Search Results (2,130)

Building performance simulation is crucial for the design and optimization of sustainable buildings. However, the increasing complexity of building systems necessitates advanced modeling techniques capable of handling multi-domain interactions. This paper presents a novel application of the bond graph (BG) methodology to simulate and analyze the thermal behavior of an integrated trigeneration system within an experimental test cell. Unlike conventional simulation approaches, the BG framework enables unified modeling of thermal and hydraulic subsystems, offering a physically consistent and energy-based representation of system dynamics. The study investigates the system’s performance under both dynamic and steady-state conditions across two distinct climatic periods. Validation against experimental data reveals strong agreement between measured and simulated temperatures in heating and cooling scenarios, with minimal deviations. This confirms the method’s reliability and its capacity to capture transient thermal behaviors. The results also demonstrate the BG model’s effectiveness in supporting predictive control strategies, optimizing energy efficiency, and maintaining thermal comfort. By integrating hydraulic circuits and thermal exchange processes within a single modeling framework, this work highlights the potential of bond graphs as a robust and scalable tool for advanced building performance simulation. Full article

Governments worldwide have set ambitious targets for decarbonising energy grids, driving the need for increased renewable energy generation and improved energy efficiency. One key strategy for achieving this involves enhanced energy management in buildings, often using machine learning-based forecasting methods. However, such methods typically rely on extensive historical data collected via costly sensor installations—resources that many buildings lack. This study introduces a novel forecasting approach that eliminates the need for large-scale historical datasets or expensive sensors. By integrating custom-built models with existing energy data, the method applies calculated weighting through a distance matrix and accuracy coefficients to generate reliable forecasts. It uses readily available building attributes—such as floor area and functional type to position a new building within the matrix of existing data. A Euclidian distance matrix, akin to a K-nearest neighbour algorithm, determines the appropriate neural network(s) to utilise. These findings are benchmarked against a consolidated, more sophisticated neural network and a long short-term memory neural network. The dataset has hourly granularity over a 24 h horizon. The model consists of five bespoke neural networks, demonstrating the superiority of other models with a 610 s training duration, uses 500 kB of storage, achieves an R² of 0.9, and attains an average forecasting accuracy of 85.12% in predicting the energy consumption of the five buildings studied. This approach not only contributes to the specific goal of a fully decarbonized energy grid by 2050 but also establishes a robust and efficient methodology for maintaining standards with existing benchmarks while providing more control over the method. Full article

Enhancing the real-world performance of sustainably designed and certified green buildings remains a significant challenge, particularly in hot climates where efforts to improve thermal comfort often conflict with energy efficiency goals. In the United Arab Emirates (UAE), even newly constructed facilities with green building certifications present opportunities for retrofitting and performance optimization. This study investigates the energy and thermal comfort performance of a LEED Gold-certified, mixed-use university campus in Dubai through a calibrated digital twin developed using IES thermal modelling software. The analysis evaluated existing sustainable design strategies alongside three retrofit energy conservation measures (ECMs): (1) improved building envelope U-values, (2) installation of additional daylight sensors, and (3) optimization of fan coil unit efficiency. Simulation results demonstrated that the three ECMs collectively achieved a total reduction of 15% in annual energy consumption. Thermal comfort was assessed using operative temperature distributions, Predicted Mean Vote (PMV), and Predicted Percentage of Dissatisfaction (PPD) metrics. While fan coil optimization yielded the highest energy savings, it led to less favorable comfort outcomes. In contrast, enhancing envelope U-values maintained indoor conditions consistently within ASHRAE-recommended comfort zones. To further support energy reduction and progress toward Net Zero targets, the study also evaluated the integration of a 228.87 kW rooftop solar photovoltaic (PV) system, which offset 8.09% of the campus’s annual energy demand. By applying data-driven thermal modelling to assess retrofit impacts on both energy performance and occupant comfort in a certified green building, this study addresses a critical gap in the literature and offers a replicable framework for advancing building performance in hot climate regions. Full article

Through a systematic review of sustainable rural dwelling recovery, this study offers a broader reflection on retrofitting practices, viewing eco-efficiency as a means to enhance both cultural heritage and agricultural landscapes. The work is based on the assumption that vernacular architecture in rural contexts embodies historical, cultural, and typological values worthy of preservation, while remaining adaptable to reuse through eco-efficient solutions and technological innovation. Using the PRISMA protocol, 115 scientific contributions were selected from 1711 initial records and classified into four macro-groups: landscape relationships; seismic and energy retrofitting; construction techniques and innovative materials; and morphological–typological analysis. Results show a predominance (over 50%) of passive design strategies, compatible materials, and low-impact techniques, while active systems are applied more selectively to protect cultural integrity. The study identifies replicable methodological models combining sustainability, cultural continuity, and functional adaptation, offering recommendations for future operational guidelines. Conscious eco-efficient retrofitting thus emerges as a strategic tool for the integrated valorization of rural landscapes and heritage. Full article

This study presents a topology optimization approach to enhance the discharging performance of a latent heat thermal energy storage (LHTES) system using paraffin wax as the phase-change material (PCM) and a high-conductivity aluminium structure. Solidification is primarily governed by conduction, and the average heat transfer rate during this process is significantly lower than during melting; therefore, the optimization focused on the discharge phase. In a previous study, a novel LHTES device based on a Cartesian lattice was investigated experimentally and numerically. The validated numerical model from that study was adopted as the reference and used in a 2D topology optimization study based on the Solid Isotropic Material with Penalization (SIMP) method. The objective was to promote more uniform temperature distribution and reduce discharging time while maintaining the same aluminium volume fraction as in the reference device. Topology optimization produced a branched fin design, which was then extruded into a 3D model for comparison with the reference geometry. The optimized design resulted in improved temperature uniformity and a faster solidification process. Specifically, the time required to solidify 90% of the PCM was reduced by 12.3%, while the time to release 90% of the latent heat during the solidification process improved by 7.6%. Full article

An efficient integrated energy system (IES) can enhance the potential of building energy conservation and carbon mitigation. However, imbalances between user-side demand and supply side output present formidable challenges to the operational dispatch of building energy systems. To mitigate heat rejection and improve dispatch optimization, an integrated building energy system incorporating waste heat recovery via an absorption heat pump based on the flow temperature model is adopted. A comprehensive analysis was conducted to investigate the correlation among heat pump operational strategies, thermal comfort, and the dynamic thermal storage capacity of piping network systems. The optimization calculations and comparative analyses were conducted across five cases on typical season days via the CPLEX solver with MATLAB R2018a. The simulation results indicate that the operational modes of absorption heat pump reduced the costs by 4.4–8.5%, while the absorption rate of waste heat increased from 37.02% to 51.46%. Additionally, the utilization ratio of battery and thermal storage units decreased by up to 69.82% at most after considering the pipeline thermal inertia and thermal comfort, thus increasing the system’s energy-saving ability and reducing the pressure of energy storage equipment, ultimately increasing the scheduling flexibility of the integrated building energy system. Full article

This article presents a new method of parametric shaping of buildings with buffer spaces characterized by complex forms and effective thermal operation in the moderate climate of the Central Europe Plane. The parameterization of an elaborated thermal qualitative model of buildings with buffer spaces and its configuration based on computer simulations of thermal operation of many discrete models are the specific features of the method. The model uses various original building shapes and a new parametric artificial neural network (a) to automate the calculations and recording of results and (b) to predict a number of new buildings with buffer spaces characterized by effective thermal operation. The configuration of the parametric quantitative model was carried out based on the simulation results of 343 discrete models defined by means of ten independent variables grouping the properties of the building and buffer space related to their forms, materials and air circulation. The analysis performed for the adopted parameter variability ranges indicates a varied impact of these independent variables on the thermal operation of buildings located in a moderate climate. The infiltration and ventilation and physical properties of the windows and walls are the independent variables that most influence the energy savings utilized by the examined buildings with buffer spaces. The optimal values of these variables allow up to 50–60% of the energy supplied by the HVAC system to be saved. The accuracy and universality of the method will continuously be increased in future research by increasing the types and ranges of independent variables. Full article

Improving the energy efficiency of residential buildings is essential for achieving global climate goals and reducing environmental impact. This study analyzes the Total Performance approach using the example of a modern semi-detached house built by a Polish developer, as an example. The building is designed with integrated systems that minimize energy consumption while maintaining resident comfort. The building is equipped with an air-to-water heat pump, underfloor heating, mechanical ventilation with heat recovery, and automatic temperature control systems. Energy efficiency was assessed using ArCADia–TERMOCAD 8.0 software in accordance with Polish Technical Specifications (TS) and verified by monitoring real-time electricity consumption during the heating season. The results show a PED from non-renewable sources of 54.05 kWh/(m²·year), representing a 23% reduction compared to the Polish regulatory limit of 70 kWh/(m²·year). Real-time monitoring conducted from December 2024 to April 2025 confirmed these results, indicating an actual energy demand of approximately 1771 kWh/year. Domestic hot water (DHW) preparation accounted for the largest share of energy consumption. Despite its dependence on grid electricity, the building has the infrastructure to enable future photovoltaic (PV) installation, offering further potential for emissions reduction. The results confirm that Total Performance strategies are not only compliant with applicable standards, but also economically and environmentally viable. They represent a scalable model for sustainable residential construction, in line with the European Union’s (EU’s) decarbonization policy and the goals of the European Green Deal. Full article

Globally, construction is among the leading sectors causing carbon emissions. Sustainable practices have become the focus, which aligns with the nation’s commitments to the Paris Agreement by targeting a 30% reduction in emissions from the 2005 levels by 2030. However, evaluation for sustainability is critical, and the Green Star certification provides assurance. Building information modelling has emerged as a transformative technology, integrating environmental sustainability into building design and construction. This study explores the use of BIM to enhance green building outcomes, focusing on optimising stakeholder engagement, energy efficiency, waste control, and environmentally sustainable design. This study employed a case study of an educational building, illustrating how BIM frameworks support Green Star certifications by streamlining design analysis, enhancing project value, and improving compliance with sustainability metrics. Findings highlight BIM’s role in advancing low-carbon, energy-efficient building designs while fostering collaboration across disciplines. This research investigates the foundational approach required to establish a framework for implementing the Green Star certification in non-residential, environmentally sustainable designs. Further, this study underscores the importance of integrating BIM in achieving Green Star benchmarks and provides a roadmap for leveraging digital modelling to meet global sustainability goals. Recommendations include expanding BIM capabilities to support broader environmental assessments and operational efficiencies. Full article

The impacts of renovation actions on pre- and post-retrofitting building performances are complex to analyse, particularly small and potentially self-actuated actions, such as adding insulation layers to a cold roof slab or changing doors. These interventions are widespread in small residential houses and cases where the owners are the residents. However, a large research gap currently remains regarding the impact of sustainable solutions on building performance. This study aims to address this issue by proposing a methodology based on commercial cloud monitoring solutions and middleware development that analyses and reports on the impact of such solutions to end users, allowing for an analysis of real variations in air temperature levels. The methodology is applied to two single/double-family residential houses, acting as demo cases for verification, across a multi-year time horizon. In both cases, measurements were conducted before and after typical limited renovation actions. Alongside the proposed methodology, descriptions of the smart solutions’ requirements are provided. The results mainly focus on temperature variations. Finally, the impact of the solutions on energy consumption was analysed for one of the buildings, and feedback was briefly provided by the users. Full article

The Retabit platform is a data-driven tool designed to bridge the gap between building rehabilitation and urban regeneration by integrating energy, economic, and social dimensions into a single framework. Leveraging multiple public data sources, the platform provides actionable insights to local and national authorities, public housing agencies, urban planners, energy service providers, and research institutions, helping to align renovation initiatives with broader urban transformation goals and climate action objectives. The platform consists of two main components: Analyse, for examining building conditions through multidimensional indicators, and Plan, for designing and simulating renovation projects. Retabit contributes to more transparent and informed decision-making, encourages collaboration across sectors, and addresses long-term sustainability by incorporating participatory planning and impact evaluation. Its scalable structure makes it applicable across diverse geographic areas, policy contexts, and domains linked to sustainable urban development. Full article

This study investigated the integration of advanced Atmospheric Water Generators (AWGs) within the design process of building energy systems, focusing on the water–energy nexus in the context of a real-life hospital building. It is based on a simulation approach, recognised as a viable means to analyse and enhance AWG potentialities. However, the current state of research does not address the issue of AWG integration within building plant systems. This study contributes to fill such a research gap by building upon an authors’ previous work and proposing an enhanced methodology. The methodology describes how to incorporate a multipurpose AWG system into the energy simulation environment of DesignBuilder (DB), version 7.0.0116, through its coupling with AWGSim, version 1.20d, a simulation tool specifically developed for atmospheric water generators. The chosen case study is a wing of the Mondino Hospital in Pavia, Italy, selected for its complex geometry and HVAC requirements. By integrating AWG outputs—covering water production, heating, and cooling—into DB, this study compared two configurations: the existing HVAC system and an enhanced version that includes the AWG as plant support. The simulation results demonstrated a 16.3% reduction in primary energy consumption (from 231.3 MWh to 193.6 MWh), with the elimination of methane consumption and additional benefits in water production (257 m³). This water can be employed for photovoltaic panel cleaning, further reducing the primary energy consumption to 101.9 MWh (55.9% less than the existing plant), and for human consumption or other technical needs. Moreover, this study highlights the potential of using AWG technology to supply purified water, which can be a pivotal solution for hospitals located in areas affected by water crises. This research contributes to the atmospheric water field by addressing the important issue of simulating AWG systems within building energy design tools, enabling informed decisions regarding water–energy integration at the project stage and supporting a more resilient and sustainable approach to building infrastructure. Full article

Nearly zero-energy buildings (nZEBs) are central to global carbon reduction strategies, and Taiwan is actively promoting their adoption through building energy performance labeling, particularly in the retrofit of existing buildings. Under Taiwan’s nZEB framework, qualification requires both an A⁺ energy performance label and over 50% energy savings from retrofit technologies. This study proposes an integrated assessment framework for retrofitting small- to medium-sized office buildings into nZEBs, incorporating diagnostics, technical evaluation, policy alignment, and resource integration. A case study of a bank branch in Kaohsiung involved on-site energy monitoring and EnergyPlus V22.2 simulations to calibrate and assess the retrofit impacts. Lighting improvements and two HVAC scenarios—upgrading the existing fan coil unit (FCU) system and adopting a completely new variable refrigerant flow (VRF) system—were evaluated. The FCU and VRF scenarios reduced the energy use intensity from 141.3 to 82.9 and 72.9 kWh/m²·yr, respectively. Combined with rooftop photovoltaics and green power procurement, both scenarios met Taiwan’s nZEB criteria. The proposed framework demonstrates practical and scalable strategies for decarbonizing existing office buildings, supporting Taiwan’s 2050 net-zero target. Full article

This study investigates the deployment of VERIFY, a dynamic life cycle assessment (LCA) and life cycle costing (LCC) tool, tailored to evaluate the energy and environmental performance of building renovation strategies. The tool was applied to three diverse building renovation projects across Europe, offering insights into how life cycle-based tools can enhance decision-making by integrating operational data and modeling of energy systems. The paper highlights how VERIFY captures both embodied and operational impacts—addressing limitations of conventional energy assessments—and aligns with EU frameworks such as Level(s). Key findings from the case studies in Italy, Spain, and the Netherlands demonstrate how LCA/LCC-based approaches can support energy efficiency objectives and guide sustainability-aligned renovation investments. Across the three case studies, the tool demonstrated up to 51% reduction in primary energy demand, 66% decrease in life cycle greenhouse gas emissions, and 51% reduction in life cycle costs. These outcomes provide researchers with a validated dynamic LCA/LCC framework and offer practitioners a replicable methodology for planning and evaluating sustainability-driven renovations. Despite their advantages, the effective use of LCA tools in energy renovation faces challenges, including limited data availability, regulatory fragmentation, and methodological complexity. The paper concludes that advanced tools such as VERIFY, when harmonized with evolving EU energy performance and sustainability standards, can strengthen the evidence base for deep energy renovation and carbon reduction in the building sector. Full article

Building energy prediction faces challenges such as data scarcity while Transfer Learning (TL) demonstrates significant potential by leveraging source building energy data to enhance target building energy prediction. However, the accuracy of TL heavily relies on selecting appropriate source buildings as the source data. This study proposes a novel, easy-to-understand, statistics-based visualization method that combines the Euclidean distance and Pearson correlation coefficient for selecting source buildings in TL for target building electricity prediction. Long Short-Term Memory, the Gated Recurrent Unit, and the Convolutional Neural Network were applied to verify the appropriateness of the source domain buildings. The results showed the source building, selected via the method proposed by this research, could reduce 65% of computational costs, while the RMSE was approximately 6.5 kWh, and the R² was around 0.92. The method proposed in this study is well suited for scenes requiring rapid response times and exhibiting low tolerance for prediction errors. Full article