Search Results (1,502)

The Hybrid Contra Rotating Propeller is a developing propulsion system that combines a conventional single-shaft propeller with a POD propeller to achieve high energy-saving performance through a Contra Rotating Propeller. In this paper, a new towing tank test method for the Hybrid Contra Rotating Propeller was suggested. By conducting seven patterns of propeller open-water tests and measuring the individual propeller performance and the interaction between the propeller and the POD, the propeller’s mutual interaction can be obtained. Towing tank tests for a study ship were conducted, and the analyzed results are shown. There exists the effect of the wake of the propeller open boat at an unusual (reversed) test layout, which simulates the Hybrid Contra Rotating Propeller, and this effect must be removed for the accurate estimation of the ship’s performance. In conventional towing tank test methods, this effect on the front propeller was obtained and used to correct the performance of the total unit of the Hybrid Contra Rotating Propeller. The presented method allows for the correct removal of the open boat effect on the performance of each propeller and the propeller mutual interaction, resulting in more accurate power estimation. Furthermore, by using the individual performance of two propellers and interaction terms, the presented method enables us to conduct a power estimation at an arbitrary revolution rate of two propellers. Full article

Maritime transport accounts for approximately 3% of global greenhouse gas (GHG) emissions, a figure projected to rise by 17% by 2050 without effective mitigation measures. Achieving zero-emission shipping requires a comprehensive strategy that integrates regulatory frameworks, alternative fuels, and energy-saving technologies. However, existing studies often fail to provide an integrated analysis of regulatory constraints, economic incentives, and technological feasibility. This study bridges this gap by developing an integrated model tailored for international maritime transport, incorporating regulatory constraints, economic incentives, and technological feasibility into a unified framework. The model is developed using a predictive approach to assess decarbonization pathways for global shipping from 2018 to 2035. A multi-criterion decision analysis (MCDA) framework, coupled with techno-economic modeling, evaluates the cost-effectiveness, technology readiness, and adoption potential of alternative fuels, operational strategies, and market-based measures. The results indicate that technical and operational measures alone can reduce emissions by up to 44%, while market-based measures improve the diversity of sustainable fuel adoption. Biofuels, particularly BISVO and BIFAME, emerge as preferred alternatives due to cost-effectiveness, while green hydrogen, ammonia, and biomethanol remain unviable without additional policy support. A strict carbon levy increases transport costs by 46%, whereas flexible compliance mechanisms limit cost increases to 14–25%. The proposed approach provides a robust decision-support framework for policymakers and industry stakeholders, ensuring transparency in evaluating the trade-offs between emissions reductions and economic feasibility, thereby guiding future regulatory strategies. Full article

In China, retrofitting rural dwellings is a crucial step toward enhancing living conditions and lowering energy waste. One of the most important ways to enhance building performance is to retrofit the building envelope. The Qianbei Region’s (Northern Guizhou Province, China) rural dwellings are the subject of this study. It identifies the persistent issue of inadequate thermal comfort in local rural dwellings through indoor thermal environment measurements and questionnaire surveys. Using a parametric modelling tool (Rhino-Grasshopper-Ladybug Tools), multi-objective optimization was performed using a non-dominated sorting genetic algorithm (NSGA-II), with the types of external windows, walls, and roof insulation as optimization variables, and building energy consumption (E), annual thermal discomfort hours (TDT), and life cycle cost increment (ΔLCC) as optimization objectives. After the retrofitting, the building’s energy consumption was reduced from the baseline value of 96.41 kWh/m² to 42.40 kWh/m² (a 56% reduction), and the annual duration of thermal discomfort decreased from 6173 h to 5078 h (a 17.7% decrease). This resulted in a positive economic return, with a cost saving of ΔLCC = −56,329.87 CNY. The research proposes a scientific method for the energy-saving retrofitting of rural dwellings in the Qianbei Region, which also serves as a guide for the optimization of building performance in comparable climate zones. Full article

Digital Twin (DT) technology is emerging as a powerful tool for optimizing energy efficiency and industrial sustainability. By creating virtual replicas of physical systems, DTs enable real-time monitoring, predictive maintenance, and resource optimization, offering new opportunities to meet growing energy demands. Despite its potential, the comprehension of DT technology’s applications, benefits, and challenges remains limited. This systematic review explores the role of Digital Twins in energy efficiency across various industries. A structured literature search was conducted in IEEE Xplore, Elsevier, Springer, MDPI, and Google Scholar, following PRISMA 2020 guidelines. After applying the predefined inclusion criteria, 50 studies were selected for in-depth analysis. The findings highlight that DT implementation can lead to energy savings of up to 30%, reduce operational costs, and improve predictive maintenance strategies. Their impact is particularly notable in smart buildings, manufacturing, and industrial processes, where real-time data analytics contribute to better energy management. However, significant barriers remain, including high implementation costs, data security risks, and the complexity of integrating DTs with existing infrastructures. By synthesizing the current research, this review underscores the transformative potential of Digital Twins while identifying key challenges that need to be addressed for their wider adoption. Future efforts should focus on developing standardized methodologies, reducing implementation costs, and enhancing cybersecurity measures to maximize their benefits in energy efficiency and sustainability. Full article

This research aimed to ascertain the ZIP (constant impedance, constant current, and constant power) coefficients and Conservation of Voltage Reduction factor (CVR_f) for residential appliances as well as for the residential network feeders in Malaysia through measurement and simulation analysis. The required power data were obtained through varying the supply voltage from 250 V to 215 V with a 5 V reduction. The appliances’ components were identified using the ZIP coefficients solved with the Sequential Least Squares Programming optimizer in Python (Spyder 5.5.4). The CVR_f for residential appliances was determined using the well-established voltage and power correlation analysis. The study’s findings demonstrate a strong association between the appliance load composition determined by the ZIP load model and CVR_f. This paper’s primary contribution is a comprehensive analysis conducted using the ZIP and CVR techniques to ascertain each appliance’s load composition. Based on the findings of this study, a classification is developed and extended to include a range of findings from other published studies in which the conclusion is consistent. Moreover, the CVR_f value for one residence corresponds to a residential substation CVR_f which is further validated via bottom-up load model analysis. The main contribution of this paper is to categorize residential appliances based on constant impedance, constant current, and constant power through the ZIP load model and the CVR_f. Additionally, this CVR analysis is the pioneer study in Malaysia; thus, it is crucial to develop a systematic approach for identifying and classifying household devices according to their electrical characteristics. Load categorization provides the fundamental understanding about an appliance to determine its behavior towards a change in voltage, thus establishing cost savings and energy management in a home. Full article

In recent years, the effects of global climate change have become more apparent, and reducing energy-derived CO₂ emissions has become an important issue. The purpose of this study is to evaluate the CO₂ emission reduction effect according to energy conservation scenarios in the residential sector, based on actual data. In this study, we set up energy-saving scenarios assuming the implementation of energy-saving behavior and the replacement of energy-consuming equipment and calculated the CO₂ emission reduction effects of energy conservation for cooling, heating, and hot water using individual data from a large-scale survey of 29,161 samples. Consequently, we could quantify the relationship between the set scenarios and the associated CO₂ reduction effects. Based on the results, we compared countermeasures and considered their respective potentials. However, despite there being an aggressive scenario in which all households implemented energy conservation measures, the calculated savings were limited. Therefore, we also considered the potential of demand response as a rough estimate. The results indicated that, while continued efforts to curb energy demand are necessary, a comprehensive countermeasure approach is important for achieving carbon neutrality. Full article

As an important ecological barrier and economic belt in China, the sustainable development of the Yellow River Basin (YRB) is of great significance to national ecological security and regional economic balance. Based on the coupled and coordinated development analysis of the water–soil–energy–carbon (W-L-E-C) system in the provinces of the Yellow River Basin from 2002 to 2022, this study systematically analyzed the interaction relationship among the various factors through WLECNI index assessment, factor identification, and driving factor exploration. Thus, it fully reveals the spatiotemporal evolution law of regional coordinated development and its internal driving mechanism. It is found that the coordinated development of the W-L-E-C system in different provinces of the Yellow River Basin presents significant spatiotemporal differentiation, and its evolution process is influenced by multiple factors. It is found that the coordination of the YRB presents a significant spatial difference, and Inner Mongolia and Shaanxi, as high coordination areas, have achieved significant improvement in coordination, through ecological restoration and clean energy replacement, arable land intensification, and industrial water-saving technology, respectively. Shandong, Henan, and Shanxi in the middle coordination zone have made some achievements in industrial greening and water-saving technology promotion, but they are still restricted by industrial carbon emissions and land resource pressure. The Ningxia and Gansu regions with low coordination are slow to improve their coordination due to water resource overload and inefficient energy utilization. Barrier factor analysis shows that the water resources utilization rate (W4), impervious area (L4), energy consumption per unit GDP (E1), and carbon emissions from energy consumption (C3) are the core factors restricting coordination. Among them, the water quality compliance rate (W5) of Shanxi and Henan is very low, and the impervious area (L4) of Shandong is a prominent problem. The interaction analysis of the driving factors showed that there were significant interactions between water resource use and ecological protection (W-E), land resource and energy use (L-E), and carbon emissions and ecosystem (C-E). Inner Mongolia, Shaanxi, and Shandong achieved coordinated improvement through “scenic energy + ecological restoration”, cultivated land protection, and industrial greening. Shanxi, Henan, and Ningxia are constrained by the “W-L-E-C” complex obstacles. In the future, the Yellow River Basin should implement the following zoning control strategy: for the areas with high coordination, it should focus on consolidating the synergistic advantages of ecological protection and energy development; water-saving technology and energy consumption reduction measures should be promoted in the middle coordination area. In the low coordination area, efforts should be made to solve the problem of resource overload, and the current situation of low resource utilization efficiency should be improved by improving the utilization rate of recycled water and applying photovoltaic sand control technology. This differentiated governance plan will effectively enhance the level of coordinated development across the basin. The research results provide a decision-making framework of “zoning regulation, system optimization and dynamic monitoring” for the sustainable development of the YRB, and provide a scientific basis for achieving high-quality development of the basin. 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

Energy efficiency and CO₂ emission reduction are key objectives related to climate change mitigation, sustainable development, and energy resource management. In the Nordic context, energy consumption trends in both the residential and industrial sectors are closely linked to European Union policies, technological innovation, and real estate investments. In recent decades, the development and renovation of the real estate sector has become one of the most important factors determining changes in energy consumption, especially in residential buildings, which remain among the largest energy consumers and polluters. In this context, countries’ efforts to reduce CO₂ emissions and increase energy efficiency are inseparable from the real estate sector’s contribution to these processes, by promoting investments in building modernization and energy-saving technologies. However, the real estate sector remains a complex area where economic interests need to be reconciled with environmental objectives, especially in the context of EU strategies such as the Renovation Wave and the Energy Efficiency Directive. This article examines the links between real estate investment, energy efficiency, and CO₂ emission reduction, based on quantitative analysis, to assess how the development of the real estate sector and EU policy measures affect sustainable development in Northern Europe. This study uses advanced quantitative methods, including a panel regression model, which helps better reveal the long-term dependencies between investment, energy consumption, and emissions dynamics. This article highlights the importance of the real estate sector in implementing sustainability policies and suggests strategic solutions that can help reconcile economic and environmental priorities. Full article

The inherent energy constraints of sensor nodes render energy efficiency optimization a critical challenge in wireless sensor network deployments. This study presents an innovative acoustic source localization framework incorporating a two-level data aggregation technology, specifically designed to minimize energy expenditure while prolonging network lifetime. A mixed noise model is proposed to describe the characteristics of abnormal noise in real environments. Subsequently, the novel two-level data aggregation technology is proposed. The first level is implemented at individual sensors, where a large number of similar measurements may be collected. The second level data aggregation technology is performed at the cluster head nodes to eliminate the data redundancy between different sensor nodes. After the novel two-level data aggregation, most of the redundant data are eliminated and a significant amount of energy is saved. Then, a nonlinear iterative weighted least squares algorithm is applied to complete the final acoustic source location estimation based on the real remaining sensor measurements. Finally, through extensive simulation experiments, it was verified that the two-level data aggregation technology reduced energy consumption by at least 51% and 43%, respectively, and that the RMSE is less than 0.96. Full article

Detailed hydraulic modeling of a water distribution network (WDN) in an urban area is implemented therein, based on data from geoinformatic tools (GIS), to investigate and analyze the network’s hydraulic response to different scenarios of operation. A detailed mapping of the water meters of the consumers in the urban district is therefore conducted in the frame of a District Metered Area (DMA) zoning. Different consumptions according to water meters and patterns of daily water demand, resulting from both theoretical and measured data from a limited number of smart meters, are used in the hydraulic simulations. The analysis conducted assists common engineering practice to identify critical locations for constructing new hydraulic infrastructure, resulting in the restructuring and reorganization of the DMA, assisting to face existing and common problems of WDNs within the general framework of DMA design and efficient water management. A case study on the WDN of Efkarpia, located in the city of Thessaloniki, Greece, satisfying the principal design criteria of DMAs, is presented in this work, under both normal and emergency conditions. Hydraulic analysis is performed based on different scenarios, mainly consisting of different consumptions according to water meters and different demand patterns, all resulting in high pressures in the southern part of the DMA. Hydraulic simulations are then performed considering two basic operating scenarios, namely the operation of the old DMA of Efkarpia and a new DMA, which is reduced in size. The two scenarios are compared in terms of estimated pressures in the studied area, as well as in terms of energy consumption in the upstream pumping station. The comparisons reveal that the new DMA outperforms the old one, with a large increase in the pressure at nodes where low pressures were assessed in the old DMA, a reduction in daily pressure variation up to 45%, and quite significant energy savings assessed around 21.6%. Full article

The increasing adoption of intermittent renewable energy sources and electric vehicles in households necessitates effective energy management systems (EMS) in the residential sector. This study quantifies the economic benefits of using a state-of-the-art EMS for optimally controlling a grid-connected smart home, which includes PV panels, a battery, and an EV charging station with either monodirectional or bidirectional charging modes. The EMS uses a two-layer approach: the first layer handles strategic decisions with day-ahead forecasts and solving a mixed-integer linear program (MILP) model; the second layer manages the real-time control decisions based on a heuristic strategy. Tested on 396 real-world case studies (based on measured data) with varying user types and energy systems (different PV plant sizes, with or without BESS, and different EV charging modes), different EV models, and weekly commutes, the results demonstrate the EMS’s cost-effectiveness compared to current non-predictive heuristic strategies. Annual cost savings exceed 20% in all cases and reach up to 900 €/year for configurations with large (6 kW) PV plants. Additionally, while installing a battery is not economically advantageous, bidirectional EV chargers yield 10–15% additional savings compared to monodirectional chargers, increasing with more weekly remote working days. Full article

Aging residential buildings in urban areas require effective thermal insulation to enhance energy efficiency and indoor comfort. In Bosnia and Herzegovina (BiH), expanded polystyrene (EPS) is the most commonly used insulation material due to its affordability, despite concerns regarding its flammability and environmental impact. While regulatory changes since 2019 have recommended rock wool for high-rise buildings, the absence of binding fire safety regulations has allowed the continued use of EPS, often driven by financial constraints. This study examines energy efficiency refurbishments in Sarajevo’s high-rise residential buildings and analyze the implications of the partial implementation of recommended measures. Using case studies, surveys, and expert interviews, this research identifies key challenges, such as limited funding, fragmented renovations, and inconsistent coordination between stakeholders. The findings indicate that facade insulation is often prioritized over comprehensive upgrades, including window replacement and heating system improvements, leading to suboptimal energy savings and minimal cost reductions for residents. Additionally, the complexity of multi-apartment ownership structures hinders uniform improvements in energy efficiency. Despite these challenges, property values tend to increase after renovation, highlighting the long-term financial benefits. To maximize energy savings and ensure sustainable urban housing, stronger interdisciplinary collaboration, improved funding mechanisms, and adherence to fire-safety standards are necessary. These measures would enhance the effectiveness of renovations and support long-term energy efficiency strategies. Full article

The new passive phase change thermal storage window integrates advanced energy-saving materials and technologies to provide efficient insulation and mechanical properties. It is suitable for green buildings. Through on-site experiments and simulations in summer, autumn, and winter in Jilin City, the cyclic use function of summer insulation and winter heating has been verified. This article establishes a numerical model and compares it with measured data to verify the accuracy of the model. In order to further verify the practicality of the new window, it was applied and tested at the Yichun substation in the cold winter region. The results showed that the new window can significantly reduce energy consumption while increasing indoor temperature. This article used a refined model established by Green Building Saville and Airpak3.0 software to deeply analyze the energy consumption and temperature field distribution of the window, and verified the reliability of numerical analysis in performance prediction. This study not only proves the effectiveness of the new phase change thermal storage window but also provides a new solution for the energy-saving design of green buildings. Full article

The impetus of the present work is to propose a comprehensive methodology for the numerical evaluation of drying/curing, as one of the most complex and energy-consuming stages in the paint shop plant, to guarantee a decrease in energy costs without sacrificing the final paint film quality and manufacturability. Addressing the complexities of vehicle assembly, such as intricate geometry and multi-zoned ovens, our approach employs a sophisticated conjugate heat transfer (CHT) algorithm, developed under the OpenFOAM framework, providing efficient heat transfer with the accompaniment of the Large Eddy Simulation (LES) turbulence model, thereby delivering high-fidelity data. This algorithm accurately simulates turbulence and stress in the oven, validated through heat sink cases and closely aligning with experimental data. Applying modifications for the intake supply heated airflow rate and direction leads to optimal recirculation growth in the measured mean temperature within with the curing oven and along the car body surface, saving a significant amount of energy. Key adjustments in airflow direction improved temperature regulation and energy efficiency while enhancing fluid dynamics, such as velocity and temperature distribution. Furthermore, the study integrates machine learning to refine the oven’s heat-up region, which is crucial for preventing paint burnout. A data-based model using a variational auto-encoder (VAE) and an artificial neural network (ANN) effectively encodes temperature and velocity fields. This model achieves an impressive 98% accuracy within a 90% confidence interval, providing a reliable tool for predicting various operational conditions and ensuring optimal oven performance. Full article