bluuebunny/crossref_metadata_2025_split huggingface dataset:
CISBAT 2021 International Hybrid Conference Carbon Neutral Cities – Energy Efficiency & Renewables in the Digital Era
Authors: Scartezzini Prof. Dr Jean-Louis , Smith Barbara 
Published: November 2021

Preface to the CISBAT 2021 Journal of Physics: Conference Series special issue

CISBAT 2021 took place from 8 to 10 September 2021 online and at the Swiss Tech Convention Center on the campus of the Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland under the heading "Carbon Neutral Buildings - Energy Efficiency & Renewables in the Digital Era".
Focused on energy efficiency and the use of renewables in buildings and cities, CISBAT bi-annually offers a dynamic platform for scientific exchange in fields ranging from nanostructured materials for renewable energy applications to urban energy systems. While recent editions have seen machine learning applications for the built environment receive ever greater attention, CISBAT 2021 has further extended its reach to include research promoting circular economy, thus offering insights into a broad range of fields that ultimately have the same target: carbon-free, sustainable buildings and cities.
List of Editorial Committee, Organising Committee, Programming Committee, Scientific Committee, Academic Partners, Session chairs, Invited speakers, Sponsors are available in this pdf.
Targeting building energy efficiency using thermal infrared earth observation telescopes
Authors: Ben Hui , Mackie Erik , Parry Ian , Shuckburgh Emily , Hawker George , Jenkins Marco Gomez 
Published: November 2021

Abstract
Upgrading the energy performance of the UK’s entire building stock is the central pillar of any credible and cost-effective strategy to meeting net zero. This research aims to open up the revenue of using thermal infrared data from satellites to assist in processes on building energy performance improvement. High-resolution thermal infrared data output from space offers the potential for fast and effective monitoring provision that can cover large areas and targeted buildings or sites. We have interviewed a set of stakeholders from government, industry and community groups to build the specific use cases and find out detailed user requirements.
Using Machine Learning to estimate the technical potential of shallow ground-source heat pumps with thermal interference
Authors: Walch Alina , Castello Roberto , Mohajeri Nahid , Gudmundsson Agust , Scartezzini Jean-Louis 
Published: November 2021

Abstract
The increasing use of ground-source heat pumps (GSHPs) for heating and cooling of buildings raises questions regarding the technical potential of GSHPs and their impact on the temperature in the shallow subsurface. In this paper, we develop a method using Machine Learning to estimate the technical potential of shallow GSHPs, which enables such an estimation for Switzerland with limited data and computational resources. A training dataset is constructed based on meteorological and geological data across Switzerland. We analyse correlations and the importance of each of the input data for estimating the GSHP potential and compare different input feature sets and Machine Learning models. The Random Forest algorithm, trained on the full dataset, provides the best performance to estimate the GSHP potential. The resulting model yields an R2 score of 0.95 for the annual energy potential, 0.86 for the heat extraction rate, and 0.82 for the potential number of boreholes per GSHP system.
Classification of the Energy Production Potential of Water Lens Solar Concentrators Using Machine Learning
Authors: Zarrinkafsh Hamidreza , Eslamirad Nasim , Luca Francesco De 
Published: November 2021

Abstract
Assessing the potential of renewable energy sources for buildings in neighborhoods becomes a crucial task in the early planning stage. Integrating solar energy equipment into urban buildings poses many challenges, such as uncertainties and the complexity of urban built agglomeration. Due to the time-consuming solar energy potential assessment process and lack of knowledge of urban actors, a reliable framework is required to predict buildings’ solar energy potential. This research presents a comprehensive machine learning data processing framework to predict output energy of Water Lenses (WL) based on buildings specifications and relationship to the neighbourhood. The research used a raw dataset consisting of 7000 sample buildings in different situations by applying 12 years of climatic conditions in Tallinn, Estonia. The results were entered into a Supervised Machine Learning process and the Gaussian Naive Bayes technique was used for classification of building features to be implemented with solar systems. Finally, the process was measured by a confusion matrix that showed 80% accuracy of ML output predictions in the urban context.
Characteristics and Challenges in Prosumer-Dominated Thermal Networks
Authors: Licklederer Thomas , Zinsmeister Daniel , Elizarov Ilya , Perić Vedran , Tzscheutschler Peter 
Published: November 2021

Abstract
Prosumer-dominated thermal networks interconnect distributed prosumers. These networks form the infrastructure that allows to execute the trading of thermal energy as desired in the context of local energy markets. However, the significantly different behavior of such networks compared to conventional district heating and cooling networks has not yet been comprehensively investigated. This paper provides a compilation of instrinsic characteristics of prosumer-dominated thermal networks and discusses challenges that arise from these characteristics. As a basis for the investigations an underlying reference concept for the considered type of networks is described. Simulative case studies are combined with scientific deduction and literature references to gain new insights on the design and operation of this type of networks. It is found that due to the variability in these networks, the definition of a design case is a challenge for the dimensioning of concrete network implementations. To anticipate the strong coupling between prosumers and the nonlinear network behavior, it is concluded that centralized control combined with a model of the physical network behavior is necessary. The discussion of characteristics and challenges in prosumer-dominated thermal networks indicates open points in this field and thus provides a starting point for consecutive studies.
Key features of climate-neutral energy systems for municipalities in different climate zones
Authors: Stryi-Hipp Gerhard , Steingrube Annette , Triebel Marc-André , Albert-Seifried Vicky 
Published: November 2021

Abstract
The conditions for cities to supply themselves with climate-neutral energy sources vary greatly around the world and depend on many parameters such as the climate, settlement density, intensity of land use, geographical conditions and the economic development stage of the country. Climate-neutral energy system solutions for 7 cities and counties in Europe, Asia and Africa were calculated and compared to identify climate zone-depending patterns for the structures of climate-neutral energy systems. It could be demonstrated that climate zones have a strong influence on the design of climate-neutral energy supply systems, both in terms of renewable energy provision (e.g. solar radiation) and energy consumption (e.g. space heating demand).
Carbon Neutral Urban Block in Athens - 2050
Authors: Maragkaki Eleni-Marina , Rajput Kartikeya 
Published: November 2021

Abstract
Athens’ extensive urbanisation, lack of green areas and the extreme heat caused by increasingly frequent heat waves indicate the need for actions improving indoor and outdoor comfort, which is closely related to the energy consumption of the buildings. This work’s aim is to create a carbon neutral block in Athens on the 2050 horizon. The optimization of the block’s form based on principles of environmental design and climatic analysis was performed to enhance its environmental benefits. Simulations on the energy performance of the block and calculations on the ability to cover the energy loads by renewables were conducted. Finally, to meet the zero-carbon neutrality, a connection with the neighbouring blocks was established. The results demonstrate the benefits of a bioclimatic, carbon neutral building design in Athens and provide a practical prototype, which can be adapted in other projects, thereby enabling the shift to a more efficient and environmentally friendly built environment.
The assessment of outdoor thermal comfort inside oasis settlements in North Africa - Algeria
Authors: Matallah Mohamed Elhadi , Alkama Djamel , Mahar Waqas Ahmed , Attia Shady 
Published: November 2021

Abstract
Oasis settlements are the most common form in the Saharan regions of North Africa, identified by a strong harmony between urban forms and palm groves, which present the economic capital for these regions. On the other hand, these oases are significantly growing and impacting the people’s livelihood and thermal well-being, especially during summer season. This study aims at first to identify the close correlation between cultivated area (palm grove) and the built-up area throughout the Tolga Oasis Complex in Algeria, which is recognised by its palm groves and well-known as one of the largest oasis settlements of the Saharan regions in North Africa. Furthermore, the current work assesses the impact of palm groves by investigating the ‘oasis effect’ on the thermal heat stress levels during July and August daytime hours within 9 conducted stations. Suprisingly, the so-called oasis effect generated by palm groves was insignificant during the extreme hot days. On the other hand, the palm groves were extremly hot affected by a warming effect during daytime hours.
Automated modelling of building energy systems with mode-based control algorithms in Modelica
Authors: Cai Xiaoye , Xue Junyi , Kümpel Alexander , Müller Dirk 
Published: November 2021

Abstract
The increasing use of renewable energy in building energy systems has brought considerable challenges for the traditional planning process to develop appropriate control strategies. In previous work, we have introduced the MODI method to support the structured development of mode-based control algorithms, in which operating modes are core elements. However, modeling of energy systems and control algorithms for control tests is time-consuming and error-prone. Identification of permissible operating modes is also unfeasible. The paper introduces a methodology to identify permissible operating modes and model energy systems with mode-based control algorithms in the modeling language Modelica automatically. In the case study, we apply the methodology for an energy supply network and verify the functionality of the methodology. In future work, automated optimization of control algorithms will be integrated into the methodology.
Time Enhanced Architectural Modelling (T.E.A.M.): Virtual reality project for the planning and visualization of kinetic architecture and dynamic design
Authors: Temporin V. , Volpato J. , Cocco P.L. , D’Angelo A. , Tieghi M. 
Published: November 2021

Abstract
T.E.A.M. is a research project that was created to facilitate the design of kinetic projects and components created through a computational design process. Time is the ingredient that allows dynamism. The following paper examines the core features of Platform One, an experimental digital application born within the project and aimed at supporting designers during the development, in a VE (Virtual Environment) of dynamic architectures and components, as well as the principles that inspired it. The application presents two key features: the first one is that everything modified and developed in the VE retains its geometric characteristics, allowing the user to reach an informed 3D model at the end of the process; the second one is the ease and enjoyment with which the user manipulates complex dynamic geometries in the three-dimensional environment through a natural interface design approach that focuses on direct manipulation of architectural objects and components. The simulator is designed to be used in a 6DOF virtual environment using a commercial VR headset. It has currently been loaded with several archetypal test architectures and soon it will be available to designers who want to test their work with it.
Modelling climate related performances of building wall coatings and understanding the portability of the “Künzel” rule in different climates
Authors: Augello Andrea , Peren Joy Alexis , Fechner Heiko , Angelis Enrico De 
Published: November 2021

Abstract
How may a coating affect the hygrothermal performance of the building envelope in different climates? Years ago, Helmut Künzel, one of the fathers of Building Physics, proposed, a simple, well-known rule, relating two characteristics of a coating: its water absorption coefficient and its vapour diffusion. The “Künzel rule” (and the associated diagram), based on a model confirmed by field tests in the German climate, set an upper limit to both parameters and their product, became a German standard and a practice among experts, practitioners and manufacturers, in many European countries. This paper proposes the results of an analysis aiming to verify its portability in other climates and is based on an extensive simulation of the hygrothermal performances of a reference wall in six different climatic conditions.
Development of a Modelica-based simplified building model for district energy simulations
Authors: Maccarini Alessandro , Prataviera Enrico , Zarrella Angelo , Afshari Alireza 
Published: November 2021

Abstract
Urban Building Energy Simulation (UBES) is an efficient tool to investigate and subsequently reduce energy demand of urban areas. Nevertheless, UBES has always been a challenging task due the trade-off between accuracy, computational speed and parametrization. In order to reduce these computation and parameterization requirements, model reduction and simplification methods aim at representing building behaviour with an acceptable accuracy, but using less equations and input parameters. This paper presents the development and validation results of a simplified urban simulation model based on the ISO 13790 Standard and written in the Modelica language. The model describes the thermo-physical behaviour of buildings by means of an equivalent electric network consisting of five resistances and one capacitance. The validation of the model was carried out using four cases of the ANSI/ASHRAE Standard 140. In general, the model shows good accuracy and the validation provided values within the acceptable ranges.
Sustainable energy supply for self-sufficient buildings with seasonal energy storages – parametric study
Authors: Zakovorotnyi Andrii 
Published: November 2021

Abstract
To reduce greenhouse gas emissions, the efficiency of energy supply systems must be increased, for example, using renewable energy sources. Since the generation of renewable energy can depend on weather conditions and other parameters, the use of short- or long-term energy storage enables an increase in the covered building energy demand. Due to the large number of available technologies for renewable energy generation and storage, it is possible to combine these systems into different energy supply concepts. By optimizing and comparing the designed concepts, the most suitable one can be determined with respect to the current and future investments. A comprehensive comparison of energy supply concepts must include both economic and energy evaluation criteria. This study focuses on parametric numerical simulations to identify economically feasible and sustainable energy supply concepts for a practical case of new residential buildings. The results show that electrical storage and on-site power generation can provide the greatest benefits. In contrast, large thermal storage systems are not economically viable.
SEAMS: an alternative techno-economic system to foster the sustainable development of renewable energy use in urban areas
Authors: Bourguignon D , Crépeaux P , Adam F 
Published: November 2021

Abstract
To foster the sustainable development of renewable energy use in urban areas, we define an alternative, reciprocity-based, techno-economic system named SEAMS (“sharing energy amongst adjacent buildings”). We demonstrate its relevance through a statistical analysis of linear heat density across coastal cities from Northwestern mainland France, and a comparison of four implementations of three techno-economic systems within the perimeter of two adjacent building blocks, located in the city center of Lorient (Brittany). The SEAMS approach promises to address the multidimensional fragility issues currently surfacing with the conventional, market-based or redistribution-based, techno-economic systems, namely electricity and gas networks (EGN) or district heating and cooling networks (DHCN).
An integrated decision-making framework for sustainable data center operation through intelligent load scheduling
Authors: Lei Nuoa , Cheng Zhu , Cao Zhi , Masanet Eric 
Published: November 2021

Abstract
Intelligent load scheduling is an emerging approach that has the potential to facilitate extreme sustainable data center (DC) operation. However, scarcity of straightforward tools in the public domain challenges decision makers performing quantitative analysis of the DC load planning and its potential benefits. In this work, a novel integrated decision-making framework was developed to address this issue, which provides the basis for the multi-objective optimization of carbon-, water-, and economic-intelligent load scheduling. The proposed framework was demonstrated with a case study DC in California, which showed the usefulness of the proposed framework in informing sustainable DC operations.
Impact of demand response on BIPV and district multi-energy systems design in Singapore and Switzerland
Authors: Waibel Christoph , Hsieh Shanshan , Schlüter Arno 
Published: November 2021

Abstract
This paper demonstrates the impact of demand response (DR) on optimal multi-energy systems (MES) design with building integrated photovoltaics (BIPV) on roofs and façades. Building loads and solar potentials are assessed using bottom-up models; the MES design is determined using a Mixed-Integer Linear Programming model (energy hub). A mixed-use district of 170,000 m2 floor area including office, residential, retail, education, etc. is studied under current and future climate conditions in Switzerland and Singapore. Our findings are consistent with previous studies, which indicate that DR generally leads to smaller system capacities due to peak shaving. We further show that in both the Swiss and Singapore context, cost and emissions of the MES can be reduced significantly with DR. Applying DR, the optimal area for BIPV placement increases only marginally for Singapore (~1%), whereas for Switzerland, the area is even reduced by 2-8%, depending on the carbon target. In conclusion, depending on the context, DR can have a noticeable impact on optimal MES and BIPV capacities and should thus be considered in the design of future, energy efficient districts.
Application of indirect evaporative cooling strategies for a warm-humid climate
Authors: Chávez José Roberto García , Salas Anaís Carrillo , García Pardo Karina A 
Published: November 2021

Abstract
Energy consumption in buildings for air conditioning has augmented worldwide by the escalation in global warming. The application of passive cooling is a promising approach to mitigate this situation. The aim of this research was to assess and characterize the performance of indirect evaporative cooling strategies combined with other passive cooling techniques, applied in experimental modules, aimed at providing hygrothermal comfort. Results showed that the investigated strategies presented lower temperatures than the external conditions and the control module. The alternative that combined indirect evaporative cooling with thermal mass, solar protection, and night radiative cooling was the most promising, with a temperature reduction of 4.2 K, relative to the mean exterior temperature, and a decrease of 8.3 K of its maximum temperature relative to the maximum exterior temperature. An additional strategy was implemented in this alternative using a phase change material, that further reduced its temperature by 6.3 K, relative to the mean exterior temperature and a reduction of 11.5 K of its maximum temperature compared to the maximum exterior temperature. It is expected that these findings are applicable in actual buildings in warm-humid regions to reduce energy consumption for air conditioning, whilst improving hygrothermal comfort and health of occupants.
Sustainable long-term energy planning for a district in Suzhou City, China
Authors: Yazdanie Mashael , Zhou Chenyu 
Published: November 2021

Abstract
A city district in Suzhou aims to develop a progressive, long-term sustainable energy strategy. This study examines possible energy planning pathways for the district through the development of a long-term optimization model and a range of energy scenarios until 2050. The scenarios explore different CO2 emission reduction strategies and technology mixes/parameters. Results suggest which low-carbon energy conversion technologies and efficiency measures should be adopted by the district alongside supportive local policies and targets. Photovoltaic (PV) and waste energy converters are two renewable energy technologies which are taken up at maximum possible rates in the evaluated scenarios to reduce long-term CO2 emissions. Once local renewable resources are exhausted, natural gas-based combined-cycle plants (CCP) and combined heat and power plants (CHP) are required to further reduce emissions, alongside efficiency measures in the built environment. Carbon capture and storage (CCS) technologies also demonstrate the potential to drastically reduce emissions; however, local feasibility studies are needed to support their implementation. Study results prescribe renewable energy share and CO2 emission reduction targets until 2050 for the district. Appropriate local policy and planning targets should also be accompanied by supplementary support studies, including local feasibility, renewable energy resource, and demand-side management studies.
Utilization of programmable cameras for web-based sensing and control of daylight in buildings
Authors: Mah Dongjun , Kim Michael , Tzempelikos Athanasios 
Published: November 2021

Abstract
The concept of integrating programmable low-cost cameras into the office infrastructure and BMS for real-time, web-based sensing and control of the luminous environment in buildings is presented in this study. Experiments were conducted to evaluate the potential of predicting the luminance field perceived by an office occupant using a programmable calibrated HDR camera installed at the rear side of a computer monitor or on the wall behind the occupant, for a variety of sky conditions and shading options. The generated luminance maps using Python scripts with OpenCV packages were further processed to extract daylighting and glare metrics using Evalgare. The results showed that: (i) among the different camera resolutions that were compared, the 330x330 resolution was selected as the best option to balance between accurate capturing of visual environment and comfort and computational efficiency; (ii) a camera sensor embedded on the rear side of a computer screen could capture interior visual conditions consistently similarly to those viewed by the occupant, except for sunny conditions without proper shading protection. This prototype study paves the way for luminance monitoring and daylight control using programmable low-cost camera sensors embedded into the office infrastructure.