Search Results (446)

The increasing deployment of decentralized renewable energy systems requires sustainable, affordable, and high-energy-density storage technologies. While thermal energy storage using phase change materials (PCMs) represents a promising solution, its widespread adoption remains limited by the low thermal conductivity of most PCMs, which restricts (dis)charge power. This work demonstrates that high discharge powers can be achieved through optimized heat-exchanger design without enhancing the intrinsic thermal conductivity of the PCM. After sizing simulations for individual homes, a thermal storage demonstrator integrating water heat exchangers immersed in two PCM reservoirs for domestic hot water and space heating was designed and experimentally investigated. The prototype achieved discharge powers exceeding 80 kW, sustaining 65 kW once transit water had fully cleared the tank, in a compact PCM heat exchanger volume of 0.79 m³, despite the low PCM thermal conductivity of only 0.16 W·m⁻¹K⁻¹. This performance is enabled by a heat-exchanger design providing 203 m² of heat-transfer area while limiting the maximum PCM-to-fin distance to about 1.5 mm. Thermosiphon-driven natural convection was also observed during melting and may further enhance heat transfer. These results demonstrate that heat-exchanger geometry, rather than enhanced PCM conductivity, is the key design parameter for achieving compact, high-power PCM thermal energy storage. Full article

The solar–air source heat pump (S-ASHP) system is used to prepare domestic hot water and is an important form of hot water preparation in many colleges and universities in China. However, the traditional design specifications and operation control strategies can cause excessive design capacity for the hot water system and energy waste. To address these issues, in this study, we integrate the S-ASHP hot water system with predictive modeling of user demand, proposing two distinct control strategies for the hot water supply system. Scheme I: The traditional hot water demand specification is used for design, and the feedback control strategy of the end hot water demand is set according to a fixed mode. Scheme II: A feedforward–feedback combined control strategy based on the ANN-LSTM-STA model is used to predict water consumption and set the end hot water demand. Compared with Scheme I, Scheme II shows significant advantages in heat supply, total energy consumption, and coefficient of performance (COP). The heat supply of the solar collector (SC) supply system is increased by 9.47%, the heat supply of the ASHP supply system is significantly reduced by 57.52%, the running time is reduced by 33.45%, the pump’s energy usage decreases by 16.65%, and the overall system energy consumption drops by 43.85%. Additionally, the coefficient of performance (COP) improves by 6.42%, and the coefficient of performance of the system (COPsys) sees a significant increase of 18.39%. Full article

Modeling an artificial neural network to predict the behavior of a heating and domestic hot water system in a residential building is the basis of this report. The heating system includes three types of energy sources: biofuel, solar, and electricity. During transitional seasons, such as spring and autumn, it is possible to use all three sources periodically or simultaneously, which leads to increased consumption and inefficiency in the system. In order to study the dynamics of the process and optimize the control, a monitoring system based on Raspberry Pi Pico W was developed. Data on the operating parameters of the boiler, tank, and radiator is transmitted in real-time to the ThingSpeak cloud platform, using the free access option that requires only registration. Due to the reinforced concrete structure of the building, the local Wi-Fi connection drops at times, so an additional router was added. Although individual values from the data are missing, they can be used to obtain graphs of the transient process. The data received in the platform does not arrive evenly due to the time required for transmission. The artificial neural network was created in MATLAB (v2025, MathWorks, Natick, MA, USA) and uses the raw data to predict changes in the processes. The missing fragments of the data have no impact, and a good match of the actual values with the predicted values was obtained for the tank and radiator, while for the boiler, the match was satisfactory. Full article

The construction sector is a complex industry whose growth and development are closely associated with overall economic expansion and the circular economy. Within this sector, Building Energy Simulation (BES) is widely employed to evaluate and compare the energy performance of proposed office buildings under both baseline conditions and with alternative heating, ventilation, and air-conditioning (HVAC) and domestic hot water (DHW) system configurations. The primary objective of this research was to conduct an energy performance assessment of administrative buildings located in Bratislava, Slovakia. A progressive methodology based on dynamic heat transfer simulation algorithms was applied to evaluate five alternative scenarios (C1–C5). Building performance and heat flow behavior were modeled and analyzed using DesignBuilder software (Version 7). The simulation results revealed that Scenario C5 represents the most effective solution for both administrative building A and administrative building B. From an economic standpoint, Scenario C5 also achieved the lowest energy costs when the DD3 electricity tariff was applied. The DD3 tariff is a dual-rate electricity pricing scheme intended for consumers with higher levels of electricity consumption during off-peak (low-tariff) periods. The findings indicate that a high level of energy sustainability in office buildings can be achieved through the effective implementation of optimized HVAC and DHW systems. Moreover, the integration of energy-efficiency measures contributes to enhanced economic performance by reducing overall energy consumption and associated operating costs. Full article

This article presents a technical and economic analysis of a photovoltaic system operating in conjunction with a heat pump in a single-family home. The aim of this study was to compare the cost-effectiveness of two prosumer billing systems currently in use in Poland, net metering and net billing, implemented in accordance with the provisions of the Renewable Energy Sources (RES) Act and the Energy Law and to assess the effectiveness of a proprietary algorithm for managing surplus electricity produced by the photovoltaic system. The energy performance of the facility was determined using ArCADia Termo 11.1 software, while energy and economic calculations were performed using Microsoft Excel 365 and a developed heat pump control algorithm. The algorithm is based on an analysis of the building’s energy balance with a 15 min resolution and utilizes data on outdoor temperature, energy production from the PV system, building heat loss, heat pump operating parameters, and energy self-consumption. Its goal was to maximize the use of energy produced for the building’s own needs by appropriately controlling the heat pump and storing surplus energy as heat stored in domestic hot-water tanks. The annual electricity consumption of the analyzed building was 6902.18 kWh, of which 3724.13 kWh was for heating and domestic hot water provided by the heat pump. The algorithm reduced grid energy consumption by approximately 900 kWh per year and achieved a self-consumption level of 12.73 (%). Full article

Urban Building Energy Modeling (UBEM) offers a scalable, physics-based method to simulate energy demand at the district level, enabling data-driven district energy demand planning and optimization. However, translating UBEM into a reliable, openly replicable workflow remains a significant methodological gap. In particular, limited attention has been devoted to the development of transparent and transferable UBEM workflows capable of systematically quantifying the impact of modeling assumptions on district-scale thermal demand accuracy. This paper presents and validates a five-step UBEM pipeline integrating freely available geospatial data from OpenStreetMap (OSM), archetype-based building characterization, multi-scenario EnergyPlus simulation via the Urban Modeling Interface (UMI) within a structured validation framework. To improve interpretability and reproducibility, a dedicated three-scenario simulation protocol was developed to isolate and quantify the influence of geometry simplifications, archetype assumptions, and weather data fidelity on model accuracy. The workflow is demonstrated through application to a real district heating system (DHS) in northern Italy, encompassing UBEM results validated against monitored consumption data at different temporal resolutions. The refined model achieves a district-scale annual magnitude error of 1.30% between real and simulated data. Persistent limitations in domestic hot water representation and peak load estimation are identified as priorities for future development. Full article

The Smart Readiness Indicator (SRI) provides a European framework for assessing the capacity of buildings to optimise operation, respond to occupants and interact with energy grids. Its current catalogue covers nine domains: heating, cooling, domestic hot water, ventilation, lighting, dynamic envelope, electricity, electric vehicle charging, and monitoring and control. This Perspective argues that this boundary is too narrow for complex buildings, where services such as lifts, security, fire safety, swimming pools, irrigation, outdoor lighting, kitchens, laundries, refrigeration, laboratories, and information and communication technology (ICT) rooms may significantly affect energy use, water use, safety, resilience, maintenance and user experience. The paper proposes five additional service families for SRI 2.0: mobility and accessibility; safety and security; water and outdoor environmental services; outdoor and site infrastructure; and special energy-intensive and facility services. These should be introduced as optional, building-type-specific modules assessed through familiar SRI functionality levels. This would make the SRI more realistic, actionable and relevant. Full article

Cold-climate dwellings can face coincident electricity and domestic hot-water shortfalls in winter, when solar availability is at its lowest. This study evaluates an integrated residential system for Aomori, Japan, combining photovoltaics, evacuated-tube solar water heating, and battery storage with electrolysis, compressed-hydrogen storage, and a PEM fuel cell operated in combined-heat-and-power mode. Building on a screening-level annual-balance analysis, a coupled annual TRNSYS simulation with a 0.125 h time step resolved battery dispatch, electrolyzer part-load operation, hydrogen compression and finite storage, seasonal fuel-cell operation, and heat recovery. The results show that the principal value of seasonal hydrogen lies in improving winter supply adequacy, dispatchability, and heat recovery rather than annual conversion efficiency. Fuel-cell heat recovery increased the number of days satisfying the hot-water screening indicator—a daily mean tank temperature of at least 43 °C—from 221 to 332. A reserve-aware criterion identified a 225 W electrolyzer operating-power cap as the positive-reserve case; 205 W was near-cyclic with a negligible margin, whereas the original 475 W cap was substantially oversized. The hydrogen pathway remained markedly less efficient than direct photovoltaic and solar-thermal use, and the estimated storage hardware’s lower bound substantially exceeded the break-even capital ceiling supported by the annual operating value. Seasonal hydrogen can therefore strengthen winter energy adequacy and heat recovery but is not yet cost-effective at the single-dwelling scale under the investigated conditions. Full article

Hin Dad hot spring is a prominent natural geothermal facility in Thailand, widely frequented by domestic and international tourists seeking hydrotherapy. According to UNSCEAR, radon (²²²Rn), thoron (²²⁰Rn), and their short-lived decay products represent the primary sources of natural ionizing radiation exposure to humans. Geothermal waters inherently carry elevated levels of these radionuclides, potentially exposing visitors and facility staff to radiological hazards. This study evaluated ²²²Rn concentrations in water samples alongside ambient air concentrations of ²²²Rn, ²²⁰Rn, and their respective progeny within the Hin Dad hot spring area. The average ²²²Rn levels in water across six sampling sites ranged from 3 ± 1 to 24 ± 1 Bq L⁻¹, remaining well below the World Health Organization (WHO) screening level for ²²²Rn in water (100 Bq L⁻¹). Ambient air monitoring was conducted using both active and passive techniques. Active measurements via an AlphaGuard detector at three designated points yielded average ²²²Rn and ²²⁰Rn concentrations ranging from 12 to 41 Bq m⁻³ and 23 to 38 Bq m⁻³, respectively. As expected from the partitioning behavior of radon between water and air, atmospheric concentrations were markedly lower than the corresponding aqueous ²²²Rn concentrations. Furthermore, long-term passive monitoring over 103 days using RADUET detectors revealed maximum time-integrated average concentrations of 66 ± 1 Bq m⁻³ for ²²²Rn and 47 ± 4 Bq m⁻³ for ²²⁰Rn. All atmospheric concentrations complied with the reference levels established by both the WHO and the International Commission on Radiological Protection (ICRP) (100–300 Bq m⁻³); as this range is defined for indoor environments, it is applied here only as a conservative benchmark for the open and semi-outdoor monitoring stations. Regarding progeny exposure, the maximum Equilibrium Equivalent ²²²Rn Concentration (EERC) and Equilibrium Equivalent ²²⁰Rn Concentration (EETC) were determined to be 21.0 ± 2.5 Bq m⁻³ and 2.7 ± 0.3 Bq m⁻³, respectively. The measured concentrations and estimated doses indicate a low radiological concern under the conditions investigated, though the assessment is based on two seasonal sampling rounds and does not include personal dosimetry or wet-season monitoring. Full article

Rural houses in cold regions of China usually have high energy demands, particularly for space heating and domestic hot water. Passive design can reduce building energy demand, but additional renewable energy systems are still needed to improve on-site energy supply. This study evaluates the performance and limitations of photovoltaic (PV) and solar water heating (SWH) systems in a passive-designed rural house in Xi’an, China. Hourly simulations were conducted for PV-only and PV–battery configurations with different south-facing roof coverage ratios and battery capacities, together with an evacuated-tube SWH system. The results show that PV electricity supply was limited by the mismatch between household electricity demand and PV generation. Household demand mainly occurred in the morning and evening, whereas PV generation was concentrated around noon. The 13 m² PV case achieved approximately 11% electricity supply capacity with a utilization ratio of 62%, while increasing the PV area to 50 m² raised the supply capacity to only 15% and reduced the utilization ratio to 23%. With battery storage, the largest PV–battery configuration supplied 48% of annual household electricity demand, while the overall electricity utilization ratio was 73%, indicating a trade-off between household electricity self-supply and system utilization. The SWH system showed better applicability for domestic hot water supply, with an annual average hot water supply capacity of 60.2% and an average device efficiency of 43.5%, but its winter performance remained weak. These results indicate that PV and SWH are useful but insufficient solar energy strategies for passive-designed rural houses. PV is mainly constrained by daily time mismatch, while SWH is mainly constrained by seasonal climate variation. Full article

Improving the operational energy and carbon performance of hotel buildings is an important environmental dimension of sustainable building design. This study develops a reproducible EnergyPlus-based framework that combines parametric simulation, interpretable sensitivity analysis, machine learning surrogates, and carrier-resolved operational carbon accounting for Beijing hotel buildings. From 20,000 Latin hypercube candidates, input-side physical and functional screening retained 4640 successful EnergyPlus simulations. The simulated EUI mean was 140.6 kWh/(m²·a), 14.3% above the published Beijing hotel mean; surrogate performance is therefore interpreted as fidelity to the simulator rather than direct measured-building prediction. SRC with bootstrap uncertainty and a SHAP cross-check identified the main domestic-hot-water, building-form, and HVAC drivers. Of 17 models, Poly3-RidgeCV achieved the highest held-out fidelity (R² = 0.9976; RMSE = 1.72 kWh/(m²·a)). Baseline OCEI averaged 48.20 kgCO₂e/(m²·a); EUI and OCEI were strongly correlated (r = 0.954) but not interchangeable, with 71.8% overlap between the top-10% low-EUI and top-10% low-OCEI cases. Emission-factor scenarios showed robust but non-static energy-carbon coupling. The framework supports early-stage comparison of energy-efficient alternatives with comparatively lower operational carbon emissions within the stated accounting boundary, contributing to sustainable hotel design without constituting a whole-life or measured-building sustainability assessment. Full article

Accelerating the renovation of existing residential buildings is essential for achieving European climate targets, but aggregate renovation rates do not show whether interventions are sufficiently deep, well targeted, or cost-effective. This paper develops a transparent scenario framework for prioritising renovation strategies at local building stock scale. The workflow combines a literature-based screening of renovation indicators and implementation conditions, semi-structured expert interviews used for qualitative triangulation, and a typology-based bottom-up model of the South Tyrolean residential stock. The stock model uses census and provincial floor-area data, representative space heating and domestic hot water demand values from SINFONIA and previous South Tyrolean studies, and static end-state renovation assumptions. Three scenarios are compared: deep renovation of priority high-demand clusters, medium renovation of the same clusters, and light renovation of the whole stock. The baseline model estimates residential heating and domestic hot water demand at approximately 1990 GWh/year. The selected priority clusters account for about 56% of floor area and nearly 59% of baseline demand. Under the central assumptions, targeted deep renovation would reduce demand by approximately 704 GWh/year (35%), targeted medium renovation by 352 GWh/year (18%), and whole-stock light renovation by 299 GWh/year (15%). Indicative CO₂ reductions are reported separately and are proportional to the same final energy reduction assumptions because carrier switching is not modelled. A static cost-effectiveness screening using Italy-level energy-related renovation cost data is reported as an order-of-magnitude range rather than a local investment forecast. The results show that renovation depth and target selection should be considered jointly, and that the framework is transferable where typological stock data and representative energy demand values are available. Full article

The sizing of rooftop solar energy systems is commonly based on the most visible load or on generic end-use allocations, leading to an inadequate distribution of the limited rooftop area between heat and electricity. This study formalizes the energy audit within a three-level deterministic framework that selects and sizes solar technologies by energy vector: demand is first decomposed by vector; the technology for the thermal vector is then selected through a levelized cost of heat selection ratio $\psi$, while the photovoltaic system of the electrical vector is sized for self-consumption; and the rooftop area is finally allocated among vectors according to marginal value per unit area. In a 75-bed university residence in Cienfuegos, Cuba, air conditioning is the dominant energy end-use in terms of installed power (accounting for $77\%$ of the connected load), whereas the thermal vector dominates annual energy consumption (domestic hot water: 127,440 versus 76,818 kWh/year for electricity; thermal-to-electric ratio $1.66$). Solar thermal technology has been selected for the thermal vector ($0.018$ versus $0.088$ USD/kWh_th; $\psi =0.21$, a robust value according to the sensitivity analysis), and the marginal value (≈111 versus ≈32 USD/(m²·year)) allocates 104 m² to solar thermal collectors and 134 m² to photovoltaic energy, thereby reversing the original design that prioritized photovoltaic energy. The resulting portfolio achieves an annual solar fraction close to $100\%$ in both vectors on an energy balance basis, avoids $86.5$ t of operational CO₂ emissions per year, and combines a simple payback of $1.1$ years (solar thermal) with a net present value of 55,327 USD and an internal rate of return of $28\%$ (photovoltaics). The sizing decision is shown to be robust to the choice of statistical design criterion (median, mean, P90, maximum), and none of the three framework decisions is reversed under $\pm 30\%$ parameter variations. By replacing the subjective weightings of multi-criteria methods with observable economic criteria, the framework provides a replicable and auditable design protocol. Full article

Green remodeling projects for public buildings in South Korea aim to improve the energy performance of aging facilities, with a policy target of achieving at least 30% energy savings. Because the 30% saving rate functions as a key policy benchmark, it is necessary to identify why some projects achieve higher savings while others remain below the target. This requires a comparative analysis of energy-saving levels in relation to baseline energy-use composition and retrofit measure applications. This study analyzes the 1954 preliminary investigation and ECO2-OD-based assessment cases of public building green remodeling projects to examine energy-saving levels, baseline energy-use composition, end-use contributions, and retrofit measure applications. Pre- and post-retrofit primary energy demand for heating, cooling, domestic hot water, and lighting were used to calculate energy-saving rates. Based on the 30% policy target, the cases were classified into Low-saving, Target-achieving, High-saving, and Very-high-saving levels. The average energy-saving rate was 36.02%, but 39.61% of cases remained below the 30% target. Higher-saving groups showed greater baseline heating energy shares, increasing from 53.38% in the Low-saving group to 66.18% in the Very-high-saving group, suggesting an association between pre-retrofit energy-use structure and predicted retrofit potential under the ECO2-OD assessment framework. Heating was also the dominant contributor to total savings, with its contribution rising from 17.07 to 44.94 percentage points. Higher-saving cases tended to involve more comprehensive retrofit packages combining envelope, system, and lighting improvements. These findings suggest that energy-saving targets and retrofit strategies should consider baseline end-use energy composition and establish differentiated saving targets according to building characteristics, rather than relying only on uniform policy targets and average project performance. Full article

Hot-water bottles are widely used domestic heat sources, but seam and neck failures can cause scald injuries, and quantitative evidence supporting replacement guidance remains limited. This study compared the tensile behaviour of unused, dry-stored hot-water bottles manufactured in 2022 and 2024, focusing on vulcanised rubber and plasticised PVC constructions. ISO 37 Type 1 dumb-bell specimens were excised from body panels and seam regions and tested in uniaxial tension at 23 ± 2 °C and 50 ± 5% RH using a grip-separation rate of 500 mm min⁻¹. Stress–strain curves were analysed to determine maximum stress, failure strain, toughness and tangent modulus, with seam and face specimens compared within each material year cohort. PVC specimens were consistently stiffer and stronger than rubber specimens but failed at lower strain. Manufacturing year-associated differences were material-dependent: PVC-2022 generally showed higher maximum stress and toughness than PVC-2024, whereas Rubber-2022 underperformed Rubber-2024 at large strain. Seam–face ordering also depended on material and year, with PVC faces outperforming seams, while rubber showed cohort-specific behaviour. These findings indicate that hot-water bottle durability is influenced by both material system and joint region, supporting the need to consider seam performance alongside bulk material properties in safety assessment and replacement guidance. Full article