bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of evapotranspiration on the local microclimate
Authors: Mauree Dasaraden , Coccolo Silvia , Scartezzini Jean-Louis 
Published: November 2019

Abstract
Climate change is having and will have drastic consequences for high density populated areas such as cities. There is thus a need to develop more tools to evaluate new strategies for adaptation to and mitigation of changing temperatures. Additional functionalities were integrated in the urban energy modelling tool CitySim to include an evapotranspiration process and to integrate low rise vegetation as well as trees. In the process, the Canopy Interface Model (CIM) – previously coupled with CitySim – was further developed to integrate the evapotranspiration process and to analyse its impact on the local microclimate. Tvapotranspiration as well as the surface temperature are computed in CitySim and the values are then used as boundary conditions in CIM to calculate the vertical profiles of wind speed, temperature and humidity. Using the campus of the EPFL in Lausanne, Switzerland as a case study, it was demonstrated that the ground evaporative cooling can be an effective mitigation measure for decreasing locally the urban heat island intensity. In future studies, other strategies such as reflective asphalt, will be combined with the evaporative cooling strategies, to determine the most effective action measures that could be easily implemented.
Cost-optimal retrofit analysis for residential buildings
Authors: Sigrist Diego , Deb Chirag , Frei Mario , Schlüter Arno 
Published: November 2019

Abstract
The current retrofit rate in Switzerland is very low. Among other reasons this is attributed to a lack of knowledge about cost-optimal retrofit strategies. In this work we carry out a holistic cost-optimal retrofit analysis for a Swiss single-family house. First, currently popular retrofit measures including all incurring lifecycle costs are identified and collected. Thereby, building systems as well as building envelope retrofit measures are considered. The retrofit measures are then combined to form a wide range of applicable retrofit strategies which are assessed in terms of cost-effectiveness and environmental impact. The calculation methodology considers the impact of building envelope retrofit measures on the design and efficiency of the heating system. For the case study building, the most cost-optimal retrofit strategy is to combine a geothermal heat pump with inter-rafter roof insulation and cellar ceiling insulation. The results indicate that the choice of heating system is much more crucial in terms of cost-effectiveness than building envelope measures. With respect to reducing primary energy consumption, building envelope measures are indispensable, however, when aiming for reducing greenhouse gas emissions, the choice of heating system becomes dominant.
Using deep neural networks for predictive modelling of informal settlements in the context of flood risk
Authors: Zhu Yue , Geiß Christian , So Emily 
Published: November 2019

Abstract
Global climate change has substantially increased the risks of cities being adversely affected by natural hazards such as floods. Among the inhabitants of cities at risk, residents dwelling in informal settlements are the most vulnerable group. To identify the future exposure of informal settlements, we adopt a data-driven model from the machine learning domain to anticipate the growth patterns of formal and informal settlements in flood-prone areas. The potential emergence of informal settlements in Shenzhen, China, is predicted by the proposed method. Then, through an analysis of the flood susceptibility of the predicted informal settlement areas, the emerging vulnerability of Shenzhen towards flooding is revealed.
Deep learning in the built environment: automatic detection of rooftop solar panels using Convolutional Neural Networks
Authors: Castello Roberto , Roquette Simon , Esguerra Martin , Guerra Adrian , Scartezzini Jean-Louis 
Published: November 2019

Abstract
Mapping the location and size of solar installations in urban areas can be a valuable input for policymakers and for investing in distributed energy infrastructures. Machine Learning techniques, combined with satellite and aerial imagery, allow to overcome the limitations of surveys and sparse databases in providing this mapping at large scale. In this paper we apply a supervised method based on convolutional neural networks to delineate rooftop solar panels and to detect their sizes by means of pixel-wise image segmentation. As input to the algorithm, we rely on high resolution aerial photos provided by the Swiss Federal Office of Topography. We explore different data augmentation and we vary network parameters in order to maximize model performance. Preliminary results show that we are able to automatically detect in test images the area of a set of solar panels at pixel level with an accuracy of about 0.94 and an Intersection over Union index of up to 0.64. The scalability of the trained model allows to predict the existing solar panels deployment at the Swiss national scale. The correlation with local environmental and socio-economic variables would allow to extract predictive models to foster future adoption of solar technology in urban areas.
Machine learning and geographic information systems for large-scale wind energy potential estimation in rural areas
Authors: Assouline Dan , Mohajeri Nahid , Mauree Dasaraden , Scartezzini Jean-Louis 
Published: November 2019

Abstract
Clean, safe, affordable and available in the long-term, wind is one of the most promising sources of renewable energy. Its optimized and profitable use, however, requires an estimation of the potential in locations of interest, given its very volatile behavior in various settings. In the present study, we propose a methodology using a combination of Machine Learning (Random Forests), Geographic Information Systems and wind parametric models to estimate the large-scale theoretical wind speed potential in rural areas over the entire Switzerland. The monthly wind speed over rural areas is estimated based on wind speed measurements and several meteorological, topographic, and wind-specific features available accross the country. Wind speed values and their associated uncertainty are computed at the scale of 200 x 200 [m2] pixels covering the territory, at a typical height for rural commercial wind turbine installation, that is, z=100m. The developed methodology, is, however, applicable to any large region, given the availability of data of interest. The results show that in the case of Switzerland, wind turbines could approximately represent an non-negligible installed power capacity of, for each pixel and for each turbine installation, on average 80 kW in Swiss rural areas, and up to 1600 kW in most suitable pixels.
Can a building read your mind? Results from a small trial in facial action unit detection
Authors: Allen Mark , Overend Mauro 
Published: November 2019

Abstract
In the last few decades, the energy consumption of individual buildings has been steadily improving. As a result, research efforts are shifting towards acquiring a deeper understanding of occupant comfort, health, and well-being in the built environment. However, existing techniques used to measure and predict the comfort of occupants have seen little change since Fanger. New research attempts are hence focusing on methods to gather more data, more frequently, and less intrusively. A little explored source of data is the one gathered from real-time videos of occupants, the so-called facial action units (FAU), which is the focus of this paper. These are the facial movements and positions that constitute the basic elements of emotions. Using software developed in the realm of affective computing, seven building occupants were monitored for a period of 2 weeks, whilst also completing surveys that gathered information about the office environment, and their work and personal life. Results found that participants that were happy with their office space showed significantly higher average values of the Cheek Raiser (AU06) and Lid Tightener (AU07) facial action units. These findings show the potential of using FAUs to assist in the control and design of buildings in a human-centric manner.
CO2 experimental measurements towards the development of a predictive framework using user actions in smart buildings
Authors: Oliveira Rui , Kämpf Jérôme , Vicente Romeu , Almeida Ricardo , Figueiredo António 
Published: November 2019

Abstract
A transition towards smart buildings is one of the challenges of the 21st century. To achieve this goal, the use of smart sensors and smart appliances can be crucial. Although research about linking real-time monitoring and the operation mode of building appliances have been carried out by other researchers, the focus was on the energy performance relegating indoor air quality and thermal comfort to the background. This paper focuses on the analysis of the preliminary results on experiments performed in a real test room to evaluate the CO2 distribution within a single zone. The strategy is to include the concerns regarding indoor air quality in a global framework where weather forecast, users’ actions and building simulation will be combined in a real-time predictive methodology. The experiments included the evaluation of the air change rate using metabolic-related CO2 as tracer gas into the test room. The attained results show an average air change rate value of 0.55h−1. Moreover, the variability of the CO2 concentration throughout the space was also analysed for different positions, using CO2 data loggers calibrated as the reference and real-time sensors. It was concluded that no optimal position of sensors was observed for a single zone, due to the small swing attained for different sensors positions.
Machine learning-based modeling and controller tuning of a heat pump
Authors: Khosravi Mohammad , Schmid Nicolas , Eichler Annika , Heer Philipp , Smith Roy S. 
Published: November 2019

Abstract
In this paper, we consider the problem of controller tuning for an operating unit in a building energy system. The illustrative example used here is a real heat pump located in the NEST building at Empa, Dubendorf, Zurich, with its outflow temperature controlled by a PI-controller. The plant is in use and accordingly, intervening in its normal operation is not allowed. Moreover, the model of plant is not available or it can be changed due to aging or possible modification. Accordingly, it is desired to utilize a tuning method which is model-free, operates online, does not intervene with the normal operation of the plant and use only the available historical measurement data. Additionally, it is required to guarantee the safety of the plant during the tuning procedure. In this regard, we formulate the controller tuning problem as a black-box optimization and adopt a safe Bayesian optimization approach for controller parameters tuning. In order to assess numerically the performances of the scheme, first we model the plant as a nonlinear ARX model in form of a feedforward neural network. Subsequently, we train the neural network using the available historical measurement data. Finally, the obtained model is used as an oracle in the controller tuning procedure in order to numerically verify the effectivity of the proposed approach.
Heat storage in building mass and shifting potential of electricity demand in buildings with heat pumps
Authors: Dott Ralf , Afjei Thomas 
Published: November 2019

Abstract
This study evaluates the potential of typical building structures to store heat and supply flexibility for electricity consumption by heat pumps. The theoretical potential of a hydronic underfloor heating to store heat and supply flexibility for electricity consumption by heat pumps is 0.16 kWh/m2 at 4 K temperature swing. In real operation with a realistic controller, about 50% of this potential can be activated even during daytime with solar gains. For all cases the overall heat demand and the thermal comfort stay equal. A simple but universal rule could be: Independent from the insulation quality of the building, an intermittent increased heating control could merge two heating cycles of the demand-controlled mode to one, where the following waiting time increases by factor 1.5 to 2.
Investigating the performance of a hybrid PV integrated shading device using multi-objective optimization
Authors: Taveres-Cachat Ellika , Goia Francesco 
Published: November 2019

Abstract
PV integrated shading devices (PVSDs) are an interesting case study for an optimisation problem as their design is non-trivial and they must balance competing parameters and uses of solar energy. In this study, the case of a south-facing, exterior louvre blade PVSD was used to investigate how multi-objective optimisation (MOO) coupled to a parametric design approach can be used as a support tool to improve the performance of the system in four different cases. The parameters optimized were the individual tilt angle of each louvre-blade (0, 15, 30 or 45 ° from the horizontal), the vertical distribution of the blades, and the type of material on the upper surface of each louvre (reflective coating or PV cells). The objectives of the optimisation were to minimise the total annual net energy electricity use and to maximise the daylighting level in the zone. The results of the investigation showed that PVSD configurations with higher louvre counts performed better as hybrid systems as they allowed to increase daylighting compared to classic, fully PV coated systems and did not increase energy use in the zone significantly. However, for systems with lower counts of louvres, the results of the optimisation showed that the surface of the louvres was more useful as a PV element, as reflective materials had little effect on the daylighting in the zone and the reduction in energy converted noticeably affected the energy performance of the building.
Implementing an open-source tool for modelling solar PV potential in dense urban areas
Authors: Erell Evyatar , Dorman Michael , Alexandroff Vladimir , Kloog Itai 
Published: November 2019

Abstract
Distributed PV has the potential for generating a significant proportion of many cities’ electricity needs. However, the number of installations in dense urban locations is still negligible. Unlike detached single-family homes in low-density neighbourhoods, where installation is relatively straight-forward and solar access is generally unobstructed, dense urban areas pose special challenges. The paper demonstrates application of a free, open-source tool to assess how building configurations affect insolation and hence PV installation potential on building envelopes (roofs and facades) in complex, irregular urban environments. A sensitivity analysis using generic building types in regular plans highlights differences in the PV potential of contrasting building typologies providing a similar number of dwellings for a prototypical 300x300m urban block with a population density equivalent to 25,000 persons/km2.
Performance assessment of solar thermally activated steel sandwich panels with mineral wool core for industrial and commercial buildings
Authors: Weiland Finn , Kirchner Maik , Rensinghoff Vincent , Giovannetti Federico , Kastner Oliver , Ridder Daniela , Tekinbas Yesim , Hachul Helmut 
Published: November 2019

Abstract
Steel sandwich panels are well established, cost effective components for the construction of structural and functional envelopes in buildings. They offer not only design flexibility but also great potential for active solar energy use. This contribution investigates the performance of solar thermal active panels with mineral wool core featuring heat exchangers comprising different designs and materials by means of FEM simulations. The simulation model is validated against measurements of fabricated test specimen. Specific results are reported for a large-sized test specimen with a grey finishing (RAL 7043) where the conversion factor η0 ranges between 0.46 and 0.56. The results imply that higher figures of 0.73 and higher are theoretically achievable with a more efficient use of the panel area and improved manufacturing.
CoolShift – Cooling of buildings by chiller-assisted nocturnal radiation and convection
Authors: Koch Manuel , Dott Ralf , Eismann Ralph 
Published: November 2019

Abstract
A novel approach for cooling an office building is numerically evaluated. PVT collectors are used for nocturnal radiative and convective cooling. A TABS ceiling serves as thermal storage. If the free cooling power of the PVT collectors is too low, it is boosted by a chiller raising the collector temperature. While the energy efficiency improves compared to a conventional daytime chiller cooling system, the room temperature cannot always be kept in the desired band. Furthermore, the PVT collectors stay cooler than comparable PV modules during the day, increasing the electricity generation.
Modelling and developing a renewable energy system for the cold stores of a food park in the UK
Authors: Li Xiaojun , Jones Phillip , Patterson Joanne 
Published: November 2019

Abstract
An on-site renewable energy system is developed and presented in this paper to supply electricity usage of potato cold stores in a UK food park. The system is designed to use the mass of the potatoes to store surplus power from PV when there are days of high solar radiation. It can also be charged from the grid during off-peak time when there are longer periods of overcast conditions. The paper presents results to show energy generated by the PV that can be used in the cooling system, and the storage potential of the potatoes in offsetting grid supply. The dynamic thermal model HTB2 with an energy system extension is employed to design the energy system. The base case representing the existing scenario is validated with previous weekly metering data. The system performance is examined in terms of annual energy performance and long-term cost-effectiveness. The simulation results indicate, 1) the cold store with potato storage is able to maintain the required temperature ranges for most periods when cooling is only powered by electricity from PV during peak-time, and it contributes to energy cost savings and electricity import reduction, but almost no cooling reduction; 2) the system combination of solar PV and off-peak cooling can be paid back within its lifespan, with the most optimal case taking only 11 years. The outcome of the research demonstrates the benefits of the optimized renewable energy system, which provides free or cheap energy supply, reduces industry-related CO2 emission, and contributes to overall energy cost savings. This technique might be applied to other type of food storage, where the thermal mass can contribute to thermal storage.
Geospatial analysis and optimization of the incoming and stored CO2 emissions within the EPFL campus
Authors: Mori Giovanni , Coccolo Silvia , Castello Roberto , Scartezzini Jean-Louis 
Published: November 2019

AbstractAll the projected scenarios agree on the immediate necessity of reducing greenhouse gas emissions, especially carbon dioxide (CO2). This research proposes an analysis on the EPFL campus of all the potential reductions of CO2emissions: energy refurbishment, the request of heat and cooling of the buildings, emissions deriving from commuting and business travel as well as the embedded emissions of the buildings through their Life-Cycle Assessment. Subsequently, compensation strategies have been evaluated: Vertical Greenery Systems, CO2uptake from trees of the campus through an automated computing technique and Direct Air Capture technology. Together, all these contributions allow to significantly reduce the annual emissions of the campus, by up to 60 %, getting below the critical threshold of 1 ton of CO2/person/year.
Algorithmic optimisation of a building plant system
Authors: Borer Marco , Frey Manuel 
Published: November 2019

Abstract
Using a practical example, the heat and cold storage volume of a building plant system is analyzed and optimized using tools integrated in the simulation software IDA ICE. In practice, the simulation models must be partially simplified for efficiency reasons. The level of detail of the storage tanks should be chosen in such a way that the temperature behavior of the simplification corresponds as closely as possible to the behavior of a non-simplified model. Hence, the required findings can be obtained from the simulation and optimizations can be carried out efficiently. The investigation showed that certain model simplifications are legitimate and that the optimization tools in IDA-ICE can be used reasonably for different tasks of an overall optimization.
An energy balance model for passive solar systems operation
Authors: Baxevanou Catherine , Fidaros Dimitris , Tsangrassoulis Aris 
Published: November 2019

Abstract
Passive solar systems (such as Trombe-Michel walls and their modifications) are a cost effective technology to reduce the energy demand for buildings’ space heating. In the present paper an energy balance model for the description of the performance of a passive solar system composed of an opaque element with transparent insulation is presented. This energy balance model has the form of a closed system of equations that could easily be solved in an open source software by an engineer.
Python-based calculation tool of wind-pressure coefficients on building envelopes
Authors: Chiesa Giacomo , Grosso Mario 
Published: November 2019

Abstract
Wind pressure distribution is an essential factor for calculation of airflow rates in controlled natural ventilation systems for both indoor air quality and cooling purposes. A pressure coefficient calculation model, CpCalc, with a modular parametric approach based on analysis of wind tunnel tests was developed by Mario Grosso within the COMIS workshop, held at Lawrence Berkeley Laboratory, UCB, CA, USA, in 1988-1992, and upgraded for the European Project PASCOOL in 1994-2001. This software allows for calculating Cp at any point of a building façade and roof slope as a function of various climate, environmental, and building geometry parameters. The present paper describes a further upgrading of this software using a Pyton script, which allows for applying CpCalc to hourly-based energy dynamic simulation codes as well as being connectable in future with parametric design software.
Educated commissioning and operation of a complex nearly zero energy office building with the help of dynamic thermal HVAC-simulations - a best practice report from the Austrian postal service headquarter Post am Rochus
Authors: Horn P , Hauer S , Bres A , Eder K , Lindmeier I , Frey A 
Published: November 2019

Abstract
This paper presents lessons learned from practice focusing on planning, commissioning and first year of operation of the Austrian Post AGs’ new headquarter “Post am Rochus”, a nearly zero energy building with 49.300 m2 gross floor area. The execution phase was supported by a research project aiming for a significant reduction of the commissioning phase. Based on the positive experience of this Austrian lighthouse project, general conclusions are drawn focusing on which activities and recommendations can be applied to similar projects, and which parts need further improvement or adaption. The question of how and when building energy performance simulations of complex HVAC-systems can be used to increase the energy efficiency, room comfort and operational stability of modern office buildings is investigated from a practical perspective. The challenge, and an outlook of how to reduce the information gap between the various disciplines involved in a complex multi-stakeholder process and the conclusions from the building owner are discussed and summarized in the conclusions.