Search Results (123)

Modular and prefabricated buildings are advantageous in terms of construction, transport, energy efficiency, fixed costs, and the use of environmentally friendly materials. Our research aims to analyze, evaluate, and optimize a lightweight perimeter structure with an integrated active thermal protection (ATP). We have developed a mathematical–physical model of a wall fragment, in which we have analyzed several variants through a parametric study. ATP in the energy function of a thermal barrier (TB) represents a high potential for energy savings. Cold tap water (an average temperature of +6 °C, thermal untreated) in the ATP layer of the investigated building structure increases its thermal resistance by up to 27.24%. The TB’s mean temperature can be thermally adjusted to a level comparable to the heated space (e.g., +20 °C). For the fragment under consideration, optimizing the axial distance between the pipes (in the ATP layer) and the insulation thickness (using computer simulation) reveals that a pipe distance of 150 mm and an insulation thickness of 100 mm are the most suitable. ATP has significant potential in the design of sustainable, resilient, and climate-adaptive buildings, thereby meeting the UN SDGs, in particular the Sustainable Development Goal 7 ‘Affordable and Clean Energy’ and the Goal 13 ‘Climate Action’. Full article

Efficient scheduling of Energy Storage Systems (ESS) within microgrids has emerged as a critical issue to ensure energy cost reduction, peak shaving, and battery health management. For ESS scheduling, both single-agent and multi-agent deep reinforcement learning (DRL) approaches have been explored. However, the former has suffered from scalability to include multiple objectives while the latter lacks comprehensive consideration of diverse user objectives. To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. The proposed model employs two independent agents: one is to minimize electricity costs and the other does charge/discharge switching frequency to account for battery degradation. The candidate actions generated by the agents are evaluated through Pareto dominance, and the final action is selected via scalarization-reflecting operator-defined preferences. The simulation experiments were conducted using real industrial building load and photovoltaic (PV) generation data under realistic South Korean electricity tariff structures. The comparative evaluations against baseline DRL algorithms (TD3, SAC, PPO) demonstrate that the proposed MAPPO method significantly reduces electricity costs while minimizing battery-switching events. Furthermore, the results highlight that the proposed method achieves a balanced improvement in both economic efficiency and battery longevity, making it highly applicable to real-world dynamic microgrid environments. Specifically, the proposed MAPPO-based scheduling achieved a total electricity cost reduction of 14.68% compared to the No-ESS case and achieved 3.56% greater cost savings than other baseline reinforcement learning algorithms. Full article

The construction industry is a major contributor to global CO₂ emissions due to high energy consumption in buildings and the production of carbon-intensive materials. Although Big Data is recognized as a transformative tool for improving sustainability by optimizing energy use, resource efficiency, and decision-making, its adoption in construction remains limited. This study aims to identify and analyze the technical, economic, and organizational factors influencing Big Data adoption for sustainability and climate neutrality in Swedish construction companies. A quantitative survey was conducted among 150 industry professionals, and the data were analyzed using descriptive statistics, Spearman correlations, ANOVA, chi-squared (χ²) tests, and principal component analysis (PCA), guided by the diffusion of innovations (DOI) theory. The results indicate that the respondents broadly acknowledge benefits such as energy savings, cost reductions, and improved decision support. The PCA revealed two key dimensions—one capturing technical/environmental benefits, the other economic/regulatory benefits—while barriers included standardization issues, limited digital skills, and investment uncertainties persist. The findings suggest that overcoming these barriers is essential for accelerating a strategic and climate-aligned digital transition in construction, offering actionable insights for policymakers and industry leaders. Full article

Educational buildings are recognized as one of the largest consumers of electrical energy. Inadequate lighting can also have negative physical and psychological effects on these environments. Therefore, optimal lighting design that meets electrical energy needs while providing visual comfort is essential. Reducing glare, primarily caused by artificial lighting in educational environments, is particularly important. Glare can lead to discomfort and eye fatigue, adversely affecting learning performance. To measure and assess this phenomenon, the “Unified Glare Rating (UGR)” metric is employed, which helps designers accurately evaluate the level of glare caused by lighting. This paper examines the parameters of height and surface reflectance as variable factors to achieve an optimal design that reduces lamp demand and minimizes glare, using a three-phase methodology: (1) using Dialux software, two primary scenarios—varying heights (2.5 and 3 m) and reflectance coefficients (ceiling, walls, floor)—were examined, (2) across 100 simulations followed by correlation and regression analyses to assess the effect of each reflectance coefficient (ceiling, walls, floor) on illuminance and the UGR, and (3) energy performance evaluation. Results demonstrate trade-offs: reducing lamps from 15 to 9 lowered energy use by 40% but increased UGR from 13 to 18 (approaching the discomfort threshold of 19), while 12 lamps achieved a balance—20% energy savings, a UGR of 14, and uniformity of 0.67. Surface reflectance emerged as critical, with high-reflectance ceilings (≥85%) and walls (≥80%) contributing 50.9% and 32% to illuminance variance, respectively. This study concludes that multi-parameter optimization—integrating height, lamp quantity, and reflectance—is essential for energy-efficient classroom lighting with acceptable glare levels, providing actionable guidelines for urban educational environments constrained by artificial lighting dependency. Full article

This paper presents the first results of a broader study aimed at considering atmospheric water generation as a viable option within sustainable building design strategies. In particular, the focus is on integrated systems in which atmospheric water generator (AWG) machines, in addition to producing water, support HVAC systems. The research focuses on the combined use of two different simulation tools: a commercial tool designed to study the energy balance of buildings and a custom-developed software for AWG modelling. This is the first step of a more complex procedure of software integration that is aimed to provide designers with a method to implement AWGs in the design process of buildings, both residential or industrial. This preliminary procedure is applied to a case study concerning the link between an advanced integrated AWG and a building housing inverters and transformers that belong to a photovoltaic field. The scope of the integration consists in enhancing the energy sustainability of atmospheric water intended for hydrogen production and panel washing by means of the dry and cold air flux that comes from the cycle of vapour condensation. The results highlight the potentialities of the integrated design, which includes AWGs, to enhance the final efficiency of sustainable housing. In particular, the joint action of the simulation tools used in this study provides insights about the possibility to reduce the size of traditional chiller that serve the building by an order of magnitude, and to achieve an energy saving of 29.8 MWh a year. Full article

The energy consumption requirement of high-rise buildings necessitates effective innovations in architectural designs. The aim is to revolutionise high-rise buildings’ thermal features and energy efficiency. This paper combines quantitative analyses through improved thermal simulations and qualitative information from surveys of stakeholders, including architects, engineers, and urban planners. Key performance indicators such as U-values, R-values, HVAC efficiency, Solar Heat Gain Coefficient (SHGC), and Energy Use Intensity (EUI) are examined in detail to assess the thermal and energy performance of contemporary façade systems. Energy-efficient building design is paramount in this time of unprecedented urban development and escalating global temperatures. However, a gap exists in understanding how these practices can be adapted and integrated effectively into modern architecture. The findings show that high-rises with optimized pattern curtain wall façades reveal considerable savings in energy usage, particularly in cooling loads, which enhances indoor thermal comfort and reduces environmental effects. Actionable recommendations are provided for architects, urbanists, and policymakers, including the designs of region-specific façade constructions, their connection with renewable energy, and compliance with high energy performance standards. All these strategies help to improve the operational efficiency, environmental sustainability, and stability of built environments in growing, developed urban areas. Full article

Electric wheel loaders (EWLs) have emerged as a pivotal innovation in the 2020s, representing a transformative shift toward high-efficiency, low-emission construction machinery. Despite their growing technological and environmental significance, a systematic synthesis of advancements in EWL design, energy optimization, and intelligent control remains absent in the literature. To bridge this gap, this review critically evaluates over 140 studies for comparative analysis. Building on the authors’ ongoing research, this paper categorizes EWL architectures and examines breakthroughs in hydraulic systems, drivetrain configurations, and bucket dynamics optimization. A dedicated focus is placed on energy-saving strategies, including advancements in battery technology, fast-charging infrastructure, intelligent torque distribution, and data-driven modeling of shoveling and operational resistance. The analysis reveals that integrating optimal control strategies with machine learning algorithms—such as model predictive control (MPC)—is a critical pathway to achieving energy-efficient and assisted driving in next-generation EWLs. Furthermore, this review advocates for the adoption of distributed electro-hydraulic drive systems to minimize hydraulic losses and enable efficient energy recovery during actuator control. By synthesizing these insights, this work not only highlights current technological frontiers but also proposes actionable research directions to accelerate the commercialization of intelligent, sustainable EWLs. Full article

This study addresses the critical challenge of performing a detailed calculation of energy savings in buildings by implementing suitable actions aiming at reducing greenhouse gas emissions. Given the high energy consumption of buildings’ space heating systems, optimizing their performance is crucial for reducing their overall primary energy demand. Unfortunately, the calculations of such savings are often based on extremely simplified methods, neglecting the dynamics of the emitters installed inside the buildings. These approximations may lead to relevant errors in the estimation of the possible energy savings. In this framework, the present study presents a novel 0-dimensional capacitive model of a radiator, the most common emitter used in residential buildings. The final scope of this paper is to integrate such a novel model within the TRNSYS 18simulation environment, performing a 1-year simulation of the overall building-space heating system. The radiator model is developed in MATLAB 2024b and it carefully considers the impact of surface area, inlet temperature, and flow rate on the radiator performance. Moreover, the dynamic heat transfer rate of the capacitive radiator is compared with the one returned by the built-in non-capacitive model available in TRNSYS, showing that neglecting the capacitive effect of radiators leads to an incorrect estimation of the heating consumption. During the winter season, with a heating system turned on from 8 a.m. to 4 p.m. and from 6 p.m. to 8 p.m., the thermal energy is underestimated by roughly 20% with the commonly used non-capacitive model. Full article

The prioritization of energy renovations is critical to achieving sustainability goals and addressing socio-economic disparities in building stock. This study proposes a novel hybrid MultiCriteria Decision-Making framework for identifying and prioritizing residential buildings for energy efficiency upgrades. By integrating granular building-level data, such as energy performance and construction year, with socio-economic indicators like energy poverty and municipal income, the framework provides a comprehensive and equitable approach. Using Python for data integration and analysis, the methodology applies weighted factors to calculate the Building Priority Factor and the Municipal Energy Poverty Factor. A prioritization analysis for Slovenia demonstrates significant regional disparities in energy savings potential and renovation priorities, with some regions emerging as high-priority targets due to their aging infrastructure and elevated energy poverty levels. Conversely, densely populated urban regions with larger cities show lower prioritization needs. The proposed framework addresses limitations in existing methods by incorporating socio-economic and spatial data, enabling a dynamic and scalable approach to financial incentives. This approach aligns with the Energy Performance of Buildings Directive, providing actionable insights for national renovation plans. The findings highlight the importance of targeted, regionally tailored interventions to maximize energy savings, reduce inequities, and support sustainable development goals. Full article

Buildings account for a substantial portion of global energy use, with about one-third of total consumption attributed to them, according to IEA statistics, significantly contributing to carbon emissions. Building energy efficiency is crucial for combating climate change and achieving energy savings. Smart buildings, leveraging intelligent control systems, optimize energy use to reduce consumption and emissions. Deep reinforcement learning (DRL) algorithms have recently gained attention for heating, ventilation, and air conditioning (HVAC) control in buildings. This paper reviews current research on DRL-based HVAC management and identifies key issues in existing algorithms. We propose an enhanced intelligent building energy management algorithm based on the Soft Actor–Critic (SAC) framework to address these challenges. Our approach employs the distributed soft policy iteration from the Distributional Soft Actor–Critic (DSAC) algorithm to improve action–state return stability. Specifically, we introduce cumulative returns into the SAC framework and recalculate target values, which reduces the loss function. The proposed HVAC control algorithm achieved 24.2% energy savings compared to the baseline SAC algorithm. This study contributes to the development of more energy-efficient HVAC systems in smart buildings, aiding in the fight against climate change and promoting energy savings. Full article

Dynamic facades allow for effective climate adaptability, representing a new trend in future building envelope design. Present research on dynamic facades often focuses solely on certain aspects of the built environment or relies entirely on simulation outcomes. Meanwhile, the real-time changing nature of dynamic facades poses challenges in accurately simulating these schemes. Therefore, it remains essential to quantify the energy consumption performances of different types of dynamic facades and their influence on the indoor environment comfort in response to ventilation, light, and thermal environment to improve energy savings. This study uses an energy management system to simulate the ability of five dynamic facades—an intelligent ventilated facade, a dynamic exterior shading, a dynamic interior shading, a buffer layer, and phase-change material (PCM) facades—to provide adequate comfort and reduce energy consumption in four climate zones in China. The simulation model of a nearly net-zero energy Solar Decathlon house “Nature Between” was validated with experimental data. Among the five dynamic facades, the energy-saving efficiency of intelligent ventilation was highest, followed by exterior shading. Compared with houses without dynamic facades, the use of the dynamic facades reduced energy consumption (and annual glare time) by 19.87% (90.65%), 22.37% (74.84%), 15.19% (72.09%), and 9.23% (75.53%) in Xiamen, Shanghai, Beijing, and Harbin, respectively. Findings regarding the dynamic facade-driven energy savings and favorable indoor environment comfort provide new and actionable insights into the design and application of dynamic facades in four climate regions in China. Full article

Buildings are responsible for approximately 40% of global energy consumption, putting pressure on the construction industry to mitigate its environmental impact. Therefore, there is an urgent need for innovative solutions to reduce power consumption, particularly in lighting systems. This study’s primary objective was to investigate novel integrated lighting solutions that significantly reduce energy use, as well as to explore their enhancement through Building Information Modelling (BIM) and the Internet of Things (IoT) to improve energy efficiency further and reduce the carbon footprint of buildings. Hence, this literature review examined energy-saving actions, retrofitting practices and interventions across a range of multi-use buildings worldwide, focusing on research from 2019 to 2024. The review was conducted using Scopus and Web of Science databases, with inclusion criteria limited to original research. The objective was to diagnose the goals being undertaken and ultimately validate new actions and contributions to minimise energy consumption. After applying eligibility criteria, 48 studies were included in the review. First, daylight harvesting and retrofitting solutions were examined using the latest technologies and external shading. The review indicates a lack of proper coordination between daylight and electrical lighting, resulting in energy inefficiency. Secondly, it reviews how the integration of BIM facilitates the design process, providing a complete overview of all the building variables, thus improving indoor daylight performance and proper lighting with energy analysis. Lastly, the review addresses the role of the Internet of Things (IoT) in providing real-time data from sensor networks, allowing for continuous monitoring of building conditions. This systematic literature review explores the integration of these fields to address the urgent need for innovative strategies and sustainability in the built environment. Furthermore, it thoroughly analyses the current state of the art, identifying best practices, emerging trends and concrete insight for architects, engineers and researchers. The goal is to promote the widespread adoption of low-carbon systems and encourage collaboration among industry professionals and researchers to advance sustainable building design. Ultimately, a new parametric design framework is proposed, consisting of five iterative phases that cover all design stages. This framework is further enhanced by integrating BIM and IoT, which can be used together to plan, reconfigure, and optimise the building’s performance. Full article

This study demonstrates the benefits of comprehensive school building (SB) energy efficiency (EE) improvements through building envelope renovations, lighting upgrades, and changes to cleaner heat sources. The parametric study in the building energy simulation software was used to check the application of various interventions on the energy consumption of existing SBs while reducing CO₂ emissions with the most profitable return on investment (ROI). The energy savings from window replacements did not correspond with expectations. However, other measures such as the wall, roof insulation, and lighting modernization improved EE by up to 152 kWh/m² and 41 kg/m² CO₂/m² annually. The study also points to a significant trade-off between district heating (which reduces CO₂ but has a slower ROI) and other heating solutions. The results suggest that climate-specific insulation thickness and glazing type needs are required, and optimal insulation strategies are shown to improve EE by 48–56% and CO₂ reductions of 45–56%. Lighting replacement and biogas boiler use were both impactful. The findings support the importance of sustainable practices, which should stimulate educational awareness and environmental responsibility. This research presents actionable insights for EE and sustainable development from within educational facilities. Full article

Dynamic simulations can accurately estimate the thermal demands for space heating and cooling in buildings, as well as the energy and economic performance of specific energy refurbishment actions. This study aims to evaluate the energy and economic savings resulting from the adoption of particular energy measures applied to a cluster of residential condominium buildings, also considering some possible Italian funding policies. To this scope, dynamic simulation models of several buildings with different features in terms of geometry, shape, and thermo-physical properties are considered. The selected buildings are representative of the most common buildings in the city of Naples, Southern Italy. Two scenarios regarding the possible penetration of the refurbishment actions are considered: the “25% scenario”, where 25% of buildings in the Naples municipality adopt the selected measures, and the “100% scenario”, where all buildings adopt such energy refurbishment actions. The results of the simulations, reported over different time periods, compare the economic, energy, and environmental benefits of the specific energy measures. This study evaluates the replacement of conventional natural gas-fired boilers with natural gas-fired condensing boilers, as well as the use of thermal insulation on the external walls of the buildings. The primary energy demand for space heating decreased by 28% when the proposed energy measures were implemented in all buildings of the Naples municipality. Full article

This article aimed to identify actions to improve energy efficiency in households. A household’s energy efficiency is aimed at obtaining the same or more services with lower energy input. The article presents energy consumption in households in Poland according to Statistics Poland and then discusses the results of the survey, where respondents were asked how they improve their energy efficiency. Improving households’ energy efficiency has gained importance due to increased energy prices in recent years. The most common methods of improving energy efficiency in a household include energy-saving devices and LED lighting, thermal modernization of the building, replacement of the heating system, and changing habits. The results were presented using the documentation and comparative methods. The article uses data from Statistics Poland and surveys conducted among 1112 representatives of households in Poland. Full article