bluuebunny/crossref_metadata_2025_split huggingface dataset:
E-DYCE - Dynamic approach to the dynamic energy certification of buildings
Authors: Larsen O K , Pomianowski M Z , Chiesa G , Belias E , de Kerchove d’Exaerde T , Flourentzou F , Fasano F , Grasso P 
Published: December 2023

Abstract
The energy performance certification (EPC) scheme, introduced in the European Union approximately 20 years ago, has become the focus of the upcoming revision of the Energy Performance of Buildings Directive (EPBD). Despite its widespread use, the current EPC scheme has several shortcomings that need to be addressed. The Energy flexible DYnamic building Certification (E-DYCE) project has developed a dynamic approach to address these issues. The methodology includes a dynamic assessment of a building’s energy needs and comfort conditions under standard and different from standard conditions of building use to support Performance Gap (PG) analyses. The E-DYCE approach includes a dynamic building performance simulation with comfort and energy-related key-performance indicators (KPIs) measured and calculated according to E-DYCE DEPC methodology. These KPIs can inform end-users about indoor environmental quality conditions decisive for building energy performance, aid building managers in detecting dysfunctions resulting in PG, and include energy performance indexes for heating, cooling, lighting, domestic hot water, and more. Overall, the E-DYCE approach offers dynamic, reliable, and customer-tailored information and optimization possibilities to end-users while potentially resolving known shortcomings of the existing EPC schemes.
Thermochemical storage networks for integration of renewable energy sources through seasonal load shifting
Authors: Baldini Luca , Zambrano Juan Mahecha 
Published: December 2023

Abstract
Thermochemical networks are a rather new subject in research and support our goal to lower winter electricity demand and foster the integration of renewable energy sources. This paper takes a first step towards a performance analysis of thermochemical networks and a comparison to a classical district heating network for a virtually defined network of 1.3 km length, assuming a space heating load of 204.7 MWh represented by 33 residential buildings. The performance comparison is done for winter operation when space heating demand is present. The simulation results clearly revealed that for the classical district heating system, thermal and pressure losses lead to a significant increase in the loads, further increasing the electricity demand for the heat pump and the circulation pump. Conversely, for the thermochemical network, no compressor is needed to extract the heat from the boreholes and the circulation of the sorbent solution was found to be minute, leading to a negligible electricity demand for space heating supply. This resulted in a very high electric COP as well as a high exergy efficiency compared to a classical district heating system. Further, the volumetric energy storage density was compared, recording a 2 to 22.3 times higher value for the thermochemical network.
Solar potential on facades at urban scale: an integrated approach combining solar and digital building modelling
Authors: Desthieux G , Gressin A , Raybaud B , Ingensand J 
Published: December 2023

Abstract
The paper presents an integrated approach to improve the solar radiation modelling on facades in large-scale built-up areas. The modelling of the built environment must first be improved in terms of level of detail. Thus, from aerial oblique images, a digital twin of the urban scene is created, allowing to process the facades as textured objects and to detect windows using an artificial intelligence image processing. Reflected radiation is significant on vertical surfaces, but complex to model on large areas. The developed model is based on a simplified radiosity approach, which reduces the volume of analysis, storage and thus the computation time, while producing reliable results. A demonstration of the integrated tool is presented for an urban area in Geneva (1 km2), including a solar energy balance assessment for one of the buildings using the results from the solar modelling. The perspective is to generalise the approach to a larger scale and to complete the solar cadastre of the roofs of the Greater Geneva area with the facades.
Experimental energy performance in electrified renewable energy-sharing community
Authors: Kim Min-Hwi , Kim Haneol , Kim Jong-Kyu , Ahn Young-Sub 
Published: December 2023

Abstract
In this study, the empirical results of renewable energy self-sufficiency for communities consisting of residential and nonresidential buildings were analyzed. These buildings were combined with a grid-connected electrified community. The community was primarily powered by building-integrated photovoltaic (BIPV) systems, and cooling and heating water were supplied by geothermal and hydrothermal source heat pump systems. The community building comprised 56 detached houses and two office buildings. The community’s primary electricity generation was provided by a 500 kWp BIPV, approximately 7.1 kWp installed per household. This community had facilities that provided cooling, heating, and domestic hot water from heat supply stations. Thermal energy for cooling and heating was mainly generated by geothermal and sewage water-source heat pumps, stored in a daily heat storage tank, and supplied to households. Based on the analysis using ISO 13790-based software, the cooling and heating requirements were 51 and 42 kWh/m2, respectively. The cooling and heating requirements were 49 and 44 kWh/m2, and a difference of approximately 5% between the simulation and experiment results was observed. Consequently, the annual zero-net energy balance was 138.2% when the plug load was excluded but 46.8% when the plug and electric-vehicle electricity loads were included.
Analysing energy use clusters of single-family houses using building and socio-economic characteristics
Authors: Schaffer M. , Hansen A. R. , Vera Valdés J.E. , Marszal-Pomianowska A. 
Published: December 2023

AbstractClustering has been shown to be a promising approach to reduce the large amount of data from smart heat meters to representative profiles. However, attempts to understand why a case (building including its occupants) is within a particular cluster have only been moderately accurate. Therefore, this work uses existing energy use clusters based on about 4500 single-family homes to investigate whether socio-economic characteristics (SECs) alone or in combination with building characteristics (BCs) can improve the insight into the energy use clusters. An established variable selection and classification approach based on random forests was used. The results show that the eight SECs used alone provide poor insight into the energy use clusters, achieving only a Matthew Correlation Coefficient (MCC) of around 0.1. Simplifying the energy use clusters based on similarities, which was successful in the past, only moderately increased the MCC (≈ 0.17). When combined with BCs, SECs were never selected by the algorithm used, showing that they do not lead to a (significant) increase in MCC for both unsimplified and simplified clusters. Thus, this work suggests that SECs do not provide additional insights into why a case is within its respective energy use cluster.
Making an air-source heat pump smart-grid ready
Authors: Thorsteinsson S , Cai H , Bendtsen J D , Heer P , Vivian J 
Published: December 2023

Abstract
In this paper we discuss the differences between the industrial and academic definition of smart-grid readiness of heat pumps and investigate possibilities to bridge this gap such that existing heat pumps, to a higher degree, can participate in a smart-grid or flexibility setting. A weather compensated heat pump has been equipped to enable heating reference tracking by overriding the outdoor air temperature measurement. The reference tracking has been performed using a model predictive controller and a PI-controller. The results show that it is possible to track a heating reference but also that operating the heat pump according to smart-grid objectives has consequences, such as reduced COP and increased defrosting rate. The model predictive and PI-controller showed little difference in performance, meaning that even simple rule-based controllers can be used for tracking. Lastly, the paper provides suggestions for signals that should be available if heat pumps in the future should operate closer to the researchers’ expectations of smart-grid readiness.
Sensitivity analysis of fifth generation district heating and cooling coupled with borehole thermal energy storage with respect to cooling adoption
Authors: Li Xiang , Chambers Jonathan , Yilmaz Selin , Patel Martin K. 
Published: December 2023

Abstract
Fifth generation district heating and cooling (5GDHC) is a promising solution for decarbonising building thermal demands, as it allows for simultaneous heating and cooling through a bi-directional network. This paper aims to investigate the general performance of 5GDHC under uncertainty. Initially, an uncertainty analysis is performed on a 5GDHC model in a case study, revealing significant variation in economic, technical, and environmental performance due to uncertain parameters. Subsequently, variance-based global sensitivity analysis is used to rank the uncertain parameters based on their impact on the economic performance of 5GDHC. The results identify cooling adoption rate, borehole pricing, and discount rate as the most influential parameters. Lastly, factors mapping demonstrates that cooling adoption rate within 0.6-0.9, low borehole costs, low discount rates, and high gas prices will drive the switch to 5GDHC. Overall, this study emphasizes the general applicability of 5GDHC.
Performance analysis and optimization of a solar assisted heat pump concept
Authors: Frappé Mathieu , Mora Laurent , Sempey Alain , Viot Hugo , Hubert Tessa 
Published: December 2023

Abstract
Solar-assisted heat pumps have become a popular choice for efficient and environmentally-friendly heating and hot water production. This article introduces a unique concept of integrating a solar thermal facade into buildings to provide the cold source for a heat pump, which is a novel approach compared to other available solutions. While accurate sizing is crucial for efficient system operation, evaluating the potential benefits of better control strategies is also important because these strategies can bring significant benefits to the system. However, at present, there is a shortage of tools that can facilitate accurate sizing and effective evaluation of various control strategies for such systems. This article explores the benefits and challenges associated with this innovative technology, highlighting the need for developing models with a good representation of the system behavior and accurate performance estimation. A parametric study will be conducting on the principal components sizing for various climates in France. The aim is to gain a comprehensive understanding of the installation’s potential performance, with the optimization of sizing and control strategies to be performed at a later stage.
Comparison of different deep neural networks for system identification of thermal building behavior
Authors: Gölzhäuser Simon , Frison Lilli 
Published: December 2023

Abstract
Having accurate information available about future thermal building behavior can help to make good decisions in various heating control tasks. However, creating precise mathematical models for many different buildings is a complex and time-consuming task, owing to the heterogeneity of the building stock and the behavior of its occupants. In this paper, we propose a DNN-based system identification approach for predicting the room temperature inside a building based on past information and future weather forecasts. We evaluate various state-of-the-art and custom-built DNN architectures for TSF. Besides prediction performance, storage space and inference speed as measures for the respective model’s complexity are also taken into account. Our main contribution is demonstrating the effectiveness of these models in predicting the room temperature for differently parameterized simulated buildings. By using several distinct buildings for training, validation and testing, we additionally show that these models are capable to generalize in a way such that the room temperature for different buildings can be predicted by a single model, without any changes or adaptions.
How good is the advice from ChatGPT for building science? Comparison of four scenarios
Authors: Rysanek Adam , Nagy Zoltan , Miller Clayton , Dilsiz Aysegul Demir 
Published: December 2023

Abstract
This paper resulted from several questions discussed between its human authors shortly after the public launch of OpenAI’s ChatGPT:
Can a language model, trained on an unimaginably vast database, be able to resolve fundamental data inference and data-driven forecasting problems which have been ’typical’ research fare in the building science domain? Is it possible that research problems which ’typically’ require user-intensive tools, such as building performance simulation and problem-specific machine learning models, can today be addressed by ChatGPT in a manner of seconds? If so, what does this mean for the future of building science, let alone the writing of novel research contributions in academia?
The entirety of this paper was produced with significant use of ChatGPT. Four arbitrarily-selected case studies were extracted from recent peer-reviewed journals and reputable sources. ChatGPT was tasked with attempting to infer the same results as the publications using only each case study’s input data. Not only were ChatGPT’s results found to be relatively credible, ChatGPT was able to communicate its results instantly and in an academic language. From start to finish, the entirety of this paper, from initial brainstorming to final editing, was completed in no more than 8 human-hours by the study’s (human) authors. The content of this paper is original and has not been published previously.
Modeling uncertainty in positive energy districts through a non-probabilistic approach
Authors: Shamsi Mohammad Haris , Kouti Amin , Ma Yixiao , Engelen Lukas , Sharifi Mohsen 
Published: December 2023

Abstract
Positive Energy Districts (PEDs) transcribe an emerging energy transition paradigm for rapid upscaling of building energy efficiency programs to match the urgency of climate mitigation and adaptation. PEDs facilitate pro-active sharing of information and experiences, responsive learning and dissemination, and cooperation across sectors and disciplines. The rapid evolution of technologies for energy efficiency and integration of renewable energy in buildings requires a research-to-design approach. Therefore, it is imperative that a designer makes informed decisions at an early stage of design from an energy-efficiency perspective. However, since PED design involves a significant number of stakeholders, the design parameters could be highly uncertain, which eventually affect the quality of the design solution space. This study uses a bilateral process workflow to quantify risks using a nonprobabilistic technique and a PED roadmap structure. The workflow evaluates different PED scenarios and quantifies the PED potential for the city of Sint-Niklaas in Belgium. The results indicate that risk quantification significantly improves PED decision-making when evaluating collective solutions (district heating) for a district.
Assessing pathways to carbon neutrality in a neighbourhood study in Germany
Authors: He Miaomiao , Nemeth Isabell , Blumenthal Astrid von , Haupt Thomas , Stopper Jochen , Jungwirth Johannes 
Published: December 2023

Abstract
Neighbourhoods are becoming more and more important for the success of the energy transition and achieving the climate protection goals. This paper describes results from a case study of a typical residential neighbourhood in Germany, in which investigation of pathways to climate neutrality has been carried out. Both technical potential and challenge under the current legal framework are presented. The aims are to answer questions such as to what extent and in what sequence the energy-related emissions of an existing neighbourhood can be reduced in the long term through further integration of photovoltaics, low-carbon technology, thermal storage and, if necessary, building refurbishment. Two pathways are exanimated: in the gas pathway by using CHP units with biogas and in the electricity pathway by electrifying the heat demand through the use of heat pumps. Three scenarios are defined for both pathways, which differ in particular by the level of building refurbishment, PV generation, supply temperatures in the heating network and uptake of electric vehicles.
Optimization of a ventilation system integrated into a window frame using CFD simulations
Authors: Karolin J. , Rahiminejad M. 
Published: December 2023

Abstract
A decentralized ventilation system has the potential to decrease the pressure drop in a ventilation system and consequently, increase the efficiency of the system and building skin. Including a decentralized ventilation system in a window cavity allows independent regulation of the fresh air quality in each room and can be easily installed without any additional brickwork. In this study, a novel ventilation system integrated into a window-frame is examined and the most critical region regarding pressure drop is identified using computational fluid dynamic (CFD) simulations. The entire fresh air channel including the optimized section is compared with the original volume regarding system resistance and satisfaction of the required airflow according to Swiss standards. The results suggest a relocation of the restricting control unit and an increased cross-section to decrease the air velocity and the pressure drop. The simulations predicted that the required airflow for sufficient indoor air quality is exceeded using the optimized geometry.
A database for positive energy districts (PED)
Authors: Alpagut B , Bossi S , Civiero P , Diaz S , Gollner C , Haase M , Kuzmic M , Sanchez N , Seco O C , Soutullo Castro S , Turci G , Zamini S 
Published: December 2023

Abstract
The development of Positive Energy Districts (PEDs) is a complex process that involves the integration of various technologies, stakeholders, and policies. To facilitate this process, a database for PEDs has been developed as a joint effort of COST Action ‘PED-EU-NET’, IEA EBC Annex 83, and JPI Urban Europe. This paper reports on the realization of the PED-Database framework and its online implementation as a modular web interoperable platform, giving details on the development life cycle since the scoping phase up to the testing phase. The PED-Database offers a variety of implementation strategies and conceptualizations for the PED concept, making it a valuable resource for urban planners, policymakers, and researchers. The testing phase has shown that there is no one-fits-all solution for PED implementation, and the overall PED framework definitions require further detailing in the local context. However, the database allows users to visualize and compare different PED scenarios by customizing their selection, accessing to the information provided by real PED cases that best meets their expectations and goals. Overall, the PED-Database provides a valuable tool for the development of sustainable and energy-efficient urban areas.
Method combining expert and analytical approaches towards economical energy renovation roadmaps and improved indoor comfort
Authors: Pomianowski M Z , Wittchen K , Schaffer M , Hu Y , Chiesa G , Fasano F , Grasso P 
Published: December 2023

Abstract
This paper proposes a two-fold method, combining expert and analytical approaches, to develop an energy renovation roadmap for residential apartment buildings. The expert approach provides cost estimates based on energy performance certificates, considering the building’s existing condition, national building tradition, and requirements. Renovation actions are limited to the most probable and required actions. The analytical approach uses computer power and various renovation action variations to identify optimal solutions for defined KPIs. As the cost efficiency of energy conservation action depends on model complexity, the expert approach considers this aspect. The analytical approach focuses on indoor comfort and energy use, as cost optimality evaluation is not possible for non-linear costs of energy conservation actions. Sensitivity analysis is used to support credible ranges for rentability of energy conservation measures and reflect on optimal solutions and indoor environmental consequences.
Comparison of supervised algorithms for automated data analysis in existing buildings
Authors: Stinner Florian , Kümpel Alexander , Müller Dirk 
Published: December 2023

Abstract
Non-residential buildings are equipped with building automation systems (BAS). BAS provide a vast amount of building operation data. However, the analysis of this data is laborious and requires a scalable and automated process. The authors developed the BUDO schema for a standardized, object-oriented description of monitoring metadata. The translation process employs artificial intelligence to translate the properties of data streams (labels, time series) from BAS into the BUDO schema. The translated data is then analyzed using various applications to detect inefficiencies, such as incorrect placement of outdoor temperature sensors or a weekend shutdown that has not been properly implemented. The paper presents a process that automatically translates, structures and analyzes operational data to identify potential for energy savings. The OOM4ABDO project monitors 138 buildings to analyze and improve building operations, whose subset of data we are using here. In addition, we use an open source data set of about 70 buildings. We compare several feature extraction methods and classifiers on their ability to support each of the stages (label translation, time series translation, application). The algorithms used reach F1 scores of up to 98% for label translation, 90% for time series translation and 92% for applications.
Effect of built form on local wind characteristics, a case of tropical savanna climate in India
Authors: Dev Govind , Saifudeen Aysha , Anurup K , Chacko Bijoy 
Published: December 2023

Abstract
Passive techniques play a substantial role in regulating the indoor environmental quality of a building, especially in the tropics. Proper air movement is necessary for warm and humid indoors by utilising the local wind pattern. Many factors influence and alter the wind character of a region. Any built form has a significant influence on the wind and vice versa. This research extensively studies the effects of wind when it encounters different built and unbuilt spaces of an office building in India’s tropical savanna climate. Applications such as Building Information Modelling (Autodesk Revit) and Computational Fluid Dynamics simulation (Autodesk CFD) are used for analysis. The impacts on the local wind character at chosen wind path timings are studied in detail to arrive at the conclusions. Various effects like wind acceleration, corner jetting, channelling, funnelling, windbreak and cumulative effects are observed as occurring due to the influence of the building’s form on the local wind. These effects increased the wind velocity from 10kmph up to 19kmph and decreased up to 6kmph. The study concludes by arriving at several considerations while developing built forms that help to reduce negative impacts and improve positive impacts on aspects like aerodynamics, user comfort, impact on surroundings, the microclimate and structural wind loads.