Building Simulation Applications BSA 2024

x The Sustainable Analytical Model (SAM), developed by Michał Dengusiak and Jakub Ziolkowski, is an innovative open-source software that broadens the selection of building energy modelling tools written in .NET C#. SAM focuses on enhancing the accuracy and efficiency of energy analysis for architects, engineers, and energy consultants, engaged in the development of energy-efficient buildings. Its open-source nature ensures a wide accessibility, making it an effective tool for bridging the gap between theoretical modelling and practical application. Furthermore, as building design continues to evolve towards more sustainable practices, SAM stands ready to meet these new requirements, providing a customisable, dependable and futuristic platform for energy modelling.

x This article presents a novel methodology that combines energy simulation and the use of advanced comfort indices for assessing thermal comfort in buildings, with a specific focus on a historical office building in Catania (Italy). The research methodology includes detailed modelling in TRNSYS, supported by surveys and on-site measurements of temperature and relative humidity. Then, suitable synthetic indices are introduced that are adaptable to different thermal comfort theories, in line with major standards (ASHRAE 55 and EN 16798-1, namely). This provides a versatile tool for assessing thermal discomfort in historical buildings while easily identifying the rooms where applying possible mitigation strategies is most urgent. This approach also allows us to evaluate the effect of suitable retrofitting options that could achieve good thermal comfort,thus reducing energy consumption and contributing to their adaptation to the evolving climate.

x This study introduces the creation and application of a data-driven digital twin for building ventilation systems,focusing on a university building as a case study. It employs a grey-box energy modelling framework to accurately forecast, simulate, and monitor the ventilation system's efficiency under diverse conditions. The study collects a substantial dataset to reflect various usage patterns and environmental influences, which serves to test and validate the component models of the ventilation system. These models are integrated into a digital twin platform, providing a comprehensive overview of the system's performance and critical indicators in real time. The digital twin facilitates informed decision-making for facility managers regarding energy consumption, inefficiency identification, and the recommendation of custom retrofitting actions specific to the building's characteristics and use. The findings confirm that digital twins are effective as a tool to continuously commission and detect anomalies in buildings. The study offers a ventilation modelling and monitoring method capable of recognizing rule-based control behaviours and changes in systems that occur in cycles,like system shifts from winter to summer, and can estimate total air mass flow rate with a correlation exceeding 80%.

x Simulation-based optimization (SBO) processes are computationally expensive and the combination with machine learning (ML) methods appears as an alternative capable of reducing computational time consumption without losing the robustness of the solutions. This study compares neural network and random forest algorithms as approaches to replace simulations during the SBO processes. The main objective is to define the best machine learning algorithm and the most reliable ratio between simulations and predictions. The problem was implemented in the Grasshopper + Rhino platform and aimed to minimize the annual energy consumption with artificial conditioning in an office building. Comparing the convergence and reliability of the hybrid processes, the results show that the neural network achieved the best results. The results also show that for this particular/specific problem, the ideal budget comprises 80% of simulations and 20% of predictions, maintaining the results' reliability and reducing the computational cost.

x Energy use intensity (EUI, kWh/m2·yr) has been widely used in the building industry for building energy bench-marking. However, this EUI-based building energy benchmarking could lead to a biased assessment because it overlooks other influential factors such as operational schedule, occupancy, plug-load, setpoint temperature, and weather (hereafter referred to as operational factors). To overcome the issue, the authors propose a normalization process for the building’s actual energy consumption considering the aforementioned factors. In this study, a concept of normalization coefficients was introduced based on the relationship between the operational factors and the change in energy consumption. The eXtreme Gradient Boost regression (XGBoost) models were used for deriving normalization coefficients that can convert the actual heating and cooling EUIs into the normalized EUIs per building under the operational factors. Validation studies demonstrated that the conversion of actual EUIs into normalized EUIs using these coefficients can contribute to fair building energy benchmarking. In other words, the proposed normalization approach holds promise for achieving more objective building energy performance benchmarking.

x Many studies have shown that by installing external Venetian blinds on the transparent envelope and utilizing daylight efficiently, we can reduce cooling and heating load and lighting energy and improve thermal and visual comfort. Among many studies, most of them use light sensors or whole-building simulation tools to derive and control illuminance that affects the indoor luminous environment. However, this requires the cost of sensor installation and a large amount of information and modeling effort for simulation. In addition, it is difficult to understand the relationship between the inflow of visible light, the slat angle of blind, and illuminance. Therefore, this study proposes a stand-alone daylighting simulator based on artificial neural network using the visible transmittance of the window with external Venetian blind. Using the developed simulator, it is possible to easily predict indoor vertical illuminance under changing external environment by reflecting natural light inflows with only some information of the system and major environmental factors without sensor installation or simulation modeling effort. In addition, due to the advantages of this simplicity, it can be easily used for model predictive control (MPC).

x Buildings can be examined during concept design to identify potential for sunlight to reflect off exterior cladding surfaces and create traffic disability glare onto surrounding roadways. Historically most assessment methodologies calculate veiling luminance hazard at roadway receiver locations assuming specular type reflections off glazing. A population dosage of veiling luminance is pro-posed in this study as a limiting measure of solar disability glare exposure to passing traffic. Modern facades are increasingly adopting metal sheet cladding products displaying both specular and highly diffuse reflective properties. In-house software has been developed to perform solar reflection calculations off a range of specular and diffuse reflective surface finishes. The program generates view-based luminance renderings at traffic receiver locations. Subsequently, a custom script evaluates the renderings and determines annual disability glare metrics including retinal irradiance, glare source angle and background luminance for comparison with existing disability glare criteria. Threshold increment is calculated from modelled veiling and background luminance as a measure of reduction in contrast due to disability glare. Case studies are reviewed where façade solar reflections flagged during early design as a traffic disability glare population dosage risk were successfully mitigated with façade treatments. Implications of façade solar reflectivity mitigation for building energy consumption are discussed.

x This paper presents the energy modelling and calibration of a small-scale experimental greenhouse using building performance simulation tools in a cold climate. The green-house is modelled in EnergyPlus using the OpenStudio interface. Evidence-based calibration is then performed using the available construction information. Subsequently, an automated off-line calibration of influent energy model parameters yielded a NMBE of 1.90 % and a CV-RMSE of 5.75 % over monthly energy data. The modelling and cali-bration conducted in this paper also helped identify knowledge gaps in controlled environment agriculture (CEA) energy modelling using building performance simulation (BPS) tools.

x This paper analyses the microclimate conditions in the Church of Santissimo Salvatore in Bologna and their influence on the acoustics of the Church and the sound of the pipe organ. It is commonly acknowledged that the variation of air temperature, median radiant temperature, relative and absolute humidity could provoke thermal expansions of metals which are used for the organ pipes. This paper analyses a monitoring campaign which lasted one year in which temperature and relative humidity were stored with a data logger. Moreover, the paper shows the effect in the variation of the microclimate conditions in the church by simulating different numbers of people in the church and different thermal conditions outdoor. Finally,the paper reports the variations of the acoustic parameters simulating the new values of temperature, relative humidity and air velocity.

x Strategic reduction of thermal zoning granularity in energy performance simulation may be advantageous in high-resolution queries involving large and complex-built objects in view of time and effort reduction potential. However, the proper choice of thermal zones' granularity is also dependent on the nature and purpose of performance queries. In this context, this paper explores the influence of the thermal zones' resolution on buildings' estimated heating and cooling loads. To this end, the illustrative instance of a multi-zone building is selected and made subject to varying levels of thermal zoning resolution.

x Research about Urban Building Energy Models (UBEMs) has undergone a significant increase in recent years. In most of the papers in the scientific literature, researchers claim that UBEMs can be used by policy makers and other stakeholders to evaluate and plan energy efficiency measures at urban scale. Despite their good purpose, researchers are still the main users of these tools. This work tries to make a step forward by calibrating an UBEM on real energy consumption data from 489 residential buildings of Padua (Italy), and to use the calibrated model to assess two energy efficiency measures on the considered sample of buildings. Results show that calibrating only two coefficients is sufficient to obtain an accurate model with a limited computation effort. The analysis of two renovation scenarios suggests that deep retrofits on the biggest consumers is an effective strategy to abate CO2 emissions at urban level.

x Over the past 25 years there has been a significant growth in final electricity consumption, and this is expected to in-crease due to greater electrification and continued integration of Renewable Energy Sources (RESs). This trend can lead to imbalances and sustained strains on power grids during surpluses and peak demand. To address these challenges, through flexible strategies, building thermal demand can be managed in response to the grid requirements. In this field, moving from the individual building level to the cluster level allows for a greater reserve of displaced energy for grid balancing. However, planning the flexible resources needed for energy management of clusters of buildings can still be difficult. Therefore, a tool to evaluate flexibility scenarios can be useful. Thus, the aim of this paper is to introduce ClustEnergy OpTool, an open tool for estimating the energy demand of a user-defined cluster of buildings under different demand management strategies. The user can compose the cluster by choosing from different building archetypes served by Heat Pumps (HPs) to meet the thermal demand for space heating, cooling and DHW. Buildings can be equipped with PV and subject to a given price signal. Then, by selecting different ways to flexible manage the cluster energy demand (e.g.,peak-shaving or demand-shifting, price signal-based management), the tool can estimate the energy shifted, peak displacement, PV self-consumption and electricity bill reductions, both at cluster and individual building level.

x The adoption of primary energy factors (PEFs) is very common in the building sector since primary energy is one of the main metrics for evaluating the energy performance of a building. The use of such factors is extensive in European and international legislative contexts to establish a regulatory framework for enhancing building energy efficiency policies. This study analyses how the use of dynamic PEFs, variable on an hourly basis, affects the assessment of building performance. The dynamic primary energy factor for electricity has been evaluated for the Italian scenario during the year 2022, applying the methodology outlined in the EN 17423:2020 standard with an hourly detail. The conversion factor was subsequently applied to the electricity demand of a reference building for residential use. The result obtained has been compared with the same evaluations carried out using the static conversion factors currently adopted by the legislation in force, showing that there is an urgent need for adjustment. The dynamically assessed total PEF stopped at an average value of 1.84, in contrast to the 2.42 used in current legislation. As a result, the total primary energy demand of a reference building decreases by 23.07%, also involving an alteration of the ratio of renewable to non-renewable share. The study concludes that the use of dynamic PEFs is essential for both the design of new buildings and the assessment of existing buildings, especially when time-dependent HVAC, renewable energy and control strategies are considered. It also allows for better energy flow management within buildings. Finally, the study emphasizes that up-to-date PEFs are crucial for improving the energy efficiency of buildings and guiding the future decarbonization of the building stock.

x This paper aims to develop a mathematical model of a dew-point indirect evaporative cooler that can be easily implemented in a TRNSYS building simulation environment. The model is validated against experimental data from a tested mixed flow prototype. The results show that the model is consistent with the experiments with an error in the primary air temperature drop between 12%and 18%. Furthermore, a parametric analysis is performed to evaluate the effect of the size of the device. The temperature drop may double by increasing three times the height or the width of the device. In conclusion, this study reveals the importance of a proper calculation of the Nusselt Number, especially for the wet channel.

x Theatres must have an adequate reverberation time depending on their intended use. In this paper the acoustic characteristics of the regional theatre of Bejaia (Algeria) built in 1936 is discussed. The hall has a regular geometry with the shape of a shoebox, with a capacity of 420 seats. Measurements of the acoustic characteristics were carried out using the bursting of an air-inflated balloon. The room has an excessive reverberation time, which is not suitable for the performance of prose shows, and so it is necessary to carry out an adequate acoustic correction to reduce the reverberation time and increase the STI to improve speech understanding. The aim of this work is to analyze, using architectural acoustics software, the conditions for improving the acoustics of the room in order to reduce the reverberation time. The study uses numerical modeling to evaluate the effects of modifying the material of the stage tower or inserting surfaces with adequate acoustic absorption.

x The Vittorio Emanuele II Theatre of Benevento was designed with a horse-shoe shaped plan, following the architectural trend 1860. The project, originally designed by architect Francesconi, was modified after World War II due to the development of cinema, which replaced traditional theatrical performances. To accommodate this shift, the room volume was reduced, as the screen was installed at the fire curtain level, effectively eliminating the fly tower. Additionally, the wooden balustrade was replaced with glass to provide a clearer view of the screen. Acoustic measurements were carried out inside the theatre according to ISO 3382-1. The main acoustic parameters were evaluated and compared with the theatre’s original function as a performance venue. The measured and simulated results indicate that the acoustic response is well-suited for an amplified audio system, though

x The research evaluated retrofitting options for a three-story church community building in Grevie, Sweden, assessing the impacts on energy efficiency, life cycle cost,and environmental concerns. An energy model was generated in IDA ICE to simulate the building performance. Various improvements were tested in two separate retrofit package scenarios. They had the following measures in common: the addition of insulation to the walls and roof, the addition of sealant and secondary glazing, the installation of a heat pump with a better seasonal coefficient of performance (SCOP) on the ground floor, and the installation of a photovoltaic (PV)system. In the first scenario, modifying the controllers of electric radiators was considered while leaving other pre-existing systems untouched. In the second scenario, all systems were replaced by two heat pumps, one for the ground floor and the second for the first floor, with improved SCOP. In the study, 1,620 different energy improvement cases with simultaneous 3,000 simulation combinations of PV systems were examined, using scripted and parametric optimization. Results suggest that adjusting controllers and adding PVs could yield significant energy savings and cost reductions. Notably, cases with an additional air-to-air heat pump on the first floor showed the best energy consumption reduction,though not the highest profitability. The research highlights the importance of combining passive and active measures and their impact on energy efficiency, life cycle costs, and environmental factors. It also shows that the most energy-efficient options may not always be the most cost-effective or environmentally friendly during a building’s lifetime.

x The lack of performance art spaces in Italy led the local authority to convert some abandoned religious buildings for live musical shows. The church of Aversa has been digitally rebuilt and used for acoustic simulations that focus on two scenarios: the existing conditions and the installation of some acoustic panels that help to direct the sound towards the seating area. The validation of the simulations is based on the acoustic measurements carried out inside the church that have been used to calibrate the 3D model. The results show that the acoustic parameters for music are highly improved, resulting within the optimal range as established by the criteria. To improve the acoustic characteristics of the church, the effects of inserting panels to be placed on the audience area were studied using numerical simulation. The procedure was performed with dedicated software for architectural acoustics.

x The text discusses the potential for energy efficiency improvements in existing buildings, emphasizing the importance of digital modeling and Building Performance Simulation (BPS) methods to achieve Net Zero Energy Building (NZEB) standards. The integration of Building Information Modeling (BIM) and Building Energy Modeling (BEM) approaches is highlighted as crucial for enhancing energy efficiency. The proposed workflow involves four steps: i) collection of building data through documental analysis and on-site surveys; ii) the construction of a BIM model and its production in Industry Foundation Classes (IFC) standards, including thermo-physical parameters; iii) the developing the BEM model; iv) the creation of a Virtual Reality (VR) interactive environment. The methodology is tested on an office building at the University of Rome Tor Vergata, built in the 1980s. Key outcomes include verifying data interoperability, optimizing energy simulation processes, and enabling interactive exploration of energy data through VR techniques. This integrated approach reduces errors, time, and costs, while also serving as a decision-making support tool for building managers and an educational tool for energy design awareness. The study presents a scalable workflow for energy building management and lays the groundwork for innovative digital twin development for buildings and structure.

x Aquifer thermal energy storage (ATES) is a type of underground seasonal thermal energy storage which uses underground water as the storage medium. Different modeling and simulation tools have been used to model ATES coupled with building and district energy systems. However, most of these methods use co-simulation techniques, which are computationally expensive, time consuming and complex to set up and debug. This paper illustrates a simplified cooling-mode operation of an ATES-based system model developed entirely using the Modelica language. Results indicate that Modelica is an appropriate tool for developing energy system models consisting of ATES to assess their performance. For the case study analyzed in this paper, we controlled the aquifer circulation pumps to supply a constant water temperature of 12 °C to the buildings. Furthermore, the model allowed us to predict the aquifer temperatures in the warm well over time at different distances.

x Building stock energy models have been receiving in-creasing attention in the last years as powerful tools to forecast energy policies at national levels. This work contributes to the existing discussion on this topic by presenting a bottom-up physic-based model of the Italian residential stock that can calculate national energy consumption using data collected by ISTAT from a 2013 survey. Such a model exploits electric appliance data and dynamic building energy simulations to analyse the current state of Italian houses’ energy consumption, and by presenting possible scenarios for 2050. The analysis of the current state focuses on the energy vectors employed, primary energy, and validation with respect to external sources. Results show good accuracy with respect to national energy balance and with respect to regional data for heating and domestic hot water. The presented future scenarios are based on expected changes in climatic condition, technology replacement, and retrofits of buildings. Considering current renovation rates, envelope insulation and heat pump installation could produce a reduction of 12% of the final energy.

x The implementation of movable solar shading is strongly encouraged in order to reduce the overheating of residential buildings. However, their efficacy is, amongst other factors, determined by the control system employed. Building occupants are often relatively passive in manually operating their shading, leading to suboptimal use, whereas automated control reacts consistently to changes in outdoor and indoor conditions. This study evaluates the impact of automated shading control on annual heating and artificial lighting energy consumption, and thermal comfort compared to manual operation in residential buildings without cooling installations. Building performance simulations are conducted for three building designs in the temperate climate of Belgium using EnergyPlus. Multiple variations are investigated to analyse the sensitivity of the impact of automated control to boundary conditions such as the orientation, reflectance of the solar shading, household composition and manual operation strategy. The results demonstrate that the implementation of automated shading control has the potential to substantially reduce thermal discomfort while exerting a minimal impact on the energy consumption. However, the relative differences in overheating show considerable variation, primarily influenced by the building design and occupant behaviour. These findings emphasise the necessity of considering co-benefits (e.g. thermal comfort) and boundary conditions when evaluating shading control strategies.

x Agri-Photovoltaics (Agri-PV) integrated in greenhouses optimize land use by combining solar energy production with crop cultivation, promoting sustainable agriculture. The REGACE project, funded by Horizon Europe, aims to develop innovative technology for PV in greenhouses to ensure uninterrupted food production. This paper introduces the initial steps of REGACE's vision by creating a dynamic model using Dynamic Building Simulation (DBS)software to understand the relationship between plant growth, energy use, and microclimate conditions in a pilot greenhouse at the University of Thessaly, Greece. The study uses the Penman-Monteith evapotranspiration model to simulate the greenhouse's thermal dynamics, identifying discrepancies between model predictions and actual temperature and humidity levels. The paper discusses these issues, attributing them to model simplifications and the need for more precise data on shading curtains and cooling systems.

x The national building renovation plan is a key element in the recently approved version of the Energy Performance of Buildings Directive. The plan will provide a comprehensive overview of the energy and environmental performance of both the residential and non-residential building stock. To achieve the objective of mapping the energy status of urban configurations, the exploitation of building typologies, representative of different climatic zones, building use categories, and construction periods,has shown to be a useful approach. The huge data uncertainty related to the building archetype generation necessitates a deeper analysis of the variation of crucial inputs that have repercussions on the energy performance assessment of the building stock. This work begins with the Urban Building Energy Model data classification aimed at identifying the fundamental inputs needed to run an urban large-scale energy analysis. Then, the paper proceeds with the review and categorisation of the existing Italian databases, exploitable to mitigate the high uncertainty related to the input data. Once the requisite information is collected and the data-bases classified, the application part progresses with the probabilistic building archetype schema generation from the energy performance certificates of the Aosta Valley Region, taken as a case study. A local large-scale sensitivity analysis, obtained varying one at a time the thermo-physical parameters of the building fabric and the window-to-wall ratio of a residential stock located in Aosta, was carried out. The study highlights how variations in statistical ranges of inputs, particularly regarding the performance of opaque building envelope components, impact the assessment of building energy needs.

x Daylight illuminance data is required for daylight scheme evaluations, while the adoption of daylight-linked control (DLLC) systems is a useful strategy for attaining energy savings on lighting. For evaluations of these daylighting schemes and DLLC, determining the sky conditions through sky luminance distributions is required. Moreover, through these distributions, the 15 CIE standard skies can be identified and daylight illuminance for any surface of interest can be derived. The crucial issue is that sky luminance data is sparingly measured. Recent studies have shown that the use of accessible climatic data and machine learning (ML) models for determining the standard skies can be viable alternatives. In this study, an ensembled-based Light Gradient Boosting Machine (LGBM) was used to identify the standard sky types in Hong Kong. The predictions of the LGBM model were then integrated with RADIANCE and EnergPlus for daylight and building energy simulations of a generic shopping mall. The simulation was carried out by comparing the Best fit, ASRC 1992 and the All-weather models against the measured data. Findings show that when tested, the LGBM model correctly classified the sky types over 70% of the time. Similarly, when used for daylight and energy simulations acceptable predictions were obtained from all models. Finally, it was found that the impact of the sky luminance distribution model on illuminance prediction is higher than that for energy estimation.

x The construction sector is a major contributor to global resource depletion and environmental impacts. Most buildings still lack energy efficiency, necessitating substantial renovations to reach European climate neutrality by 2050. Energy efficiency measures typically prioritize investment cost and targeted energy performance, often neglecting the environmental impact associated with the production and disposal of the selected materials. This paper presents the development of a design assistant tool that combines sustainability indicators with cost and energy performance, aiming to foster sustainable renovation. Through automated data exchange between Auto-desk Revit, CasaClima software and Microsoft Excel, the tool identifies optimal retrofit solutions. Users can choose materials and systems and visualise different retrofit alternatives through a user-friendly interface. The paper describes how the tool is structured to quickly evaluate a wide range of energy efficiency measures.

x Daylight-linked lighting control (DLLC) system has been recognized as one of the effective measures for improving indoor illuminance distribution and energy performance. However, the system is often considered ineffective due to poor calibration and commissioning of the system and lack of design guidelines (Bellia et al., 2016). Among different causes, the positions of photosensors play a crucial role in DLLC systems. The position affects the DLLC system in two major aspects. First, the location of the sensor needs to reflect the illuminance level on the working plan level where it would not be affected by a strong source of sunlight. Secondly, under normal circumstances, DLLC is controlled by a single photosensor which leads to over-dimming in the rear part of the room or overprovided electrical lighting at the front part of the room. Traditionally, the use of open-loop and closed-loop controls makes it impossible to change the dimming ratio of artificial lighting due to indoor illuminance distributions and climatic conditions. Hence, an artificial neural network (ANN)-based machine learning (ML) is used to identify the correlation between artificial lighting and photosensors under different operating conditions. This paper focuses on identifying the major input parameters for the ANN model. Find-ings show that the input parameters (features) have strong correlations with the dimming output. Also, the ANN model performed very well with very small errors in most of the cases.

x We propose an open-source-based workflow which connects Building Information Modelling (BIM) with thermal Finite Element (FE) – Analysis. We use the open IFC-standard for data interoperability and leverage open-source FE software packages for both 2D and 3D thermal analysis. The Finite Element Method (FEM) represents a highly flexible state-of-the-art approach for thermal analysis in construction engineering. With the recent increase in computing power, even complex 3D FE models can be analysed within a feasible amount of time. However, the integration of FE-Analysis into BIM-workflows remains an active area of research. Especially, a consistent and automated flow of material and boundary condition information is a challenging task to realize. The aim of this work is to contribute to the advancement of automated and open-source-based solutions for thermal analysis of buildings. The proposed workflow has the potential to decrease the time needed for evaluation of energy efficient building designs, especially in early design-phases. Its open-source nature promotes transparency, reproducibility, and collaboration in the building industry. The implementation of the proposed workflow results in a software prototype, which is tested based on a selected use case.

x In Hungary and generally in Central Europe, a significant part of the existing building stock is constructed using traditional technologies that were widespread in the 19th and 20th centuries. Due to a lack of quality building materials, it was common practice to build structures using materials that were not specified and not following the prescribed layering scheme, so even a simple renovation project could typically be problematic. Moisture generated during the use of the building, condensation, and the initial construction moisture also have significant effects on building structures. In many cases, the reconstruction works are carried out due to a change of function, which can cause various external and internal moisture effects to affect the structure. To reduce the energy needs of the existing building stock, an increasing number of experts are starting to work on thermal and hygrothermal simulation of building structures. Numerical simulations of the distribution of humidity and temperature inside buildings can be used to determine the behavior of a building element during its life cycle, which can facilitate, among other things, the maintenance of architectural heritage and the design of renovations for energy efficiency. Within the framework of this research, detailed thermal and coupled heat and moisture transport simulations based on finite element methods were carried out to evaluate the energy performance of the most common traditional slab structures in Hungary. There were significant differences in both heat losses and thermal conductivity depending on whether only thermal or hygrothermal simulation was used and in general, hygrothermal simulations can provide much more accurate and detailed results. The simulations showed that none of the historic slab structures meet today's minimum energy and durability requirements, but with the suitable renovation method, heat losses for example, can be reduced by up to 25–60 %.

x In this work,aTRNSYS model of a five-story hotel located in Northern Italy is used to evaluate simple energy flexibility strategies for the cooling season to be used in a possible smart grid integration. The strategies are demand-side and include energy efficiency and load shifting. Two models are used, one of the building envelopes, to evaluate the instantaneous heating and cooling demands, and the HVAC system model, used to simulate the heating and cooling production by two multifunctional heat pumps and two heat pump boosters for the domestic hot water production. The flexibility strategies are applied in the building model controlling the room thermostats while the heating and cooling demands are calculated using meas-ured occupation profiles. On the other hand, the hot and cold-water tanks set point temperatures are used to implement the energy flexibility of the HVAC system. In both cases, the target is to shift the loads in the PV panels production hours, reducing the electricity demands from the grid during the other hours.

x Concerns about noise conditions in schools have led many countries to introduce standards or guidelines for school acoustics design. The aim of this paper is to investigate the extent to which classroom acoustics affect perceived well-being and noise disturbance at the University of Pescara in Italy. Approxi-mately 100 students aged between 20 and 30 participated in the study, during which room acoustic measurements were taken, and noise levels were monitored in accordance with the national standard UNI 11532. To validate the measurements, a questionnaire was used, following the ISO 12913 standard. In addition to the empirical study, a numerical model was developed using ODEON, a widely recognized room acoustics simulation software. This model was employed to simulate and analyze the acoustic conditions in the classrooms under various scenarios, providing additional insights into the acoustic environment. The results of the correlation between subjective responses and objective measurements will be used to design more positive and inclusive learning environments.

x Energy consumption and its consequences are inevitable in modern-age human activities, particularly in the school environment. School buildings require significant energy inputs for heating and air-conditioning, and the majority of the occupants are adolescent students, whose health and cognitive performance are vulnerable to poor indoor air quality (IAQ), thermal discomfort and acoustic noise sources. The present study employs measurements and numerical methods to improve Indoor Environmental Quality (IEQ)and reduce energy consumption in school buildings. Accurate measurements enable the quantification of various environmental parameters, from indoor air pollutants to temperature and relative humidity levels. These measurements form the basis for informed decision-making and interventions to improve the environment. Numerical methods, on the other hand, offer a means to model and simulate the impact of different factors on environmental quality. Advanced computational tools allow for the assessment of scenarios, enabling stakeholders to identify optimal solutions for achieving and maintaining high standards of environmental quality in schools.

x In the assessment of energy performance of buildings, the efficiency of technical building systems, especially those related to heating and cooling services, has a significant impact on the overall energy consumption. For this reason, accurately determining the performance of these systems is of utmost relevance. Current simplified procedures for evaluating technical building systems lack complete validation, potentially leading to undesired inaccuracies in the results. This paper analyses the existing simplified procedures provided by standards for assessing heat emission and control subsystems. It examines the procedure currently in use in Europe and presents a comparative analysis with more detailed procedures. Through a case study approach, the research explores several configurations of a representative residential space, considering factors such as climatic data, envelope properties, emission terminals, and control strategies. By addressing these aspects, this research contributes to enhancing the understanding of the effectiveness and reliability of simplified procedures for assessing the performance of technical building systems.

x Building energy automation and control strategies have recently been applied to improve the energy performance of the building and to exploit the integration of the building envelope, HVAC and RES. To optimise their application, reliable data on the dynamic energy behaviour of the building should be available possibly from monitoring, but also from simulation at the design stage. This paper compares the results of two building performance simulation tools: TRNSYS, which implements a fully detailed model and software implementing a simplified model according to the EN ISO 52016-1 standard. We are interested in investigating the potential of the EN ISO 52016-1 model to capture the dynamic behaviour of the building. A NZEB single-family house in Northern Italy, where the thermal loads are met by a domestic air handling unit (AHU) with heat recovery was taken as a case study. The TRNSYS model is calibrated using data available from the 15-minute monitoring of the indoor/outdoor temperatures, the electrical energy consumption and the source/sink temperatures of the heat pump, and then compared with the result of the standard model in terms of both monthly thermal energy demand and hourly heating demand. The simplified model overestimates the annual heating demand compared to the detained model, but is able to capture the daily maximum both in terms of value and temporal cadence

x This article proposes a renovation concept for multi-family houses and apartment blocks based on a groundwater loop with heat pumps supplied by groundwater. The study applies the proposed concept to a multi-family building in the province of Milan. The analysis relies on dynamic energy simulations of the building and thermo-hydraulic simulations of the low-temperature distribution circuit. Energy, economic, and environmental indicators are evaluated to compare the proposed solution against a benchmark retrofit with individual condensing gas boilers. The study demonstrates that the proposed renovation concept leads to increased Energy Efficiency Class compared to the benchmark renovation scenario, as well as to lower operating costs and CO2 emissions. The proposed concept is promising, especially for areas where ground-water is easily available, and no local legal restrictions are present.

x It is widely recognized that the shading effect between buildings significantly contributes to cooling and heating loads, independent of individual building performance. This necessitates energy normalization for the shading effect to ensure a more objective building performance assessment, requiring an urban database containing the geometric interactions between buildings for analysis. However, in the real world, obtaining data about shade and solar radiation reduced or generated by adjacent buildings is challenging. Such data are crucial for energy normalization concerning the shading effect, and it necessitates the introduction of scientific tools to complement them. With this in mind, the authors suggest the urban-scaled building shading simulation based on the geographic information system (GIS) to address the data acquisition challenge. The GIS serves as an urban database, integrating diverse city information such as buildings, energy, finance, demographics, and transportation, with spatial information as its core, based on a coordinate system. This study utilized the GIS called “Road Name Address System”, managed by the Korean government to foster the address-based industry, as the primary input data. EnergyPlus, the whole building energy simulation, was employed as the virtual experiment tool about the geometric interactions between buildings and to quantify the shading and solar radiation on building surfaces. In this paper,the authors discuss how the database of shading and solar irradiation on building surfaces was constructed based on the urban-scaled EnergyPlus simulation and anticipate that the data augmentation with the virtual experiments will contribute to a better explanation of the macroscopic dynamic characteristics of buildings.

x This study presents a holistic approach to evaluating the heating refurbishment of a historic Victorian hall in Brighton, UK, using infrared ceiling panels. While field studies have explored radiant heating ceiling panels in new constructions, limited research has investigated their application in renovating historic buildings with highly dissipative envelopes. The methodology addresses this gap and integrates perceived thermal comfort, financial feasibility, and environmental impact. The study involved a two-phase method: a thermal comfort analysis and Building Energy Simulations (BES). Results revealed that while infrared panels are easy to install, their environmental impact outweighs alternatives requiring more complex installations but offering economic returns and user satisfaction. The study provides valuable guidelines for designing and installing ceiling radiant systems in large community spaces, emphasizing comprehensive planning to achieve user comfort, energy savings, and environmental sustainability.

x Personal Comfort Systems (PCSs) have emerged as a solution to customize thermal conditions at individual work-stations, potentially reducing overall energy consumption. This study investigates the optimal utilization of PCSs in office environments extending beyond their thermal comfort provision to delve into their overall energy performance, considering various HVAC systems, building insulation levels, and occupancy patterns. Building dynamic Energy Simulations (BES) were conducted for an open-plan office in London, utilizing heating desks. The evaluation method involves comparing scenarios with and without PCSs across various indices, including energy cost and Primary Energy consumption. Results highlight the year-round adaptability of PCSs, offering insights into their efficacy, efficiency, and potential impacts in both new and existing buildings. The absolute savings vary between non-insulated and highly insulated buildings and the study suggests integrating PCSs into building design for optimized energy efficiency and cost-effectiveness.

x To forward renewable energy as a self-reliant option of energy production, the Government of India is promoting the extensive adoption of Rooftop Solar Photovoltaic (PV) in domestic buildings. Rooftop solar PV systems offer the dual benefit of being a clean energy source and serving as shading devices for roofs, reducing the impact of incident solar radiation. However, the effectiveness of PV shading in minimizing incident solar radiation on mounting surfaces depends on the urban context such as neighbouring building heights and distances between buildings, as well as on the mounting angle and geometry of the PV panels. This study investigates the potential of a roof-mounted PV as a shading element for a typical and retrofitted roof of a low-rise building in a warm and humid climate in Kharagpur, West Bengal. To identify the geometry of PV panels, a grid-connected PV system was first designed for the selected residential unit using PVSyst. The identified PV structure (with dimensions 5.5 m (l) X 4 m (w)) has been considered, mounted over the building at a height of 1.9 m with a tilt of 22° facing south (true azimuth). DesignBuilder, integrated with the EnergyPlus building en-ergy simulation engine, is used to simulate the model to predict the heat transfer through the roofing structure and evaluate the change in the cooling demand associated with it. Three types of roofing structures were studied: an uninsulated roof, a cool roof retrofit, and a roof with mounted PV structure. The results show that the PV structure can provide additional shade to the roof, decreasing the conductive heat gained by incident solar radiation through the roofing assembly by 13.7 % and 9 % for the uninsulated and cool roof cases, respectively. Considering this study observes the Solar PV as a detached and mounted structure, focussing solely on its shading, the reduction in heat gain also resulted in a decrease in the annual cooling demand of the building, demonstrating the effectiveness of PV panels not only as an energy generation solution but also as a thermal management strat-egy for buildings in warm and humid climates.

x In recent years, vertical greening systems have been progressively used not only on the external side of the building but also within indoor spaces. In parallel to other IEQ domains as thermal comfort, air and acoustic quality, an Indoor Living Wall (ILW) impacts lighting quality. In lighting design with specific simulation software, it is fundamental set the most appropriate colouration and reflectance coefficients (ρs) of the surfaces. Otherwise, plants’ reflectance coefficients are difficult to estimate since they do not have any of the following characteristics: planarity, colour and texture uniformity. In addition, each plant’s essence is characterized by peculiar lighting and growing properties. These factors make the design process quite tricky because the unknown distance between simulated lighting conditions and real lighting performances is difficult to be evaluated in advance. This research describes a case study where a room containing an ILW is simulated with DialuxEVO and then compared and validated with in situ monitored data. An empirical procedure for estimating ρs of the ILW in situ is used. The aim is to assess the level of precision of the previous procedure by comparing measured and simulated lighting data in order to carry out useful hints for ILW lighting simulations for designers.

x The net-zero energy concept significantly impacts global goals regarding energy accessibility (SDG 7) and responsible consumption (SDG 12), particularly in the building sector, which accounts for substantial energy use and green-house gas emissions. While extensive research on Net Zero Energy Buildings (NZEB) has focused on the global north, tropical regions require further study, where high solar radiation, temperatures, and humidity challenge building performance throughout the year. Addressing problems like mold growth caused by these tropical climate aspects can undermine NZEB's performance. This study aims to evaluate the impact of mold growth on a representative building under the tropical climate of Panama City (high temperatures and humidity) and Boquete (low temperatures and high humidity). Long-term hygrothermal and energy performance analyses are conducted using simulation software to assess when and how mold growth affects building performance. Mold can harm the health of occupants and increase energy consumption, as additional humidity control devices may be required after the building's design phase.

x Overheating in buildings is a prevalent issue during summer, especially in school buildings due to their design and use. Despite schools being mostly closed during peak summer months, warmer temperatures in May, June, and September exacerbate the situation. We analyzed a primary school building in Budapest, conducting dynamic simulations to evaluate interventions such as flat roof renovations, window shading techniques, passive ventilation strategies, and a comprehensive ‘nearly zero’ energy retrofit. Systematic night-time ventilation proved an effective tool for summer cooling, offering a sustainable, cost-effective solution. The simulations revealed that the current state of the primary school leads to significant overheating. However, the cases revealed that systematic night-time ventilation of the buildings is an effective tool for summer cooling. Additionally, installing shades proved beneficial, installing external overhangs or shades offers practical retrofit options. Conversely, flat roof insulation and energy renovation resulted in slightly worse summer overheating values. Among the solutions, light-colored re-flective surface waterproofing performed the best, but further studies with green roof layering are still worthwhile. The study also revealed that a ‘nearly zero’ energy efficiency retrofit focusing solely on thermal insulation and airtightness led to higher indoor temperatures without altering ventilation patterns. This highlights the need for a balanced approach that includes both insulation and ventilation. Combining night-time ventilation with window shading was the most effective strategy to mitigate over-heating in schools. These findings can guide energy renovations in educational facilities to enhance comfort and sustainability, ultimately creating a healthier learning environment for students and reducing energy consumption.

x The paper analyses using recycled materials for insulation panels, focusing on repurposing surgical masks for building insulation in a circular economy. Since insulation panels made from recycled materials are suitable for use in disadvantaged contexts, dynamic simulations are performed before and after applying the panels in an apartment of approximately 80 m² of floor area, part of a social housing complex in Milan (Italy). The TRNSYS software analysis focuses on the heating season, assessing the impact before and after energy retrofit interventions with an inside application of insulation panels. Additionally, further analyses compare energy savings using commercial insulants like mineral wool and polystyrene. Results show that the reduction in thermal energy demand for heating employing commercial insulants is comparable to the obtained from employing non-commercial insulants. Moreover, the comfort analysis also displays similar results after the employment of commercial and non-commercial insulants.

x The paper provides an analysis of the application of reinforcement learning (RL) in the domain of building controls, summarizing four years of research. The primary focus is exploring RL's potential to adaptively learn from building data, bypassing the need for individualized extensive building modeling efforts and enabling the transfer and adaption of trained agents to similar building environments. Despite its promising prospects, RL faces challenges such as extended training durations, instability during early exploration phases, and issues in interpreting the actions of trained agents. The research was focused on two core areas. The first area investigates strategies to enhance RL agents' learning efficiency and stability in building control contexts with approaches such as imitation learning, inverse RL, and online learning with guided exploration with surrogate models utilizing rule-based controls, showing significant improvements in the training process. The second area addresses the critical aspects of scalability and interpretability of RL agents. It examines the feasibility of transferring trained agents to various buildings, potentially with new objectives, highlighting RL's adaptability and practical applicability in real-world building control scenarios. In summary, this paper consolidates critical findings from the research and offers actionable insights and recommendations for practical deployment and training RL in building energy management systems without extensive building modeling efforts.nIt emphasizes the transformative potential of RL in this field and suggests avenues for future exploration and development.

x This study aims to enhance the energy performance and user comfort of educational buildings, focusing on the BME Building ST as a case study. Using a comprehensive approach that combines dynamic energy simulations and genetic algorithms, we explored optimal renovation alternatives for the building envelope. Various thermal insulation materials and configurations were assessed, leading to improved user comfort and reduced energy demand in all simulated versions. Notably, models with greater thermal insulation exhibited higher comfort levels. Additionally, natural-based materials like wood fibre showed significant potential in reducing embodied carbon emissions, particularly in continental climates such as Hungary. The methodology involved creating a BIM model of the building in Autodesk Revit 2023, followed by advanced energy simulations using the EnergyPlus engine. We generated 160 different building versions with varying insulation materials and thicknesses. These simulations were processed in a Python environment utilizing the Eppy package for managing IDF files and the Pymoo package for implementing the NSGA-II optimization algorithm. The energy performance and user comfort of each version were evaluated to identify the best-performing models. The most energy-efficient model featured 12.5 cm vacuum insulation panels on facades and 25 cm mineral wool on roofs. Financial analysis indicated acquisition costs ranging from 1 to 3.5 million EUR, with estimated global costs over a 20-year period between 6.75 to 9.2 million EUR, compared to the reference building’s 7.4 million EUR. The project developed a versatile methodology for multi-objective building energy optimization in a Python environment, applicable to various building types, prioritizing versions with minimal environmental impact and maximal user comfort. The study underscores the potential of energy-efficient renovations to enhance user comfort, reduce energy consumption, and mitigate environmental impacts in educational buildings.

x Occupancy behaviour, including presence at the work-place, has a significant influence on a building's energy requirements. However, modelling occupancy behaviour is complex, multidisciplinary, and stochastic rather than deterministic. As little information about the intended use is available during the building planning phase, general assumptions about occupancy behaviour are made during building simulation and system planning, based on empirical and standardised models. However, these are formulated as generally as possible to achieve the broadest possible applicability. For example, despite improved simulation techniques, assumptions about occupant behaviour in the workplace often lead to deviations from the real situation, i.e. energy performance gaps. A better understanding of the factors that influence occupant behaviour, their weighting, and the improved models derived from them are proving to be crucial for eliminating performance gaps. Using advanced statistical methods and High-Performance Computing, representative samples of potential scenarios were created in this study to fully quantify the impact on energy performance. This was based on minute-by-minute occupancy and energy data from a one-year series of measurements in an open-plan office of Bartenbach, Austria. This research, based on High-Performance Computing, presents a breakdown of organisational and individual factors influencing energy-related occupancy behaviour. The results provide a promising basis for future research and pave the way for more targeted and energy-efficient building planning.

x Leveraging advanced simulation processes and optimization algorithms, this research aims to enhance energy performance and daylight harvesting for a case-study building, the Bullitt Center, Seattle, Washington, U.S.. Specifically, it studies the role of shading devices to conserve energy. Central to this research is the utilization of simulation processes and optimization algorithms as powerful tools to analyse and fine-tune building performance. Through systematic examination, the research offers nuanced insights into the dynamic interplay between architectural elements and environmental conditions, highlighting the potential of advanced simulation methodologies to address contemporary challenges in building design and performance.

x A micro-cogeneration solution based on an alkaline fuel cell, supplied by solar hydrogen to satisfy electric and thermal energy demands in an off-grid building, is investigated. Hydrogen is produced by using PV surpluses through an alkaline electrolyzer and stored in a pressurized gas tank. Regarding a reference building with a gross footprint of 100 m² affected by severe winter climate conditions and heated by a radiant floor supplied by an air-water heat pump, TRNSYS simulations showed that 14.4 kWp of PV power and 5 m³ of hydrogen tank volume ensure the building energy self-sustainability. Indoor comfort conditions are achieved by observing air temperatures always in the range of 19–21 °C during winter. The thermal power recovered from the fuel cell reduced DHW demand noticeably. Results show that hydrogen acts as an interseasonal storage with summer overproductions needed for the fuel-cell winter operation. An economic analysis confirms that the system is profitable when compared with electric storage made of batteries periodically replaced.

x Solutions conceived to mitigate the mismatching between electricity production and demand in buildings are decisive in maximizing the benefits of Renewable Energy Communities. In this context, Building Energy Simulation (BES) tools can be used for accurately assessing energy flows considering variable conditions, especially if equipped with electric generation systems for heating and cooling. In this paper, a PV generator for a scholastic canteen belonging to a municipal REC, in which the main electric load is represented by a VRF heat pump, is evaluated by TRNSYS simulation to optimize the self-consumption share. A monitoring campaign targeted at the collection of real electrical profiles and climatic data was carried out to validate the building-plant model. A simultaneity factor (SF) between electric demand and production was introduced to evaluate actual self-consumption and electric surplus to share within the REC. Results showed the decisive role of Demand Side Management, whereas mono-crystalline cells perform better than other technologies avoiding installing the maximum installable PV peak power. For the considered case study, despite the building being occupied occasionally, an SF of about 75% can be achieved.

x Cities are crucial for the energy transition, as recognized by the European Union in policies such as the Fit for 55 package and the Climate-Neutral and Smart Cities mission. The former calls for the revision of several directives, among which the Energy Performance of Buildings Directive (EPBD) plays a major role, targeting the phasing out of fossil fuels and the achievement of minimum performance objectives for all existing buildings. It reinforced the role of the Energy Performance Certificate (EPC) as a shared evaluation schema. However, considering the 30-50% coverage of EPCs in the European building stock, new methodologies and models are required to assess the building stock extensively. Considering the valuable data contained in EPCs, these can be used to train Urban Building Energy Models which leverage the potential of Earth Observation. This study proposes a new method to segment the building stock according to thermographic pictures, resorting to EPC information for the energy class distribution analysis. Thermographic values are used to assess thermal losses and replicate the energy class distribution accordingly. Different EPC data are assessed in order to understand the best configuration both in terms of share between training and validation data and of the need for potential pre-filtering. The method appears to be reliable – with 66% of buildings classified correctly on average – yet simple, thus being attractive for policymakers to define retrofitting campaigns able to meet European requirements. With simplicity and flexibility being the main strengths of the method, it is also possible to consider additional inputs and make the model more complex to improve the accuracy.

x The building sector is responsible for about 36% of global final energy use and Heating, Ventilation and Air-Conditioning (HVAC) systems are responsible for about 50÷60% of the building sector’s energy demand. In this paper, a detailed dynamic simulation model of a typical HVAC system including a single duct dual-fan constant air volume Air-Handling Unit(AHU) has been developed via the TRaNsient SYStems software platform (TRNSYS 18). The simulation outputs were compared with field operation data measured during 14 experiments performed with reference to a fully instrumented HVAC set-up serving the SENS i-Lab of the Department of Architecture and Industrial Design of the University of Campania Luigi Vanvitelli (Aversa, south of Italy). The comparison was carried out to validate and assess the simulation model accuracy. The results highlighted a high capability of the developed model in simulating the experimental behaviour, with maximum percentage differences between the predicted and experimental values up to -6.0%, 18.3%, -9.1%, -10.6%, -15.3% in terms of heating coil energy, cooling coil energy,humidifier electric demand, heat pump electric consumption and refrigerating system electricity request, respectively.

x Nature has been fundamental in influencing the design of traditional habitations across the globe. Climatological factors such as wind directions, sun path, precipitation,etc., play a vital role in the design of buildings for occupants and community comfort keeping the local lifestyles into account. This research aims to explore the impact of climatological parameters (solar geometry and wind patterns) on the design of vernacular settlements. This study particularly looks into orientation of streets and building units, materials, and building features. The study is based on real-time on-site fieldwork complemented with computational models.

x Indoor environment quality (IEQ) has emerged as a crucial factor after the COVID-19 pandemic determining the health, well-being and productivity of occupants. The current research aims to examine the buildings’ ability to regulate indoor air quality, specifically looking at indoor moisture and toxicity characterised in terms of total volatile organic compounds (TVOCs). According to the United States Environmental Protection Agency (USEPA), the concentration of these compounds is two to five times greater indoors as compared to outdoors. Building materials and indoor surfaces such as paints, synthetic floorings, carpets, etc., constantly emit TVOCs. The dependence of TVOC on varying moisture regimes has been examined in this study. The climatic response of these dwellings has been examined through indoor comfort and air quality parameters. The indoor temperature, humidity and TVOC levels in conventional and vernacular residential dwellings have been examined for the warm and humid climatic zone. Concurrently, these dwellings have also been modelled (and validated with real-time data for temperature and relative humidity levels) using Design Builder. This study examines indoor moisture and toxicity (TVOCs) levels in vernacular and conventional buildings for three climate-change scenarios. Simulation studies gave an insight into how the indoor temperature, indoor humidity and indoor TVOC levels, attributed to fresh paints, could increase over the years as per different climate change scenarios. The ageing of the wall paints has been examined further to compare how power decay affects the emissions in the future. The naturally derived materials do not have any harmful chemicals and, hence, emit less TVOCs as compared to the conventional building materials, thereby, maintaining better indoor air quality for the occupants.

x Indoor Earth-based plasters in buildings offer indoor humidity regulation through moisture buffering. This study examines the applicability of using earth-based plaster in-doors as a passive strategy for regulating indoor humidity for occupant comfort, using a simulation-based approach. BESTEST model geometry was used to simulate indoor T/RH conditions with varying window-to-wall ratio (WWR) and air changes per hour (ACH) for Indian climate zones using EMPD (Effective Moisture Penetration Depth)model in DesignBuilder tool. Experimentally derived material properties of earth-plaster were used as input to the model. The results revealed that the surface area available for moisture sorption/desorption or WWR is critical in determining the moisture buffering potential. High WWR leads to low surface area available for moisture buffering,resulting in high diurnal indoor Humidity Ratio peaks. Also, air changes per hour (ACH) have a significant bearing on moisture buffering. As the ACH increases, the peaks in indoor HR increase and become closer to the out-door HR. In this chapter, monthly mean indoor HR for the given geometry was computed for the 5 climate zones of India. These results were examined vis-à-vis indoor comfort Humidity Ratio recommendations for comfort (ac-counting for thermal, skin, and respiratory comfort) for oc-cupants in the rural Indian setup as reported in our previous work. The results suggest that earth-plaster for moisture buffering can be effectively used in Warm and Humid, Hot and Dry, and Composite climate zones of India. Using this strategy in Temperate and Cold climate zones was not found effective. Earth-based plasters are derived from natural soil, and their use can avoid cementitious (energy and carbon-intensive) material and support occupants' wellness simultaneously.

x The need to mitigate the risks of overheating in buildings due to climate change has highlighted the importance of accurate models for predicting indoor temperatures and thermal comfort, particularly after retrofitting. To this end, white-box models, such as Building Energy Models(BEMs), and black-box models, such as Long Short-Term Memory (LSTM) neural networks, have been extensively used in recent decades. While BEMs provide detailed in-sights through physically-based simulations, requiring calibration for enhanced accuracy, LSTMs provide a data-driven approach that captures complex thermal dynamics with greater simplicity, albeit with less interpretability. Few studies have undertaken a comparative analysis of these models in terms of prediction accuracy, especially across pre- and post-retrofit conditions and different lengths of training periods. Thus, in this study, a comparison between the predicting capabilities of calibrated BEMs and LSTM in summer was carried out using two real monitored mock-ups in Northern Italy representing both pre- and post-retrofit conditions. The results show that, for the considered limited training periods (8 and 3 days), the dataset size does not significantly influence BEM accuracy, while LSTM accuracy is more affected. Moreover, BEMs show higher prediction accuracy in scenarios with higher indoor air temperature (IAT) variability, i.e. where unseen data could be less predictable, such as in pre-retrofit conditions. LSTMs, however, excel in low-variability scenarios, such as the post-retrofit conditions in this case. This study highlights the critical need for careful model selection and calibration based on the data availability and building typology to ensure prediction reliability.

x This study compares three different radiation decomposition models (Erbs, DIRINT, and DISC) for estimating direct normal radiation to the data from the reanalysis dataset ERA5. It also evaluates the impact of considering these different models and datasets on building energy simulation outcomes for three locations in Brazil (Brasília, Salvador, and São Paulo). As the simulation study case, we analyzed a typical residential building in the Brazilian context. This building model was analyzed in three different cases (Brazilian standard building characteristics reference, low solar absorptance values, and considering a 0.80 m overhang). Regarding radiation datasets, the Erbs model exhibited the lowest RMSE for direct and diffuse radiation compared to the monthly values provided by the Brazilian Solar Atlas. By analyzing the RMSE values, we demonstrated that ERA5 over-estimated direct normal radiation while significantly underestimating diffuse values compared to the Solar Atlas. Concerning simulation results, we observed differences of up to 14% higher cooling load values when comparing the results using ERA5 data with the DISC model ones. However, maximum operative temperatures did not show such significant differences, with a maximum deviation of 1%. Also, the three cases tested demonstrated the sensitivity of the building simulation to the different radiation datasets. These results are important for advancing the understanding of the impacts of using reanalysis datasets, which is becoming an increasingly common approach.

x Renewable energy technologies represent a promising option to cover the building sector energy needs. In particular, micro vertical axis wind turbines are emerging as a viable solution thanks to their ability to capture wind from all directions and efficiently convert wind energy into electric power. In this study, the performance of a 2.2 kW commercial vertical axis micro wind turbine serving a typical residential building located into five different cities in Italy (Naples, Rome, Milan, Palermo, Alghero) has been analysed by means of the TRaNsient SYStems simulation tool (TRNSYS) allowing us to evaluate the effects of climatic conditions (including wind velocity). Simulations have been performed by considering three different sources of long-term wind speed data for each city: (a) the Typical Meteorological Year version 2 weather database (TMY2), (b) the NASA LaRC POWER database, and (c) the Open-Meteo database. The results highlighted that (a) the selected wind speed datasets significantly affect the assessment of wind turbine performance, as well as (b) the proposed micro wind turbine can reduce the electric energy imported from the grid, the equivalent global CO2 emissions and the operating costs up to 43.46%, 43.50% and 95.62%, respectively.

x The recent focus on new strategies towards the achievement of smart cities and energy community goals has required a massive use of urban scale tools for building energy modelling. The main aim is to support decision makers to address urban energy policies allowing the develo-ment of energy scenarios combining multiple actions. Despite some exceptions of simplified input datasets, urban scale simulation tools commonly require a large amount of input data to describe the building stock investigated, depending on the tool and the modelling purpose. Several literature studies explained the building stock modelling challenge, enhancing the current lack of complete data-bases describing the national building stock. The regional datasets of energy performance certificates are not fit for purpose and are often not available for research or statistical analysis. To tackle this issue, a hybrid approach combining different sources of information can be implemented; however, large quantities of data belonging to heterogeneous datasets must be updated, harmonized, integrated, potentially reducing the available data or reducing the accuracy. For these reasons, a possible way is the definition of archetype and prototype buildings, defined as ideal buildings described by sets of characteristics considered as representative of certain clusters of the building stock. However, a major challenge still must be solved: how is it possible to properly distribute archetype properties respecting the real presence of buildings within the considered location? In this work the last Italian population and housing census has been used to determine the distribution of building typologies according to the Italian building stock. Statistical analysis allowed for the clustering of the available information to deal with the lack of information for urban scale modelling tools, providing useful data for the representativity of available information within the national building stock. Future applications will apply the methodology to other case studies.

x The most important challenge of energy modelling is certainly to guarantee that the energy consumption predicted by the simulation during the Design phase reflects the real consumption of the building once built. With the increase in energy consumption monitoring, in recent years it has been realized that there is often a substantial difference between expected and actual energy consumption; this difference is called the “Performance Gap” or “Energy Gap”. Furthermore, the energy classification of buildings according to methodologies recognized by Italian regulations is becoming increasingly important, in order to have access to economic benefits or building bonuses. The scope of this work is to compare the energy consumption estimated through dynamic energy simulations and through the Italian regulation-based software with the real consumption of the building, evaluating the reliability of the calculation procedures and calibrating the dynamic model with the real usage schedules (post occupancy evaluation). This study is based on a large recent office building, with high national and international energy performance standards (LEED certified).

x The thermal behaviour of buildings’ opaque components is still one of the most important aspects in the overall energy performance of a building. In the framework of the reduction of greenhouse gas emissions and global energy consumptions, the optimization of the walls’ composition can lead to more sustainable and highly-efficient buildings, both for new and existing constructions. One of the parameters describing the thermal performance of a building’s wall is the thermal transmittance or U-value. The determination of the U-value is usually done through analytical methods according to the Standard UNI EN 6946, especially when components are characterized by simple geometries and uniform layers. However, when such a hypothesis does not stand anymore, experimental procedures in controlled environments must be adopted, e.g., climatic chambers. Stationary methodologies, like the ones suggested either by the standard UNI 1934 or the UNI EN ISO 8990, are extremely accurate and reliable, but the main drawback is the long-time procedure required, especially for highly-insulated walls with larger thicknesses. To overcome this issue and to save both time and energy required to run the experiment, techniques based on the response factors theory have been recently gained interest with the aim of finding an alternative methodology to the standard time-consuming one, without compromising the accuracy of results. The simple application of a triangular temperature solicitation at one side of the wall, allows the determination of the thermal response of the wall in time, as well as, the assessment of the U-value, within a significant shorter time. Besides, such dynamic methods are capable of considering also the thermal capacity of the wall, which also influences its thermal performance. Nevertheless, the technique relies on very strict experimental conditions, e.g., high signal to noise ratios. For this reason, this work investigates the effect that noisy boundary conditions, in terms of temperature, have on the determination of the thermal transmittance of walls. To do this, simulation tests in dynamic regime were developed in a COMSOL Multiphysics® environment. By applying multiple levels of noise to the boundary conditions, simulations are run and results in terms of perturbated heat fluxes and computed U-values are analysed. Results are then compared to the reference U-value obtained through a steady-state simulation. The main outcomes of this research can lead to practical guidelines for an alternative experimental technique aimed at measuring thermal transmittances of opaque buildings’ components in controlled ambient conditions

x Thermal comfort assessment in buildings usually relies on the calculation of Predicted Mean Vote (PMV) which is determined by four environmental variables, such as air temperature, air humidity, air velocity and mean radiant temperature, and by two personal factors, namely the metabolic rate and the clothing level. The latter factor is fundamental in determining the thermal sensation since it can be changed and adapted in response to the indoor conditions, thus allowing an extension of the neutral temperature range. Moreover, the uncertainty of clothing level in simulated models can affect the reliability of results in terms of thermal comfort and overall IEQ assessment. This study aims to calibrate existing models on an extensive set of data collected in an Italian high school located near Rome and to build a new clothing model. The outdoor and indoor environmental conditions in 22 natural ventilated classrooms were monitored during the school years 2020-2022. Students’ thermal sensation votes and the corresponding clothing levels were surveyed during regular lessons. First, the physical variables used in the literature to predict clothing insulation were at first analyzed to highlight the significant ones based on the collected data. Second, the significant physical variable (i.e., operative temperature) was used as input to feed existing models and to predict clothing insulation; the predicted values were then compared with the observed mean clothing insulation of the students in each classroom. Third, a calibration of a clothing linear model based on operative temperature was carried out and a new linear model based on the indoor running mean temperature was set. Finally, to explore to which extent the linear clothing model based on Top can affect the thermal comfort simulation, the Predicted Mean Vote (PMV) was calculated.

x Challenges of climate change affect various aspects of human life. This research focuses on the health implications resulting from climate-induced alterations and underlines the vulnerabilities experienced by specific demographic groups,notably the elderly and socioeconomically disadvantaged. These individuals frequently suffer the impact of extreme heat events due to their limited access to cooling technologies, such as air conditioning units, thus exacerbating their vulnerability to heat-related illnesses and diminishing their overall quality of life. Relying on air conditioning systems causes various limitations, including increased energy consumption, exacerbation of greenhouse gas emissions, and the risk of po-er outages. Moreover, rules and financial problems such as initial and operational costs block widespread adoption, particularly among low-income households. In response to these problems, this study promotes an affordable alternative strategy focused on utilizing practical yet effective methods, electric fans, window coverings, and natural ventilation to alleviate indoor heat stress and to evaluate their efficacy in enhancing thermal comfort and protecting the well-being of occupants. Numerical simulations were conducted using EnergyPlus and Design Builder software. The simulations focused on a prototypical building, reflecting the common architectural features, representative of multi-family housing built from 1961 to 1975, using the Tabula web tool. The simulations were executed for three cities, Palermo, Pisa, and Trieste in Italy. The analytical framework of this study extends beyond historical weather data, including datasets covering future projections. This comprehensive approach enhances analysis by integrating changing climate conditions. The findings reveal a significant reduction in hours with heat strain with electric fans emerging as a key tool in mitigating them, even under worst-case scenarios. Natural ventilation and window shading also play significant roles in reducing heat strain hours within apartments. In conclusion, the study emphasizes the urgent need to address the multifaceted impacts of climate change on public health. It advocates for affordable solutions such as electric fans, window coverings, and natural ventilation to combat high internal temperatures and to contribute to broader environmental sustainability goals.

x Indirect CO2-based measurement of the ventilation rate is a well-established method based upon a balance equation of the CO2 generated by people and dispersed by infiltration and ventilation. In principle, ventilation rate can also be estimated by water vapour mass balance when storage terms are properly modelled. This work aims to bench-mark the CO2-based model and the water vapour-based model to estimate of ventilation rate in classrooms. The case study is a secondary school in Morlupo, Rome. Here,four naturally ventilated classrooms and the adjacent spaces were monitored for a two-week period (indoor temperature and relative humidity RH, CO2 concentration, occupancy, outdoor temperature and RH). The ventilation rate for each classroom was estimated using the in-direct CO2-based method and then fed to an energy model developed in TRNSYS. Buffer effects for moisture were estimated using a single-layer Equivalent Penetration Depth Model. The simulated humidity ratio was compared to the measured one and input parameters for the storage models were tweaked until convergence using an optimization algorithm. Such process was repeated for 2 of the 4 class-rooms. Then, the tuned parameters identified for the storage model were used as input on the remaining 2 class-rooms and the ventilation rate obtained using the water-vapour based method was compared to the results of the CO2-based method. Results show that the water vapour-based method significantly underestimates the air changes per hour, calling for an in-depth analysis of storage buffer terms.

x Urban Heat Island (UHI) effects, intensified by growing urbanization, significantly impact thermal comfort and energy demand in cities. To accurately model these effects in building performance and urban energy simulations, precise weather data and boundary conditions are essential. Although weather stations in city centers are increasingly used to develop typical meteorological years, they often fail to capture the microclimate variations across urban areas. New tools and methods are thus needed to help building professionals and municipalities assess UHI severity, use more representative weather data, and evaluate the impact of buildings on the urban microclimate. Among available tools for UHI impact assessment, Computational Fluid Dynamics (CFD) models offer detailed analysis but are computationally intensive and impractical for large-scale, year-round studies. Conversely, equivalent RC net-works are more computationally efficient but still require extensive inputs, limiting their widespread use in large cities. This research introduces a new workflow using correlations to estimate UHI effects from rural weather data. The MIT Urban Weather Generator (UWG) was used to simulate UHI in representative districts, with the results employed to develop correlations for mapping local microclimates across urban areas. The proposed methodology is preliminary applied to the Italian city of Turin, focusing primarily on the correlation between urba morphology and the UHI phenomena (i.e., paying attention to those variables with the most significant effects on the local urban microclimate, according to the literature). The UHI impact has been quantified in terms of differential heating and cooling degree-days with respect to the rural environment. Results prove that with a training set of about 5% of the city, modelled in detail with UWG, developed correlations appear robust enough to describe the phenomenon for residential districts of Turin.

x In the wake of the worsening of the energy crisis in winter 2022, several public administrations in Italy recommended simple energy systems operation control measures, to be implemented in the local building stock to reduce energy consumption and produce economic savings in the short term. In particular, in the municipality of Bolzano, Italy, these measures ranged from lowering the heating setpoint temperature, implementing systems setbacks or ON/OFF setting and reducing ventilation rates. However, these measures were applied to all buildings, without distinguishing vintage and type, with the risk of worsening the indoor environmental quality (IEQ) in some of them. In this context, this study focuses on the analysis of two kindergartens of dated and recent construction in the city of Bolzano, with the aim of evaluating the applicability of the proposed energy-saving control measures on buildings representative of “old” and recent constructions. Results proved the importance of carefully considering building specific features to design effective HVAC systems operation measures, able to optimize the systems performance and guarantee adequate IEQ conditions.

x This study introduces an innovative high-efficiency air conditioning system that utilizes solar-assisted heat pumps to enhance the coefficient of performance by elevating the thermal level of the lower temperature heat source. Solar energy stored in thermal storage is used to optimize operating conditions by increasing the cold source temperature. A demonstrator of such a system is investigated by referring to the residential building “Chi-odo 2” located at the University of Calabria, where an existing plant equipped with heat pumps in master-slave configuration are already operational. The simulation model was developed within the TRNSYS environment. The development process of the virtual system model is presented in detail, encompassing solar collectors, thermal storage, heat pump and a photovoltaic system. Through an analysis of the winter operation of the system, the study identifies key requirements, including the optimal thermal storage volume and the optimal size of solar collectors, to maximize energy efficiency. Specific operating conditions are proposed, such as the synergis-tic use of solar collectors and heat pump in particular thermal scenarios, to enhance performance.

x Modern glazing systems, including triple-glazing with integrated blinds and advanced façade technologies, exhibit complex thermal behaviors that traditional metrics like the Solar Heat Gain Coefficient (SHGC) and the thermal transmittance (U-value) inadequately capture. This paper introduces novel Key Performance Indicators (KPIs) for assessing the solar performance of glazing units under dynamic, realistic conditions. Such new proposed KPIs — Daily Integrated SHGC and Maximum Solar Gain Ratio MSGR — provide a more accurate reflection of a building's energy performance by considering daily variations in solar exposure and the way the radiation is transferred through a complex transparent component. This research aims to validate the new KPIs in a simulated environment before applying them to actual building components, offering a comprehensive evaluation of their variability with changing environmental and configuration variables.

x This paper utilizes High Dynamic Range Imaging and deep learning that utilize pixelwise information from the entire luminance distribution in the field of view to classify day-lighting preferences of office workers. Generated luminance and contrast similarity maps were used for training convolutional neural network (CNN) models to classify the occupant’s visual preferences. Preference datasets for 11 individ-uals, collected in real offices, were used to evaluate the preference classification performance. The results showed the superiority of the luminance similarity map as a visual preference indicator compared to common static lighting parameters.

x Upcycling End-of-Life Solar Photovoltaic panels in buildings is a novel approach to manage the imminent growing problem of PV waste. The EoL-PV panels have been characterized to have a high U-value and low thermal mass. To address this issue, interventions involving tandem plywood (preferably EoL packaging plywood) have been proposed and tested through whole building simulations in our preceding studies. A typical PV panel is encased in an aluminium frame whose thermal conductivity is of two orders of magnitude higher than a PV panel. This causes thermal bridging, which must be accounted for in the U-value calculation of PV panels. In this study, the thermal bridging effect due to the aluminium frame is analysed using two-dimensional finite-element method-based tool,THERM. A rise in the U-value of around 13% has been estimated due to the presence of a frame in PV panel. To demonstrate the impact of U-value of PV panel on the building’s thermal performance, simulations have been performed with lumped-capacitance simple single zone model in TRNSYS. One of the interventions, having the highest plywood thickness in tandem to the EoL-PV panel,was the least sensitive to the thermal bridging effect on annual heating/cooling load and fared best in terms of thermal mass.

x The building sector plays a major role in terms of energy consumption and consequently carbon emissions in a city. In a typical European city, the share of CO2 related to this sector is around 40-50%, being the most impacting one. In this context, characterised by high complexity, it is necessary to develop manageable, science-based models that policymakers can use to design and simulate the impact of feasible decarbonisation actions over space and time. This paper presents a simulation platform capable of modelling actions for city decarbonization, particularly focusing on the building sector. Each action is modelled in terms of primary energy exploitation (type and quantity) and its impacts on energy consumption and emissions using a tailored set of metrics. This involves considering the unique characteristics and challenges of the city, such as its existing infrastructure, building stock, energy sources,and policy context. The proposed approach is applied to a real European city to demonstrate its feasibility and assess its effectiveness in achieving emissions reduction targets. The results provide effective support to the municipality in setting up the city action plan towards climate neutrality.

x Thermal Source Network (TSN) district heating systems are a sustainable solution for integrating renewable energy and waste heat sources in the urban heating sector. These networks typically employ heat pump-based prosumers on the supply side. On the demand side, a heat pump substation at each consumer upgrades the heat received from the district heating network to the suitable temperature for a given building. However, there is a gap in the literature for an evaluation metric for assessing the efficiency of the prosumers in TSN networks. This paper proposes a new evaluation framework, the Prosumer Performance Index (PPI), to evaluate low-grade heat prosumers' efficiency in a TSN system from the aspects of energy, economics, and environment. This framework facilitates district heating owners' decision-making using low-grade waste heat in TSN networks. The simulation results demonstrate the variation of PPI over a year for four different scenarios of the central heat pump plant’s supply temperature setpoints. Overall, by promoting energy efficiency, economic viability, and environmental sustainability, the PPI contributes to advancing sustainable urban heating solutions in alignment with global climate objectives.

x Today, the increasing need for inclusive school environments is driven by the growing population of neurodivergent individuals, particularly those sensitive to sudden and loud noises. Addressing their specifi needs enhances their educational and social performance and improves conditions for all students. Inclusive design can lead to more effective learning environments, fostering a sense of belonging and reducing stress for all occupants. This study investigates the influence of acoustic stressors in school environments that accommodate neurodivergent individuals who are sensitive to sudden and loud noises. The research focuses on identifying noise sources such as objects falling, doors shutting, school bells and chairs scraping. A range of classroom settings wil be simulated to determine whether the produced noise could be configured as a potential stressor for autistic individuals.

x Accurate prediction of Global Horizontal Irradiance (GHI) is crucial for optimizing solar power generation systems, especially in mountainous regions characterized by complex topography and specific microclimates. These areas face significant challenges due to limited availability of reliable data and accuracy issues stemming from the dynamic nature of the atmosphere and local weather conditions. This scarcity of precise GHI measurements impedes the development of accurate solar energy prediction models, affecting both economic and environmental aspects. In this framework, this paper proposes a novel methodology to address data scarcity challenges in solar energy prediction, particularly focusing on Alpine regions. We employ machine learning techniques such as Random Forest (RF) and Extreme Gradient Boosting (XGBoost) regressors, in conjunction with synthetic data generation, to predict GHI. To assess our approach's accuracy, we selected Bolzano as a case study and modelled the PV AC power outputs before and after optimizing GHI data.

x This paper explores the challenges and opportunities in integrating Building Performance Simulation (BPS) in the the design of the built environment. While the complexity of building performance and the challenging sustainability target would benefit from a more systematic adoption of BPS, some limitations are still evident. Process-based changes and new business approaches should complement BPS tools technical innovation to better equip practitioners to contribute to addressing future challenges. The paper addresses the barriers to integrating BPS into professional practice, such as the complexity of simulation tools, the need for specialist knowledge and education, and the lack of a shared participative approach to design and building. The potential of BPS to support integrated performance analysis and its role in transforming design practices to meet national and international carbon reduction targets are examined. Recommendations are suggested for overcoming these barriers and promoting a wider adoption of BPS in professional practice.