Search Results (30,046)

Industry 4.0 (I4.0) represents a transformative approach, integrating technology, production methods, and information and communication technology to enhance industrial value creation. A central I4.0 goal in the energy domain is improving energy efficiency to boost industrial competitiveness and profitability. Given that induction motors account for nearly two-thirds of industrial electrical energy consumption, optimizing their efficiency is crucial. Energy management systems (EMSs) need real-time data to assess motor efficiency, enabling prompt identification and replacement of inefficient motors with alternatives that have optimal efficiency class and rated power for specific applications. This paper introduces a novel non-intrusive method for estimating the load and efficiency of induction motors without disrupting their operation. To reach that goal, the proposed method optimizes the parameters of a set of relationships between output power, input power, and losses with the motor speed, minimizing the error in the estimates. It requires only input electrical power and motor speed measurements to set the model parameters and estimates the load and efficiency using either speed or input power measurements. The experimental results demonstrate that the proposed method, with a mean overall error of less than 3.5% in estimating output power and efficiency, outperforms conventional methods. Full article

Abstract: Hydropower is a vital strategic component of China’s clean energy development. Its construction and optimized water resource allocation are crucial for addressing global energy challenges, promoting socio-economic development, and achieving sustainable development. However, the optimization scheduling of cascade hydropower stations is a large-scale, multi-constrained, and nonlinear problem. Traditional optimization methods suffer from low computational efficiency, while conventional intelligent algorithms still face issues like premature convergence and local optima, which severely hinder the full utilization of water resources. This study proposed an improved whale optimization algorithm, the Black-winged Differential-variant Whale Optimization Algorithm (BDWOA), which enhanced population diversity through a Logistic-Sine-Cosine combination chaotic map, improved algorithm flexibility with an adaptive adjustment strategy, and introduced the migration mechanism of the black-winged kite algorithm along with a differential mutation strategy to enhance the global search ability and convergence capacity. The BDWOA algorithm was tested using test functions with randomly generated simulated data, with its performance compared against five related optimization algorithms. Results indicate that the BDWOA achieved the optimal value with the fewest iterations, effectively overcoming the limitations of the original whale optimization algorithm. Further validation using actual runoff data for the cascade hydropower station optimization scheduling model showed that the BDWOA effectively enhanced power generation efficiency. In high-flow years, the average power generation increased by 8.3%, 6.5%, 6.8%, 4.1%, and 8.2% compared to the five algorithms while achieving the shortest computation time. Significant improvements in power generation were also observed in normal-flow and low-flow years. The scheduling solutions generated by the BDWOA can adapt to varying inflow conditions, offering an innovative approach to solving complex hydropower station optimization scheduling problems. This contributes to the sustainable utilization of water resources and supports the long-term development of renewable energy. Full article

The implementation of sponge cities in China modifies the hydrological conditions of the underlying surface, effectively alleviating the urban heat island effect. However, in planning and construction, heat island mitigation targets are difficult to quantify and lack quantitative design and evaluation methods. To address this issue, two planning schemes were proposed based on sponge city management and control indicators. The WRF-UCM model was used to conduct numerical simulations of the current conditions (case 1) and the sponge city planning schemes (cases 2 and 3), analyzing the impact of sponge city initiatives on the mitigation of the heat island effect. The results indicated that by changing the structure of the underlying surface and increasing the water content of the underlying surface, the sponge city affects the urban energy distribution process and regional horizontal advection pattern. This not only reduces heat accumulation within the urban area but also suppresses regional convection during high-temperature periods, thereby mitigating the urban heat island effect. Moreover, different schemes following the same sponge city design requirements have varying impacts on urban microclimate elements and heat island distributions. Notably, a higher subsurface water content yields a more pronounced inhibition of the heat island effect. Finally, a sponge city planning method with the consideration of heat island mitigation was proposed, facilitating pre-simulation optimization and decision-making in sponge city planning. Full article

This review article discusses the performance evaluation and integration strategies for solar façades, focusing on photovoltaic (PV) façades in diverse climatic conditions. It examines recent technology developments and methodologies for performance assessment, highlighting the potential of solar façades to enhance energy performance through on-site electricity generation. This study offers novel insights into the economic viability of façade-mounted photovoltaics, highlighting their potential in urban areas with constrained rooftop availability. Additionally, it emphasizes their distinct advantages in cold climates, such as reduced maintenance requirements and extended operational lifespans. Additionally, it addresses challenges such as technical complexity, esthetic considerations, and market awareness, emphasizing the balance between efficiency and design. Novel findings underscore the promise of advanced materials like perovskites in improving the flexibility and performance, as well as strategies to optimize BIPV integration in different climate zones. For stakeholders, this research highlights the importance of supportive policies and innovative solutions to overcome barriers, while offering researchers valuable perspectives on the advancement of solar façades toward zero-energy and zero-carbon building targets. Full article

With the energy transition, energy supply trends indicate more autonomy for the final consumer, with a more decentralized, intelligent, and low-carbon scenario. Multigeneration technologies offer substantial socioeconomic and environmental advantages by enhancing the efficient utilization of energy resources. The main objective of this study is to develop a flexible, easy-to-use tool for the optimization of multigeneration systems (configuration and operation), focused on obtaining minimal annual costs. C++ was used for the implementation of the optimization problem, which was solved using IBM’s ILOG CPLEX Optimization Studio solver. The case study is a residential consumer center, with energy demands encompassing electricity (including electric vehicles), sanitary hot water, and coolth (air conditioning). The optimal economic solution indicates the installation of 102 photovoltaic modules and the use of biomass to produce hot water. When compared with a conventional solution, where all energy demands are met conventionally (no renewables nor cogeneration), the optimal economic solution reduced annual costs by 27% despite presenting capital costs 42% higher. Full article

With rapid urbanization and industrialization, Vietnam is facing many challenges in solid waste management and increasing energy demand. In this context, the development of renewable energy from solid waste not only solves the problem of environmental pollution but also makes an important contribution to energy security and sustainable economic development. Solid waste to energy is a system of solid waste reatment by thermal methods, in which the heat generated from this treatment process is recovered and utilized to produce energy. Site selection is one of the biggest challenges for renewable energy projects. In addition to technical factors, this decision must also consider environmental impacts, including protecting ecosystems, minimizing noise, and limiting impacts on public health. To solve this problem, multi-criteria decision making (MCDM) methods combined with fuzzy numbers are often used. These methods allow planners to evaluate and balance competing factors, thereby determining the most optimal location for the project. In this study, the authors proposed a Spherical Fuzzy Multi-Criteria Decision-making Model (SFMCDM) for site selection in solid waste-to-energy projects. In the first stage, all criteria affecting the decision-making process are defined based on literature review, experts and triple bottom line model (social, environmental, and economic), and analytic hierarchy process (AHP), and fuzzy theory is applied for calculating the weights in the second stage. The weighted aggregated sum product assessment (WASPAS) method is utilized for ranking four potential locations in the final stage. The contribution of the proposed process is its structured, systematic, and innovative approach to solving the location selection problem for renewable energy projects. Choosing the right location not only ensures the success of the project but also contributes to the sustainable development of renewable energy. Full article

The greenhouse effect and global warming, driven by the accumulation of pollutants, such as sulfur oxides (SOx), nitrogen oxides (NOx), and CO₂, are primarily caused by the combustion of fossil fuels and volcanic eruptions. These phenomena represent an international crisis that negatively impacts human health and the environment. Several studies have reported novel carbon capture, utilization, and storage (CCUS) technologies, promising solutions. Notable methods include chemical absorption using solvents, and the development of functionalized porous materials, such as MCM-41, impregnated with amines like polyethyleneimine. These technologies have demonstrated high capture capacity and thermal stability; however, they face challenges related to recyclability and high operating costs. In parallel, biodegradable polymers and hydrogels present sustainable alternatives with a lower environmental impact, although their industrial scalability remains limited. This review comprehensively analyzes CO₂ capture methods, focusing on silica-based porous supports, polymers, hydrogels, and emerging techniques, like CCUS and MOFs, while including traditional methods and a bibliometric analysis to update the field’s scientific dynamics. With increasing investigations focused on developing new CCUS technologies, this study highlights a growing interest in eco-friendly alternatives. A bibliometric analysis of 903 articles published between 2010 and 2024 provides an overview of current research on environmentally friendly carbon capture technologies. Countries such as the United States, the United Kingdom, and India are leading research efforts in this field, emphasizing the importance of scientific collaboration. Despite these advancements, implementing these technologies in industrial sectors with high greenhouse gas emissions remains scarce. This underscores the need for public policies and financing to promote their development and application in these sectors. Future research should prioritize materials with high capture capacity, efficient transformation, and valorization of CO₂ while promoting circular economy approaches and decarbonizing challenging sectors, such as energy and transportation. Integrating environmentally friendly materials, energy optimization, and sustainable strategies is essential to position these technologies as key tools in the fight against climate change. Full article

Fly ash consists of significant amounts of lithium, which is an essential resource for developing batteries. This study proposed an efficient method for extracting lithium from fly ash. First, we explored the parameters affecting the activation effect of sodium carbonate roasting and the leaching efficiency of lithium using acid leaching. Additionally, ultrasonic pre-treatment was applied to enhance activation. A further mechanism for the roasting extraction of lithium was symmetrically analyzed. The results showed that ultrasonic treatment at 200 W for 1 h under alkaline leaching conditions (sodium hydroxide solution 4 mol/L, reaction temperature 80 °C, leaching time 2 h, solid–liquid ratio 1 g:30 mL) achieved a lithium leaching rate of 90.74%, surpassing the 84.72% with traditional roasting–alkaline leaching. Under optimal acid leaching conditions (850 °C for reaction of 2.5 h, fly ash-to-sodium carbonate ratio (R_fs) 1:2, sulfuric acid 2 mol/L, reaction temperature 80 °C, solid–liquid ratio 1 g:30 mL, and leaching time 1.5 h), the leaching rate reached 96.62%. With ultrasonic pre-treatment and acid leaching, the highest leaching rate of 98.68% achieved under optimal conditions: reaction temperature 850 °C for 2.5 h, mass R_fs at 1:1.5, sulfuric acid 2 mol/L, reaction temperature 80 °C, solid–liquid ratio 1 g:35 mL, and leaching time 120 min. The study demonstrated that ultrasonic pre-treatment outperforms the traditional method, achieving a higher leaching rate with fewer roasting additives and lower energy consumption. Full article

Vehicle-to-vehicle dynamic wireless charging (V2V-DWC) represents a modern advancement in electrified transportation, where a specialized charging vehicle delivers power to another vehicle on the move. The rising popularity of this technology can be attributed to the gradual advancements in energy storage technologies and the scarcity of plug-in charging infrastructure. V2V wireless power transfer provides a solution for electric vehicles (EVs) to recharge their batteries while in transit. The existing literature confirms the empirical validation of this concept through analytical and experimental studies, yet the challenge of misalignment remains insufficiently explored. Achieving optimal power transfer in V2V systems necessitates precise alignment of the inductive coils. Lateral misalignment (LTM) occurs due to the deviation of the coils from the proper alignment, leading to significant energy losses. Additionally, the development of effective controllers to address the V2V misalignment problem remains inadequate. This study proposes the development of a neural network-based adaptive fuzzy logic controller (ANFIS) to alleviate the misalignment issues in V2V-DWC systems. A comparative analysis is conducted between the proposed ANFIS controller and the conventional fuzzy logic controller (FLC) to evaluate their performance across various degrees of LTM. The performance of the proposed ANFIS controller is evaluated through simulations in MATLAB/Simulink, supplemented by experimental testing. The results indicate that the proposed ANFIS controller surpasses the FLC in both simulation and experimental contexts in addressing the V2V misalignment challenge. Full article

This paper details the enhancement of the optoelectronic properties of Cu-(In, Ga)-Se₂ (CIGSe) solar cells through a two-segment process in the ultraviolet (UV)–visible spectral range. These include fine-tuning the DC sputtering power of the absorber layer (ranging from 20 to 40 W at segment I) and thoroughly checking the trace micro-chemistry composition of the absorber layer (CdS, ZnO/CdS, ZnMgO/CdS, and ZnMgO at segment II). After segment I of treatment, the optimal 30 W CIGSe absorber layer (i.e., with a 0.95 CGI ratio) can be obtained, it can be seen that the Cu-rich film exhibits the ability to significantly promote grain growth and can effectively reduce its trap state density. After the segment II process aimed at replacing toxic CdS, the optimal metal alloy (Zn_0.9Mg_0.1O) composition (buffer layer) achieved the highest conversion efficiency (η) of 8.70%, also emphasizing its role in environmental protection. Especially within the tunable bandgap range (2.48–3.62 eV), the developed overall internal and external quantum efficiency (IQE/EQE) is significantly improved by 13.15% at shorter wavelengths. A photovoltaic (PV) module designed with nine optimal CIGSe cells demonstrated commendable stability. Variation remained within ±5% throughout the 60-day experiment. The PV modules in this study represent a breakthrough benchmark toward a significant advance in the scientific understanding of renewable energy. Furthermore, this research clearly promotes the practical application of PV modules, harmonizes with sustainable goals, and actively contributes to the creation of eco-friendly communities. Full article

Anaerobic digestion (AD) is a promising and yet a complex waste-to-energy technology. To optimize such a process, precise modeling is essential. Developing complex, mechanistically inspired AD models can result in an overwhelming number of parameters that require calibration. This study presents a novel approach that considers the role of trace metals (Ca, K, Mg, Na, Co, Cr, Cu, Fe, Ni, Pb, and Zn) in the modeling, numerical simulation, and optimization of the AD process in a batch bioreactor. In this context, BioModel is enhanced by incorporating the influence of metal activities on chemical, biochemical, and physicochemical processes. Trace metal-related parameters are also included in the calibration of all model parameters. The model’s reliability is rigorously validated by comparing simulation results with experimental data. The study reveals that perturbations of 5% in model parameter values significantly increase the discrepancy between simulated and experimental results up to threefold. Additionally, the study highlights how precise optimization of metal additives can enhance both the quantity and quality of biogas production. The optimal concentrations of trace metals increased biogas and CH₄ production by 5.4% and 13.5%, respectively, while H₂, H₂S, and NH₃ decreased by 28.2%, 43.6%, and 42.5%, respectively. Full article

Microalgae have attracted wide attention due to their extensive application potential. Dewatering is a necessary work for the application of microalgae, especially in biofuel production, where forward osmosis (FO) research is relatively advanced but still faces technical bottlenecks hindering large-scale commercialization. Based on the current research in recent years, the research progress in the causes and control of membrane fouling, the development of membrane materials and optimization of membrane structure, and the energy saving and efficiency of the process are reviewed in this paper. We found that different species of algae have direct effects on membrane fouling. Chlorella vulgaris has a low membrane fouling trend, but the mechanisms of fouling need further investigation. The material development and structure optimization of membranes are the main research methods to reduce membrane fouling, but there are still some defects, such as complicated preparation and low water flux, which are difficult to apply on a large scale. The research progress of reducing costs by using seawater, urine, fertilizer, etc. as new draw solutions (DS) is reviewed. At present, many aspects of FO microalgae dewatering technology are still not well understood, and future research should focus on scaling up the existing technologies. Full article

In the context of global carbon emissions and climate change, identifying context-specific low-carbon pathways for urban areas is critical for achieving socio-environmental sustainability. This study applies the technology–organization–environment (TOE) framework to examine the driving mechanisms and the diversity in carbon reduction pathways across 81 cities in China. Utilizing partial least squares structural equation modeling (PLS-SEM) and necessary condition analysis (NCA), this research assesses the roles of technological, organizational, and environmental drivers in urban carbon reduction. Fuzzy-set qualitative comparative analysis (fsQCA) is employed to uncover distinct carbon reduction pathways and causal asymmetries between cities. The findings reveal that technological, organizational, and environmental factors significantly drive carbon reduction, with technological and organizational factors playing the central roles. Environmental factors exert primarily indirect effects, interacting with technological and organizational drivers. This study categorizes cities into three distinct carbon reduction models: cities with high carbon-neutral potential primarily leverage technological innovation and energy efficiency optimization; cities with moderate potential integrate technology and policy, emphasizing green landscape planning to achieve balanced development; and cities with lower carbon reduction potential are mainly policy-driven, constrained by technological and resource limitations. This study underscores the role of computational modeling in providing valuable insights for the development of context-tailored carbon reduction strategies. It highlights the synergetic interactions among technological, organizational, and environmental factors, offering essential guidance for advancing sustainable development planning and facilitating the low-carbon transition of cities and communities. Full article

Industrial production today increasingly prioritizes sustainability, emphasizing not only efficiency but also minimizing environmental and social impacts. Quality control is key in steel production. The continuous casting process is crucial, as early defect detection can lower costs and prevent unnecessary material use, thereby conserving energy and raw materials. Eliminating defects early reduces the need for costly reworking, saving resources and reducing equipment wear. Additionally, this defect prevention supports efficiency in later steps, like rolling, benefiting overall energy and material consumption. During this research, we identified several parameters whose influence we analyzed on the surface quality of deep-drawn steel. The research confirmed that, for example, the casting speed has a significant influence on the occurrence of surface defects, while, for example, the final bubbling had no statistically significant effect on the surface quality. From a sustainability perspective, monitoring and optimizing key production parameters, like the casting speed, is essential, as improper speeds can cause surface defects that risk the functionality of the final products. By optimizing these parameters, it is possible not only to reduce the risk of product failure but also to contribute to the long-term sustainability of the entire production process, reducing waste and fostering a more considerate approach to natural resources. Full article

Wind and solar energy sources, while sustainable, are inherently variable in their power generation, posing challenges to grid stability due to their non-dispatchable nature. To address this issue, this study explores the synergistic optimization of wind and solar photovoltaic resources to mitigate power output variability, reducing the strain on local grids and lessening the reliance on balancing power in high-penetration renewable energy systems. This critical role of providing stability can be effectively fulfilled by run-of-river hydropower plants, which can complement fluctuations without compromising their standard operational capabilities. In this research, we employ a straightforward energy balance model to analyze the feasibility of a 100 MW virtual hybrid power plant, focusing on the northern region of Portugal as a case study. Leveraging actual consumption and conceptual production data, our investigation identifies a specific run-of-river plant that aligns with the proposed strategy, demonstrating the practical applicability of this approach. Full article