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Energy Efficiency through Building Simulation

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "G: Energy and Buildings".

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 6788

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Special Issue Editors

Dr. Jérôme Frisch

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Guest Editor

Energy Efficient and Sustainable Building E3D, RWTH Aachen University, Mathieustr. 30, 52074 Aachen, Germany
Interests: building performance simulation; numerical analysis; algorithmic development; high-performance computing; fluid flow simulations
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Rita Streblow

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Guest Editor

Einstein Center Digital Future, TU Berlin, Berlin, Germany
Interests: energy system optimization; digital energy neighborhoods; thermal comfort

Special Issue Information

Dear Colleagues,

By the 1960s, simulation tools were already being used in the area of building simulation. Since then, programs have been continuously developed and adapted in many different areas ranging from thermal simulations to acoustics and daylight simulations. With rising computational capabilities and with both new emerging methods and existing methods adapted to the area of building performance simulation, such as artificial intelligence, new and exciting research fields can be tackled which were unfeasible a few years ago.

We cordially invite you to submit your current research to this Special Issue, focusing on energy efficiency in building simulations concerning the performance of single buildings up to district level. This includes (but is not limited to) research in the area of building performance simulation, energy efficiency in general, energy simulations in building environments, indoor thermal comfort simulations and applications, building services and appliance simulation, occupant behavior in buildings, building information modelling coupled with simulations, computational fluid dynamics simulations for indoor environment settings, energy-saving and optimization efforts in building domains, energy distribution in buildings and districts, and applications of artificial intelligence in building simulation contexts. Focus should also lie on the validation and verification of the selected methods in terms of methodological approach as well as data coherency.

You are invited to present your new methodologies and are asked to state your contribution to knowledge with your research paper. We are looking forward to your contributions!

Dr. Jérôme Frisch
Prof. Dr. Rita Streblow
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

building performance simulation
energy efficiency
energy simulations in building environments up to district level
indoor thermal comfort simulations and applications
building services and appliance simulation
occupant behavior in buildings
building information modelling
optimization efforts in building domains
validation and verification of simulation methods and data

Published Papers (6 papers)

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Research

12 pages, 429 KiB

Open AccessArticle

An Automated Machine Learning Approach towards Energy Saving Estimates in Public Buildings

by Felix Biessmann, Bhaskar Kamble and Rita Streblow

Energies 2023, 16(19), 6799; https://doi.org/10.3390/en16196799 - 25 Sep 2023

Cited by 1 | Viewed by 1071

Abstract

Reducing the energy consumption of buildings in the public sector is an important component in our efforts towards reaching our sustainability goals. In this context, a decisive prerequisite for administrations and policy makers is a tool for estimating the effectiveness of measures to reduce energy consumption. Estimating the impact of planned investments in building technology at scale, however, remains challenging, mainly for two reasons. For one, accurate physical modeling requires detailed building data, which can be difficult to obtain. Second, adapting established building models to novel measures aiming at energy consumption reduction is difficult. Hence, modeling building consumption patterns after retrofitting is a non-trivial task, and more research is needed to improve modeling techniques as well as to assess their effectiveness across a wide range of application scenarios. Modeling tools need to be generic enough to enable modeling of a variety of building types, they should ideally require as few input features as possible and they should allow for a high degree of automation in the selection and calibration of building modeling tools. Here, we propose a novel machine learning approach that does not require detailed building data and can automatically adapt to retrofitting measures. We evaluate our method on a data set of 113 public buildings in 4 building categories in Berlin, Germany. The data set contains energy consumption data in the initial state and after implementation of a weather-predictive heating control system. Despite being fully automated and requiring only minimal information about the building, our model can reliably predict the energy consumption of large public buildings better than established methods. All code and data are publicly released. Full article

(This article belongs to the Special Issue Energy Efficiency through Building Simulation)

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18 pages, 7233 KiB

Open AccessArticle

Advances in the Co-Simulation of Detailed Electrical and Whole-Building Energy Performance

by Stephen Frank, Brian Ball, Daniel L. Gerber, Khanh Cu, Avpreet Othee, Jordan Shackelford, Omkar Ghatpande, Richard Brown and James Cale

Energies 2023, 16(17), 6284; https://doi.org/10.3390/en16176284 - 29 Aug 2023

Viewed by 710

Abstract

This article describes recent co-simulation advances for the simultaneous modeling of detailed building electrical distribution systems and whole-building energy performance. The co-simulation architecture combines the EnergyPlus^® engine for whole-building energy modeling with a new Modelica library for building an electrical distribution system model that is based on harmonic power flow. This new library allows for a higher-fidelity modeling of electrical power flows and losses within buildings than is available with current building electrical modeling software. We demonstrate the feasibility of the architecture by modeling a simple, two-zone thermal chamber with internal power electronics converters and resistive loads, and we validate the model using experimental data. The proposed co-simulation capability significantly expands the capabilities of building electrical distribution system models in the context of whole-building energy modeling, thus enabling more complex analyses than would have been possible with individual building performance simulation tools that are used to date. Full article

(This article belongs to the Special Issue Energy Efficiency through Building Simulation)

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22 pages, 3388 KiB

Open AccessFeature PaperArticle

Automated Generation of Energy Profiles for Urban Simulations

by Tobias Maile, Heiner Steinacker, Matthias W. Stickel, Etienne Ott and Christian Kley

Energies 2023, 16(17), 6115; https://doi.org/10.3390/en16176115 - 22 Aug 2023

Viewed by 878

Abstract

Urban simulations play an important role on the way to a climate neutral society. To enable early assessment of different energy concepts for urban developments, energy profiles for different building types are needed. This work describes the development and use of a new engineering tool GenSim to quickly and reliably generate energy profiles for urban simulations and early building energy predictions. While GenSim is a standalone tool to create energy profiles for early design assessment, it was developed in the context of urban simulations to primarily support energy efficient urban developments within Germany. Energy engineers quickly embraced the tool due to its simplicity and comprehensible results. The development of the tool was recently switched to open source to enable its usage to a broader audience. In order to foster its development and use, a detailed testing framework has been established to ensure the quality of the results of the tool. The paper includes a detailed validation section to demonstrate the validity of the results compared to a detailed building energy simulation model and actual measured performance data. Full article

(This article belongs to the Special Issue Energy Efficiency through Building Simulation)

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19 pages, 425 KiB

Open AccessArticle

Modernization Roadmaps for Existing Buildings under Limited Energy Resources and Craftwork Capacities

by Jan Richarz, Nico Fuchs, Dominik Hering and Dirk Müller

Energies 2023, 16(12), 4822; https://doi.org/10.3390/en16124822 - 20 Jun 2023

Cited by 1 | Viewed by 1182

Abstract

Great potential for saving carbon emissions lies in modernizing European buildings. Multi-year modernization roadmaps can plan modernization measures in terms of time and are able to consider temporal interactions. Therefore, we have developed a mixed-integer program that determines modernization roadmaps. These roadmaps include changing the energy supply system, improving the envelope, and considering annually varying boundary conditions. High craftwork capacities are required to implement the necessary modernizations to meet climate goals. Unfortunately, studies showed that the current shortage of craftworkers will intensify in the next years. Other important limitations correspond to energy resources. Recent crises show that many energy systems need to handle these limitations. Therefore, we extended the mixed-integer program by a method to handle these limitations inside the roadmaps. By the use of data from 90 interviews with craftwork specialists about the time needed to realize modernization measures, the method is applied. The main purpose is to analyze how modernization strategies change under limited resources, especially in terms of craftwork capacities. Hence, the method is exemplified by a representative single-family dwelling. Within this use case, modernization roadmaps with different craftwork capacity levels were calculated. The results show that modernization roadmaps change comprehensively over these levels. Key findings are that costs and emissions rise with decreasing craftwork capacities. Furthermore, smaller storages and pv systems are implemented at low craftwork capacities. The electrification of the heat supply supported by medium insulation standards should also be implemented with limited craftwork capacities. Full article

(This article belongs to the Special Issue Energy Efficiency through Building Simulation)

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15 pages, 2736 KiB

Open AccessArticle

Thermal Performance Optimization Simulation Study of a Passive Solar House with a Light Steel Structure and Phase Change Walls

by Lei Cheng, Chunlong Zhuang, Shengbo Li, Guangqin Huang, Hongyu Zhang, Fei Gan, Ningge Xu and Shanshan Hou

Energies 2023, 16(9), 3725; https://doi.org/10.3390/en16093725 - 26 Apr 2023

Cited by 4 | Viewed by 953

Abstract

Phase change materials are used in passive solar house construction with light steel structure walls, which can overcome the problems of weak heat storage capacity and poor utilization of solar heat and effectively solve the thermal defects of light steel structure walls. Based on this, on the basis of preliminary experimental research, this study further carried out theoretical analysis and simulation research on the thermal performance of a light steel structure passive solar house (Trombe form) with PCM walls. Through the heat balance analysis of heat transfer in the heat collecting partition wall, the theoretical calculation formula of the phase change temperature of the PCM was obtained, and it verified theoretically that the phase change temperature value should be 1–3 °C higher than the target indoor air temperature. The evaluation index “accumulated daily indoor temperature offset value” was proposed for evaluating the effect of phase change materials on the indoor temperature of the passive solar house, and “EnergyPlus” software was used to study the influence of the phase change temperature, the amount of material, and the thickness of the insulation layer on the indoor air temperature in a natural day. The results showed that there was a coupling relationship among the performance and between of the thickness of the PCM layer and the phase change temperature. Under typical diurnal climate conditions in the northern Tibetan Plateau of China, the optimal combination of the phase change temperature and the layer thickness was 17 °C and 15 mm, respectively. Especially at a certain temperature, excessive increases in the thickness of the phase transition layer could not improve the indoor thermal environment. For this transition temperature, there exists an optimal transition layer thickness. For a Trombe solar house, the thickness of the insulation layer has an independent impact on indoor temperature compared to other factors, which has an economic value, such as 50 mm in this case. In general, this paper studied the relationship between several important parameters of the phase change wall of a solar house by using numerical simulation methods and quantitatively calculated the optimal parameters under typical meteorological conditions, thus providing a feasible simulation design method for similar engineering applications. Full article

(This article belongs to the Special Issue Energy Efficiency through Building Simulation)

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24 pages, 4726 KiB

Open AccessArticle

Calibrating the Dynamic Energy Simulation Model for an Existing Building: Lessons Learned from a Collective Exercise

by Adriana Angelotti, Livio Mazzarella, Cristina Cornaro, Francesca Frasca, Alessandro Prada, Paolo Baggio, Ilaria Ballarini, Giovanna De Luca and Vincenzo Corrado

Energies 2023, 16(7), 2979; https://doi.org/10.3390/en16072979 - 24 Mar 2023

Cited by 1 | Viewed by 1310

Abstract

Calibration of the existing building simulation model is key to correctly evaluating the energy savings that are achievable through retrofit. However, calibration is a non-standard phase where different approaches can possibly lead to different models. In this study, an existing residential building is simulated in parallel by four research groups with different dynamic simulation tools. Manual/automatic methodologies and basic/detailed measurement data sets are used. The calibration is followed by a validation on two evaluation periods. Monitoring data concerning the windows opening by the occupants are used to analyze the calibration outcomes. It is found that for a good calibration of a model of a well-insulated building, the absence of data regarding the users’ behavior is more critical than uncertainty on the envelope properties. The automatic approach is more effective in managing the model complexity and reaching a better performing calibration, as the RMSE relative to indoor temperature reaches 0.3 °C compared to 0.4–0.5 °C. Yet, a calibrated model’s performance is often poor outside the calibration period (RMSE increases up to 10.8 times), and thus, the validation is crucial to discriminate among multiple solutions and to refine them, by improving the users’ behavior modeling. Full article

(This article belongs to the Special Issue Energy Efficiency through Building Simulation)

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