egypt’s housing archetypes. Understanding these measures will not only reflect on existing building stock but will also provide guidelines for the government’s building codes and legislation to be implemented in new constructions.

Main References

(max 200 words)

- Kavgic, M., Mavrogianni, A., Mumovic, D., Summerfield, A., Stevanovic, Z., & Djurovic-Petrovic, M. (2010). A review of bottom-up building stock models for energy consumption in the residential sector. Building And Environment, 45(7), 1683-1697. doi: 10.1016/j.buildenv.2010.01.021

- Pasichnyi, O., Wallin, J., & Kordas, O. (2019). Data-driven building archetypes for urban building energy modelling. Energy, 181, 360-377. doi: 10.1016/j.energy.2019.04.197

- Famuyibo, A., Duffy, A., & Strachan, P. (2012). Developing archetypes for domestic dwellings—An Irish case study. Energy And Buildings, 50, 150-157. doi: 10.1016/j.enbuild.2012.03.033

- Krarti, M., Aldubyan, M., & Williams, E. (2020). Residential building stock model for evaluating energy retrofit programs in Saudi Arabia. Energy, 195, 116980. doi: 10.1016/j.energy.2020.116980