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).

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Session Overview
Session
Session F1.3: Buildings paving the way for the energy transition
Time:
Friday, 03/Sept/2021:
8:30 - 10:00

Session Chair: Eline Himpe, Ghent University
Session Chair: Vincenzo Corrado, Politecnico di Torino
Location: Cityhall (Belfry) - Room 3

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Presentations
8:30 - 8:48

Cooling energy use reduction in private residential buildings in Egypt accounting for global warming effects.

Mohammad Abdollah Fadel Abdollah, Rossano Scoccia, Giulia Filippini, Mario Motta

Politecnico di Milano, Italy

Aim and Approach

(max 200 words)

Residential and commercial buildings are responsible for almost 50% of the total electricity consumption in Egypt. Most of the electricity production is from coal-based power plants which have significant environmental impact. This percentage is expected to exponentially increase due to the global warming effect. This work deals with the cooling energy reduction strategies, thermal comfort analysis and the usage of solar water heating system compatible with the Egyptian market and accounting for the global warming effects for a privately owned residential building in Cairo as a part of the Mediterranean Investment Facility project in Egypt (MIF) which is an initiative under UN Environment with the overall objective of scaling up clean energy technologies. A study of the Egyptian market was done to explore the best available envelope technologies. Series of dynamic simulations were executed in TRNSYS 18 and a multi criteria decision analysis was conducted to choose the best alternatives. The envelope alternatives were then tested again against the predicted future weather which was generated using statistical downscaling methods to test the continuous validity of the chosen alternatives.

Scientific Innovation and Relevance

(max 200 words)

After assessing common technologies and practices in the Egyptian market. Parametric dynamic simulation campaign was launched for the envelope alternatives for the specific building including different thermal masses and insulation thicknesses and window types. Financial, Energetic, and environmental factors were taken into consideration and comparative analysis was done to assess the best alternatives. Moreover, simple measures to further reduce the cooling energy need was explored such as the usage of more efficient lighting and night ventilation. Additionally, the efficiency and the potential financial and energy savings from the solar water heating system was assessed. Using statistical downscaling methods on the global climate models, future weather files adapted to climate change were generated and the selected passive strategies were tested to assess the validity of such strategies in the future keeping the same level of occupant’s thermal comfort. The size sufficiency and the variation in performance of the HVAC systems were checked to ensure the system adequacy in the future with accordance to the generated adapted weather files.

Preliminary Results and Conclusions

(max 200 words)

This work led to a reduction of 41% in the cooling energy needs and CO2 emissions, with a discounted payback period of 6 years. The cooling energy needs are expected to increase by 39% while the peak cooling loads are also expected to increase by 23% by 2080 rendering the current installed HVAC system undersized. Although the alternative chosen according to the current external conditions were still the best out of the other alternatives, the favourability of the strategies is declining with respect to the alternatives with higher insulation thickness up to 8cm of insulation thickness.

Main References

(max 200 words)

1. A. A. Saleem, A. K. Abel-Rahman, A. H. H. Ali, and S. Ookawara, “An Analysis of Thermal Comfort and Energy Consumption within Public Primary Schools in Egypt,” IAFOR J. Sustain. Energy Environ., vol. 3, no. 1, 2016.

2. J. F. Nebojsa Nakicenovic, Joseph Alcamo, Gerald Davis, Bert de Vries, T. K. Stuart Gaffin, Kermeth Gregory, Amulf Griibler, Tae Yong Jung, T. M. Emilio Lebre La Rovere, Laurie Michaelis, Shunsuke Mori, A. R. William Pepper, Hugh Pitcher, Lynn Price, Keywan Riahi, P. S. Hans-Holger Rogner, Alexei Sankovski, Michael Schlesinger, and Z. D. Steven Smith, Robert Swart, Sascha van Rooijen, Nadejda Victor, “Special Report on Emissions Scenarios,” The Edinburgh Building, Cambridge, 2000.

3. R. A. Cox, M. Drews, C. Rode, and S. B. Nielsen, “Simple future weather files for estimating heating and cooling demand,” Build. Environ., vol. 83, pp. 104–114, 2015.

4. S. E. Belcher, J. N. Hacker, and D. S. Powell, “Constructing design weather data for future climates,” Build. Serv. Eng. Res. Technol., vol. 26, no. 1, pp. 49–61, 2005.

5. L. Abdallah and D. El-shennawy, “Evaluation of CO2 emissions from electricity generation in Egypt: Present Status and Projections to 2030.” .



8:48 - 9:06

Multi-criteria optimization of an earth-air heat exchanger based system for several climates of European capital cities.

Arnaud Lapertot, Benjamin Kadoch, Olivier Le Metayer

Aix Marseille Université, CNRS, IUSTI UMR 7343, 13453, Marseille, France

Aim and Approach

(max 200 words)

In Europe, the energy consumed from the heating, air conditioning and ventilation system represents 68 % in the residential sector [1]. The European Union's strategies planned to reduce energy consumption in the building in order to fight global warming. One possible solution is to use Earth-Air Heat Exchangers (EAHE) based on renewable energies. The EAHE is a heating, ventilating and air-conditioning system using outside air flowing through underground tubes to recover energy from the soil [2]. This energy is used to preheat or cool the air in the building by ventilation. Moreover, the addition of a Heat Recovery Ventilation (HRV) [3] improves the performance of the system by recovering the energy lost by the exhaust air. However, the system requires an auxiliary system to satisfy the energy needs [4]. The energy system can also be coupled with a heat pump and photovoltaic collectors in order to satisfy the heating needs in winter and the cooling demands in summer [5]. The main objective is to determine the optimal sizing and regulation of the energy system using an optimization procedure. This one is composed of a sensitivity analysis, a multi-criteria optimization and a decision-making.

Scientific Innovation and Relevance

(max 200 words)

An innovative multi-criteria optimization methodology applied to this EAHE energy system is achieved. The energy system is first dynamically modelled over a full year using several models such as the EAHE, the HRV, the bypass, the building, the heat pump and photovoltaic collectors. The bypass corresponds to the EAHE regulation which allows to have a building temperature as close as possible to the comfort temperature. The regulation operates with four modes: the insufflated air comes from the outside air, the EAHE, the HRV or the coupling EAHE/HRV. Furthermore, a sensitivity analysis, using the FAST method [6], is performed to select the most significant parameters. Then, a multi-criteria optimization study, based on the genetic algorithm NSGA-II [7], is carried out to determine the best compromises. The multiple-criteria decision making TOPSIS method [8] selects the optimal sizing and regulation. Finally, this optimization procedure can be used for different climates of European capital cities which are different in nature due to the diversity of climates in Europe (Mediterranean, oceanic, continental, ...).

Preliminary Results and Conclusions

(max 200 words)

A preliminary study involving different French climates has been performed using the electrical grid to complete the heating and cooling demands. The associated results show that the system operates more frequently with the EAHE in summer and with the coupling EAHE/HRV in winter. The sensitivity analysis reveals that tube radius, tube length, burial depth, air renewal and regulation temperature are the most significant parameters. A multi-criteria optimization study illustrates that when the cost of the energy recovered and the coefficient of performance decrease, the fraction of renewable energy increases. A multiple-criteria decision making method exhibits the optimal parameter values are obtained for a large tube length and air renewal, an average tube radius and a burial depth and a small regulation temperature. The results show even though the system depends on weather conditions, it can achieve high energy performance for several climates. In addition, the energy system combined with a heat pump and photovoltaic collectors allows to avoid the use of auxiliary energy resources from the electrical network. This system satisfies the energy needs because the fraction of renewable energy is close to unity. Finally, the optimized system improves performance compared to the reference case.

Main References

(max 200 words)

[1] L. Pérez-Lombard, J. Ortiz, C. Pout, A review on buildings energy consumption information, Energy and Buildings 40(2008)394–398.

[2] S. Thiers, B. Peuportier, Thermal and environmental assessment of a passive building equipped with an earth-to-air heat exchanger in France, Solar Energy 82(2008)820–831.

[3] H. Li, L. Ni, G. Liu, Z. Zhao, Y. Yao, Feasibility study on applications of an earth-air heat exchanger (EAHE) for preheating fresh air in severe cold regions, Renewable Energy 133(2018)1268–1284.

[4] M. Cuny, A. Lapertot, B. Kadoch, O. Le Métayer, Multi-criteria optimization of an earth-air heat exchanger for different french climates, Renewable Energy 157(2020)42–352.

[5] P. Poulet. R. Outbib. Energy production for dwellings by using hybrid systems based on heat pump variable input power. Applied Energy 147(2015)413-429.

[6] A. Saltelli, M. Ratto, T. Andres, F. Campolongo, J. Cariboni, D. Gatelli, M. Saisana,S. Tarantola, Global Sensitivity Analysis. The Primer, Vol. 304, John Wiley & Sons, 2008.

[7] K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multi-objective genetic algorithm: NSGA-II, Evolutionary Computation 6(2002)182–197.

[8] G.H. Tzeng, J.J. Huang, Multiple attribute decision making: Methods and applications, CRC Press, Taylor and Francis Group, A Chapman & Hall Book, Boca Raton, 2011.



9:06 - 9:24

Control of a state-wide pool of hybrid heat pumps to decrease the GHG emissions of heating

Marianne Biéron1,2, Jérôme Le Dréau1, Benjamin Haas2

1LaSIE (UMR CNRS 7356) - La Rochelle University, La Rochelle, France; 2Engie Lab Future Buildings and Cities, CRIGEN, ENGIE, France

Aim and Approach

(max 200 words)

Decarbonizing space heating and domestic hot water production is a key to cope with climate change as these are mostly provided through fossil fuels and are energy intensive. In our work we focus on the case of France where these usages represent around 25% of the final energy consumption . Since these consumptions are spread over different energy vectors and space heating is highly seasonal, choosing the right vector at the right time is crucial to decarbonize them. Demand side management in buildings is a way to improve the integration of the fatal renewable energies into the power grid and for the interruption of demand for power when the marginal technologies for electricity production are fossil.

According to the French Low Carbon Strategy and its associated Multi Annual Energy Plan, the share of electricity for heating in the used primary energy source should grow and aerothermal heat pumps should be widely spread on the territory. In this article we will therefore consider the control of a pool of hybrid heat pumps supplied with electricity or with green gases (mixed or not with natural gas). The selection of the right energy will be driven by the GHG emissions of the electricity grid.

Scientific Innovation and Relevance

(max 200 words)

In the proposed demand side management strategy the share of gas boilers to activate at each time is optimized in order to minimize the carbon intensity of both electricity and gas consumed during the entire operating time of the hybrid heat-pumps. As the reduction of the consumption of electricity during the activation of the gas boilers influences the electricity grid and thus the level of the GHG emissions, coupling the supply and the demand models is essential. In order to do this, we modeled the French electricity system using an approach inspired by the priority list methods. Due to their low complexity these methods are suitable for real time control of systems. The influence of the change in the electricity production is strongly related to the amplitude, the duration and the time of the variation of the demand, parameters that are not always considered in the marginal emission factors calculation. In this system the marginal GHG emission is the difference between the emission of the overall electric system without gas activation and with activation of a share of gas boilers.

Preliminary Results and Conclusions

(max 200 words)

The developed model for simulation of a national electric system was calibrated and validated for France. The same methodology can be used for other countries. The influence of the heating demand electrification in France and the optimal share of hybrid heat pump in the country has been estimated using this model. The pattern (duration, frequency and amplitude) of the activation of the gas boilers has been estimated in order to minimize the GHG emissions of the energy systems. In our study a first scenario of 50,000 hybrid heat pumps was considered and the aggregated load of the overall pool was simulated. At a later stage the control of one heat pump at a time, at the scale of a single building and the optimal aggregation of these individual heat-pumps will be studied. Our results show a significant positive impact on the current electrical mix, this impact being sensible to the considered GHG intensity of the gas in future and to the number of installed heat-pumps.

Main References

(max 200 words)

Delarue, Erik. (2009). Modeling electricity generation systems. Development and application of electricity generation optimization and simulation models, with particular focus on CO2 emissions.

Delarue, E, Cattrysse, D., & D’Haeseleer, W. (2013). Enhanced priority list unit commitment method for power systems with a high share of renewables.

J. Clauß, C. Finck, P. Vogler-Finck, et P. Beagon, "Control strategies for building energy systems to unlock demand side flexibility – A review, Building Simulation 2017", San Francisco, 7-9 August 2017.

T. Péan, J. Salom, J. Ortiz," Environmental and Economic Impact of Demand Response Strategies for Energy Flexible Buildings", 2018

C. Roux, P. Schalbart, et B. Peuportier, "Development of an electricity system model allowing dynamic and marginal approaches in LCA—tested in the French context of heating in buildings", Int. J. Life Cycle Assess., vol. 22, no 8, p. 1177‑1190, August 2017.

S. Heinen et M. O’Malley, "Power system planning benefits of hybrid heating technologies", in 2015 IEEE Eindhoven PowerTech, 2015, p. 1‑6.

Z. Zheng, F. Han, F. Li, J. Zhu, "Assessment of Marginal Emissions Factor in Power Systems Under Ramp-Rate Constraints". 1(4), 37–49., December 2015



9:24 - 9:42

A machine learning-based methodology for harnessing the energy flexibility potential of residential buildings

Adamantios Bampoulas1,2, Fabiano Pallonetto1, Eleni Mangina1,3, Donal P. Finn1,2

1UCD Energy Institute, University College Dublin, Dublin, Ireland; 2UCD School of Mechanical and Materials Engineering, University College Dublin, Dublin, Ireland; 3UCD School of Computer Science, University College Dublin, Dublin, Ireland

Aim and Approach

(max 200 words)

The current paper aims to develop a data-driven machine learning model to assess the energy flexibility potential of residential buildings based on day-ahead load prediction. The most informative predictors are selected based on random forests and the autocorrelation and Pearson coefficients to forecast the space heating electrical demand of the ground source heat pump (GSHP). The candidate features include weather variables (ambient temperature, solar radiation, etc.), temporal variables (minute of day, day of week, etc.), time-shifted lag values of the GSHP operation (electric load, water tank temperature, water mass flow rate), and the zone thermostat setpoint. The forecasts are produced daily by using the next-day prediction dataset as the testing set, which is based on random forests and a series cross-validation method. This approach emulates practical scenarios for day-ahead energy flexibility prediction. In the full paper, energy flexibility will be assessed from an integrated systems perspective by considering various types of machine learning models and DR events.

The synthetic datasets are generated by utilising a calibrated white-box model of a residential building. The model is developed with EnergyPlus by using a 15-min simulation time-step and comprises inter alia, a 12-kW GSHP coupled with a 0.8 m3 hot water storage tank.

Scientific Innovation and Relevance

(max 200 words)

A key issue in energy flexibility assessment is the lack of a robust and practicable approach to assess the flexibility of residential buildings on a one-by-one basis [1]. The accurate quantification and characterisation of residential building flexibility potential are likely to allow electricity aggregators to evaluate a portfolio of buildings. White-box physical models developed using building simulation tools have been shown to accurately predict baseline and modulated energy consumption [2]. However, energy flexibility depends both on the building thermal dynamics and on time-variant attributes such as occupancy, weather, electrical component mix, and any active storage systems. In contrast to white-box models, data-driven models can be attuned to incoming smart meter data and adapt to these changes without manual intervention. This feature may not only enable customer-tailored model development but also ensure scalability.

Previous studies on machine learning approaches to building load forecasting have been developed for building performance evaluation [3,4], and energy management systems [5]; however, few works develop data-driven models to assess the flexibility potential of residential buildings. Preliminary results show that a priori knowledge of zone thermostat setpoints, as well as the use of the GSHP operation and zone temperature time-shifted values, shape the day-ahead power profile forecast.

Preliminary Results and Conclusions

(max 200 words)

The adopted thermostatic setpoint is based on a daily average occupancy profile resulting from a UK Time Use Survey [6]. 35 candidate variables were selected, based on data that an energy management system could measure, including variables related to weather, occupancy, and the GSHP operation. By using the Pearson coefficient for one heating season it is shown that the water tank temperature (WT(t)), the water mass flow rate (MFR(t)), the zone thermostat setpoint (TH_SET(t)), and the zone temperature (ZT(t)) exhibit the highest correlation; nevertheless, only the TH_SET(t) can be used directly as a predictor. The lag terms, from the GSHP power and the WT(t), MFR(t), ZT(t) exhibiting the highest autocorrelation, are selected as candidate features and random forests are used both to assess feature importance and train the model.

Based on a parametric analysis and the daily root mean square error (RMSE), the optimal feature number is 11. A weekly simulation has shown that the average daily RMSE is 164 W and the model generalises better for weekdays (RMSE=141W) compared to weekend days (RMSE=221W). The TH_SET(t) is the most meaningful feature while the optimal feature set also comprises a series of the GSHP operation lag terms and the ambient temperature.

Main References

(max 200 words)

1. G. Krishnadas and A. Kiprakis. A Machine Learning Pipeline for Demand Response Capacity Scheduling. Energies, 2020, doi: 10.3390/en13071848

2. G. Reynders, J. Diriken, D. Saelens. Generic characterization method for energy flexibility: Applied to structural thermal storage in residential buildings. Applied Energy, 2017 URL: https://doi.org/10.1016/j.apenergy.2017.04.061

3. A. Attanasio, M. Savino Piscitelli, S. Chiusano, A. Capozzoli, T. Cerquitelli, Towards an Automated, Fast and Interpretable Estimation Model of Heating Energy Demand: A Data-Driven Approach Exploiting Building Energy Certificates. Energies 2019, URL: https://doi.org/10.3390/en12071273

4. Y. Guo, J. Wang, H. Chen, G. Li, J. Liu, C. Xu, R. Huang, Y. Huang, Machine learning-based thermal response time ahead energy demand prediction for building heating systems. Applied Energy, 2018, URL: https://doi.org/10.1016/j.apenergy.2018.03.125

5. D. Zhang, S. Li, M. Sun, and Zheng O’Neill, "An Optimal and Learning-Based Demand Response and Home Energy Management System," IEEE Transactions on Smart Grid, vol. 7, no. 4, pp. 1790-1801, 2016, doi: 10.1109/TSG.2016.2552169.

6. G. Buttitta, D. P. Finn, “A high-temporal resolution residential building occupancy model to generate high-temporal resolution heating load profiles of occupancy-integrated archetypes,” Energy & Buildings, 2020, https://doi.org/10.1016/j.enbuild.2019.109577



9:42 - 10:00

Simulation based evaluation of building integrated solar envelope systems on building level

Fabian Ochs1, Mara Magni1, Martin Hauer2, Samuel De Vries3, Paolo Bonato4

1University of Innsbruck, Austria; 2Bartenbach, Austria; 3TUe, The Netherlands; 4Eurac Research, Italy

Aim and Approach

(max 200 words)

“Building Integrated Solar Envelope Systems for HVAC and Lighting” were investigated within IEA SHC Task 56 by means of literature review, workshops, laboratory tests, onsite monitoring as well as dynamic building and system simulation. A solar envelope consists of elements that use and/or control solar energy and deliver renewable thermal and/or electric energy to the building HVAC system providing heating, cooling and ventilation, and/or daylighting control. For the detailed technical and economic analysis of these solar façade systems on building level, building and HVAC simulations were performed using reference buildings. Furthermore, experience from demo projects were included in the analysis.

An integral and systemic approach is required to promote solar envelopes integrated into the building’s HVAC and lighting systems. Both, residential and tertiary buildings (office, school, library) as well as new-built and retrofitted ones were considered. The energy performance, primary energy savings, indoor air quality, thermal and visual comfort as well as architectural integration were investigated on component and on building level. Virtual case studies were examined using several cross-validated calculation and simulation platforms and for three European climates (cold: Stockholm, moderate: Stuttgart, warm: Rome), representing heating and cooling dominated climates as well as different solar potential.

Scientific Innovation and Relevance

(max 200 words)

The European Commission requests that member states implement nZEB (EPBD) requirements applying from 2021 on, enabling buildings with very low energy demand due to efficient building envelopes and HVAC systems as well as RE integration on a cost-optimal level.

This contribution focuses on simulation-assisted evaluation of the cost-optimal level. Techno-economic analysis is performed using different building and HVAC models that were previously cross-validated. (Pre-) Design calculation tools as well as dedicated simulation platforms (TRNSYS, E+, Modellica, Matlab) were used for the virtual case studies. A sensitivity analysis as well as multi-objective optimization was performed.

The evaluation was extended to monthly primary energy factors accounting for different scenarios for the future electricity mix, i.e. with different RE shares (hydro, wind, PV). The cost-intensity (€/saved kWh) was used as a performance indicator to compare cost-optimal solution integrating high shares of RE into buildings. The comparison was extended to different European countries allowing to compare possible PE savings and additional costs to achieve these primary energy savings. For certification of buildings, simplified, fast and easy to use methods are required, contrariwise, only dynamic simulation models allow a realistic prediction of e.g. the PV self-consumption considering thermal mass and (thermal/electric) storage.

Preliminary Results and Conclusions

(max 200 words)

For all virtual case studies, primary energy savings and the capitalized total annual costs were evaluated. A techno-economic analysis of different technologies including passive components (envelope, mechanical ventilation with heat recovery (MHVR), shower drain water recovery (SDWR)), active components (heat pump) and renewables (BI-ST, -PV, -PVT) was performed. Cost-optimal solutions based on suitable combinations of passive and active technologies can be identified depending on the climate and type of building i.e. residential buildings and non-residential buildings as well as application (heating, cooling, DHW, lighting, appliances). The cost efficiency of different technologies was evaluated vs. their primary energy savings. The investigated virtual cases of solar façade systems show the potential of integrating passive and active solar technology. A methodology was developed to analyse and compare different solutions. The capitalized life cycle costs per saved kWh of PE of different passive and active technologies are plotted vs. the primary energy, or primary energy savings, respectively. Based on the presented results design guidelines can be elaborated. Furthermore, the investigated numerical models can be used in future work to further foster and optimize solar façade systems.

Main References

(max 200 words)

Magni, M.; Ochs, F.; Bonato, P.; D'Antoni, M.; Geisler-Moroder, D.; de Vries, S.; Loonen, R-; Maccarini, A.; Afshari, A.; Calabrese, T. (2019): Comparison of simulation results for an office building between different BES tools: the challenge of getting rid of modeller Influence and Identifying Reasons for deviations. IBPSA., Rome, 2019.

Calabrese T., Ochs F., Siegele D., Dermentzis G., Potential of covering electricity needs of a flat of a MFH with decentral compact heat pumps with PV – Simulation study for different DHW profiles and PV field sizes, EuroSun 2018, Rapperswil

D’Antoni M., Geisler-Moroder D., Bonato P., Ochs F., Magni M., de Vries S., Loonen R., Fedrizzi R., Definition of a reference office building for simulation based evaluation of solar envelope systems, EuroSun 2018, Rapperswil

Ochs, F.; Dermentzis, G. (2018): Evaluation of Efficiency and Renewable Energy Measures Considering the Future Energy Mix. In: 7th IBPC, Syracuse, 2018.

Taveres-Cachat E., Goia F. Grynning S., „Solar efficiency index of building envelopes and load matching in low energy buildings,“ in 7th IBPC, Syracuse, 2018.

Dermentzis G., Ochs F., Passive House with PV façade and electric heating, Low costs and minimal installation effort vs. Performance, PV potential and evaluation of PE consumption, ABS 2018, Bern.



 
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