Search Results (2,198)

The environmental challenges posed by global warming have significantly increased the global pursuit of renewable and clean energy sources. Among these, solar energy stands out due to its abundance, renewability, low environmental impact, and favorable long-term economic viability. However, its intermittent nature and dependence on weather conditions hinder consistent and efficient utilization. To address these limitations, nanoparticle-enhanced phase change materials (NPCMs) have emerged as a promising solution for enhancing thermal energy storage in solar thermal systems. NPCMs incorporate superior-performance nanoparticles within traditional phase change material matrices, resulting in improved thermal conductivity, energy storage density, and phase change efficiency. This review systematically examines the recent advances in NPCMs for solar energy applications, covering their classification, structural characteristics, advantages, and limitations. It also explores in-depth analytical approaches, including mechanism-oriented analysis, simulation-based modelling, and algorithm-driven optimization, that explain the behavior of NPCMs at micro and macro scales. Furthermore, the techno-economic implications of NPCM integration are evaluated, with particular attention to cost-benefit analysis, policy incentives, and market growth potential, which collectively support broader adoption. Overall, the findings highlight NPCMs as a frontier in materials innovation and enabling technology for achieving low-carbon, environmentally responsible energy solutions, contributing significantly to global sustainable development goals. Full article

Borophene, a two-dimensional (2D) allotrope of boron, has emerged as a highly promising material owing to its exceptional mechanical strength, electronic conductivity, and diverse structural phases. Unlike graphene and other 2D materials, borophene exhibits inherent anisotropy, flexibility, and metallicity, offering unique opportunities for advanced nanotechnological applications. This review presents a comprehensive summary of recent progress in borophene synthesis methods, highlighting both bottom–up strategies such as chemical vapor deposition (CVD) and molecular beam epitaxy (MBE), and top–down approaches, including liquid-phase exfoliation and sonochemical techniques. A key challenge discussed is the stabilization of borophene’s polymorphs, as bulk boron’s non-layered structure complicates exfoliation. The influence of substrates and doping strategies on structural stability and phase control is also explored. Moreover, the intrinsic physicochemical properties of borophene, including its high flexibility, oxidation resistance, and anisotropic charge transport, were examined in relation to their implications for electronic, catalytic, and sensing devices. Particular attention was given to borophene’s performance in hydrogen storage and hydrogen evolution reactions (HERs), where functionalization with alkali and transition metals significantly enhances H₂ adsorption energy and storage capacity. Studies demonstrate that certain borophene–metal composites, such as Ti- or Li-decorated borophene, can achieve hydrogen storage capacities exceeding 10 wt.%, surpassing the U.S. Department of Energy targets for hydrogen storage materials. Despite these promising characteristics, large-scale synthesis, long-term stability, and integration into practical systems remain open challenges. This review identifies current research gaps and proposes future directions to facilitate the development of borophene-based energy solutions. The findings support borophene’s strong potential as a next-generation material for clean energy applications, particularly in hydrogen production and storage systems. Full article

Lithium-ion batteries are pivotal components in battery electric vehicles, significantly influencing vehicle design and performance. This study investigates the interactions between cell properties and battery pack characteristics through statistical correlation analysis of datasets derived from industry-leading benchmarking platforms. Findings indicate that energy densities are comparable across cell formats at the pack level. While NMC and NCA chemistries outperform LFP in energy density at both cell and pack levels, LFP’s favorable cell-to-pack factors mitigate these differences. Analysis of cell properties suggests that increases in cell-level volumetric and gravimetric energy density result in proportionally smaller gains at the pack level due to the growing proportion of required passive components. The impact of cell chemistry and format on the z-dimension of a battery pack is analyzed in order to identify dependencies and influences between nominal cell properties and the geometry of the battery pack. The analysis suggests no significant influence of the used cell chemistry on the vertical dimension of a battery pack. The consideration of cell formats shows a dependency between the battery pack z-dimension and cell geometry, with prismatic cells reaching the highest pack heights and cylindrical cells being observed in packs of smaller vertical dimensions. The study also investigates the emerging sodium-ion battery technology and assesses pack-level energy densities derived from cell-level properties. The insights of this study contribute to the understanding of cell-to-pack relationships, guiding R&D toward improved energy storage solutions for electric vehicles. Full article

Against the backdrop of accelerating global energy transition, developing high-performance energy-storage systems is crucial for achieving carbon neutrality. Traditional electrode materials are limited by a single densification storage mechanism and low conductivity, struggling to meet demands for high energy/power density and a long cycle life. Carbon/high-entropy alloy nanocomposites provide an innovative solution through multi-component synergistic effects and cross-scale structural design: the “cocktail effect” of high-entropy alloys confers excellent redox activity and structural stability, while the three-dimensional conductive network of the carbon skeleton enhances charge transfer efficiency. Together, they achieve synergistic enhancement via interfacial electron coupling, stress buffering, and dual storage mechanisms. This review systematically analyzes the charge storage/attenuation mechanisms and performance advantages of this composite material in diverse energy-storage devices (lithium-ion batteries, lithium-sulfur batteries, etc.), evaluates the characteristics and limitations of preparation techniques such as mechanical alloying and chemical vapor deposition, identifies five major challenges (including complex and costly synthesis, ambiguous interfacial interaction mechanisms, lagging theoretical research, performance-cost trade-offs, and slow industrialization processes), and prospectively proposes eight research directions (including multi-scale structural regulation and sustainable preparation technologies, etc.). Through interdisciplinary perspectives, this review aims to provide a theoretical foundation for deepening the understanding of carbon/high-entropy alloy composite energy-storage mechanisms and guiding industrial applications, thereby advancing breakthroughs in electrochemical energy-storage technology under the energy transition. Full article

The soft-reset process, or a sequence of charge emissions from a floating storage node through a transistor biased in a subthreshold bias condition, is modeled by a master (Kolmogorov–Bateman) equation. The Coulomb interaction energy after each one-charge emission leads to a stepwise potential increase, giving correlated emission rates represented by Boltzmann factors. The governing probability distribution function is a hypoexponential type, and its cumulants describe characteristics of the single-charge Coulomb interaction at room temperature on a mesoscopic scale. The cumulants are further extended into a complex domain. Starting from three fundamental assumptions, i.e., the generation of non-degenerated states due to single-charge Coulomb energy, the Markovian property of each emission event, and the independence of each state, a moment function is identified as a product of mutually prime elements (algebraically termed as prime ideals) comprising the eigenvalues or the lifetimes of the emission states. Then, the algebraic structure of the moment function is found to be highly analogous to that of an integer uniquely factored into prime numbers. Treating the lifetimes as analogs of the prime numbers, two types of zeta functions are constructed. Standard analyses of the zeta functions analogous to the prime number problem or the Riemann Hypothesis are performed. For the zeta functions, the analyticity and poles are specified, and the functional equations are derived. Also, the zeta functions are found to be equivalent to the analytic extension of the cumulants. Finally, between the number of emitted charges and the lifetime, a logarithmic relation analogous to the prime number theorem is derived. Full article

Hybrid offshore wind-wave systems play an important role in renewable energy transition. To maximize energy utilization efficiency, a comprehensive assessment to select optimal locations is urgently needed. The hydraulic power characteristics of these systems cause power fluctuations that reduce grid frequency stability. Thus, a site suitability assessment and a grid-forming battery energy storage system (BESS) configuration method are proposed. Considering energy efficiency, dynamic complementary characteristics, and output stability, a framework integrating three indices of Composite Energy Output Index (CEOI), Time-Shifted Cross-Covariance Index (TS-CCI), and Energy Penetration Balance Index (EPBI) is constructed to assess site suitability. To ensure secure and stable operation of microgrid, the frequency response characteristics of the hybrid system are analyzed, and the corresponding frequency constraint is given. A BESS configuration method considering frequency constraint is developed to minimize life cycle costs and maintain grid stability. Applied to a case study along China’s southeast coast, the assessment method successfully identified the optimal offshore station, confirming its practical applicability. The BESS configuration method is validated on a modified IEEE 30-bus system, with a 6.35% decrease in life cycle cost and complete renewable utilization. This research provides a technical and cost-effective solution for integrating hybrid wind-wave energy into island microgrids. Full article

Integrating renewable energy, particularly wind power, into modern power systems introduces challenges concerning stability and reliability. These issues require enhanced regulation to balance power supply with load demand. Flexible loads and energy storage provide viable solutions to stabilize the grid without relying on new resources. This paper proposes building thermostatically controlled loads (BTLs), such as heating, ventilation, and air conditioning (HVAC) systems, as flexible demand-side management tools to address the challenges of intermittent energy sources. A new concept is introduced, portraying BTLs as a stochastic battery with losses, offering a compact representation of their dynamics. BTLs’ thermal characteristics, user-defined set points, and ambient temperature changes determine the power limits and energy capacity of this stochastic battery. The model is simulated using DIgSILENT Power Factory, which includes thermal power plants, gas turbines, wind power plants, and BTLs. A dynamic dispatch strategy optimizes power generation while utilizing BTLs to balance grid fluctuations caused by variable wind energy. Performance analysis shows that integrating BTLs with conventional thermal plants can reduce variability and improve grid stability. The study highlights the dual role of simulating overall flexibility and applying dynamic dispatch strategies to enhance power systems with high renewable energy integration. Full article

This study investigates the energy consumption characteristics of individual and clustered thermal storage electric heating systems, focusing on their sustainability implications for regional load distribution and user energy consumption patterns. Simulation results show that thermal storage electric heating shifts peak energy demand from daytime to nighttime low-price hours, reducing electricity costs and optimizing grid load balancing. As the proportion of thermal storage electric heating increases from 10% to 30%, the daytime minimum load reduction rate rises from 7% to 22%, while the nighttime maximum load increase rate increases from 16% to 63%. This operational mode supports sustainable energy usage by alleviating daytime grid peak pressure and leveraging low-cost, off-peak electricity for heat storage. The findings highlight the potential of thermal storage electric heating to enhance energy efficiency, integrate renewable energy, and promote grid stability, contributing to a more sustainable energy system. Full article

This paper proposes a novel unsupervised multi-model fusion framework for robust cell-level anomaly detection in grid-scale battery energy storage systems (BESSs). Addressing the complex nonlinearity and prevalent data quality issues (e.g., asynchronous sensors, sampling anomalies) in historical operational data, the framework synergistically integrates three complementary techniques: isolation forests for efficient feature screening and dimensionality reduction; LSTM autoencoders to capture the long-term temporal dependencies in normal behavior; and a functional principal component analysis–Mahalanobis distance (FPCA-MD) for statistically rigorous anomaly validation. The fully automated workflow pioneers the combined application of feature screening, temporal modeling, and functional data validation for cell-level diagnostics. Key contributions include (1) maintaining a high detection accuracy despite asynchronous or faulty sensor data; (2) leveraging multi-dimensional operational features beyond traditional voltage curves, optimizing the utilization of historical data through tight integration of the battery characteristics with anomaly signatures; and (3) achieving enhanced performance and robustness via the complementary fusion of diverse algorithms. Comprehensive experimental results demonstrate the framework’s effectiveness in accurately identifying cells exhibiting various anomaly patterns (e.g., noise interference, performance degradation, cluster outliers) while significantly reducing the leakage and misdetection rates inherent in single-algorithm approaches, as validated by the probability scores from the fusion output. Full article

Energy shortage and environmental pollution have accelerated the adoption of lithium-ion batteries (LIBs) as efficient energy storage solutions. However, their performance and safety challenges under extreme temperatures highlight the urgent need for effective temperature control during charging and discharging, making a comprehensive understanding of electrochemical and thermal behaviors crucial. This paper develops a 3D electrochemical–thermal coupled model for 150 Ah lithium iron phosphate (LFP) batteries to investigate thermal behavior at varying charge–discharge rates. An integrated learning regression prediction system, incorporating a structured vector autoregression (SVAR) model, is subsequently proposed to analyze the interactions among multiple electrochemical and thermal variables. The temperature difference exceeds 5 °C at higher charging rates (1.3C, 1.5C), driven primarily by accelerated heat generation—especially reversible heat. Complex interactions exist between electrochemical and thermal parameters. When charging at 0.5C, voltage, current density, battery capacity, and the maximum temperature difference (MTD) are all significantly and positively correlated (p < 0.001). Under 1C discharge conditions, voltage exhibits a strong positive correlation with most thermal characteristic variables, and correlation coefficients across different operating conditions range from −0.9731 to 0.973. Finally, the proposed ensemble learning system exhibits excellent prediction accuracy, strong generalization, and robust trend analysis, with practical guiding value. Full article

To alleviate the pressure on grid regulation and ensure grid safety, pumped storage power stations need to frequently start and stop and change operating conditions, leading to the pump-turbine easily entering the hump characteristic zone, causing flow oscillation within the unit and significant changes in its input power, resulting in increased vibration and grid connection failure. The spatial distribution of energy losses and the hydrodynamic flow features within the hump zone of a pump-turbine under pumped storage operation are the focus of the study. The SST k-ω turbulence model is applied in CFD simulations of the pump-turbine within this work, focusing on the unstable operating range of the positive slope, with model testing providing experimental support. The model test method combines numerical simulation with experimental verification. The LEPR method is used to quantitatively investigate the unstable phenomenon in the hump zone, and the distribution law of energy loss is discussed. The results show that, at operating points in the hump zone, up to 72–86% of the energy dissipation is attributed to the runner, the guide vane passage, and the double vane row assembly within the guide vane system. The flow separation in the runner’s bladeless area evolves into a vortex group, leading to an increase in runner energy loss. With decreasing flow rate, the impact and separation of the water flow intensify the energy dissipation. The high-speed gradient change and dynamic–static interference in the bladeless area cause high energy loss in the double vane row area, and energy loss mainly occurs near the bottom ring. In the hump operation zone, the interaction between adverse flows such as vortices and recirculation and the passage walls directly drive the sharp rise in energy dissipation. Full article

The use of thermal insulation material in building envelopes is closely related to economic benefits, energy-savings, and carbon reduction of buildings. The construction forms of different components in building envelopes have an important influence on the optimization design of thermal insulation in building envelopes. In this study, an integrated optimization approach is proposed to search for the best solution of thermal insulation in external walls and the optimal combination scheme of different construction forms of envelope components in granaries. The integrated optimization approach consists of an orthogonal experimental design (OEDM) method-based determination module of an optimal combination scheme of different construction forms of components, an assessment model-based quantitative analysis module, and an integrated assessment indicator-based selection module of the best solution of external wall insulation. Firstly, the OEDM method is used to determine the optimal combination scheme of different construction forms of the foundation wall of an external wall, thermal insulation material, external window, roof, and floors in buildings. Secondly, integrated economic, energy, and carbon analysis models are developed to analyze comprehensive performance of external wall insulation. Finally, an integrated assessment indicator consisting of an energy balanced index, a carbon balanced index, and weight coefficients is presented to determine the best solution of external wall insulation. The applications of this optimization approach in different ecological grain storage zones in China demonstrated that the outdoor air temperature characteristics could affect the comprehensive performance of external wall insulation in granaries, significantly. The best solution of external wall insulation in granaries in Turpan city, Daqing city, Kaifeng city, Changsha city, Anshun city, and Danzhou city was expanded polystyrene insulation (EPS) with a layer thickness of 0.078 m, 0.048 m, 0.083 m, 0.089 m, 0.062 m, and 0.131 m, respectively. The greatest difference in the lowest entire construction cost and the lowest carbon emission of external wall insulation among different typical climate regions in China was 12.987 USD/m² and 6.3 kgCO2e/m², respectively. Full article

This study examines the issue of wind power smoothing in renewable-energy-grid integration scenarios. Under the “dual-carbon” policy initiative, large-scale renewable energy integration (particularly wind power) has become a global focus. However, the intermittency and uncertainty of wind power output exacerbate grid power fluctuations, posing challenges to power system stability. Consequently, smoothing strategies for wind power energy storage systems are desperately needed to improve operational economics and grid stability. According to current research, single energy storage technologies are unable to satisfy both the system-level economic operating requirements and high-frequency power fluctuation compensation at the same time, resulting in a trade-off between economic efficiency and precision of frequency regulation. Therefore, hybrid energy storage technologies have emerged as a key research focus in wind power energy storage. This study employs the SE-SGMD method, utilizing the distinct characteristics of lithium batteries and supercapacitors to decompose frequency regulation commands into low- and high-frequency components via frequency separation strategies, thereby controlling the output of supercapacitors and lithium batteries, respectively. Additionally, the GA-GWO algorithm is applied to optimize energy-storage-system configuration, with experimental validation conducted. The theoretical contributions of this study include the following: (1) introducing the SE-SGMD frequency separation strategy into hybrid energy storage systems, overcoming the performance limitations of single energy storage devices, and (2) developing a power allocation mechanism on the basis of the inherent properties of energy storage devices. In terms of methodological innovation, the designed hybrid GA-GWO algorithm achieves a balance between optimization accuracy and efficiency. Compared to PSO-DE and GWO-PSO, the GA-GWO energy storage system demonstrates improvements of 21.10% and 17.47% in revenue, along with reductions of 6.26% and 12.57% in costs, respectively. Full article

As consumer awareness grows and regulations regarding the quality and safety of perishable goods become stricter, careful management of environmental conditions throughout the supply chain is becoming essential. Among these factors, storage temperature plays a crucial role in preserving the physicochemical characteristics of products. Therefore, an effective approach to ensure quality and safety up to the final customer is to continuously monitor the temperature within warehouses, using specific location-mapping techniques and stocking optimization methods. This study proposes a dynamic optimization model for the storage location assignment problem, integrating both temperature and humidity constraints into the placement of stock-keeping units. The model operates under a multi-period, multi-product framework and leverages real-time sensor data to account for spatial temperature stratification and environmental variability within the warehouse, contributing to the reduction in the energy consumption. Two alternative optimization strategies are explored: one focused on minimizing thermal and humidity stress, and another targeting the reduction in average storage cycle time. A detailed what-if analysis is conducted across three scenarios, varying warehouse fill rates and incoming load volumes, in order to prove the effectiveness of the proposed model in a real-data context. The results show that the approach minimizing environmental stress consistently outperforms traditional methods in quality-related metrics, maintaining superior objective function values. Full article

In the context of the evolving global energy landscape, tight gas fields have gained in-creasing significance due to their low-porosity and low-permeability reservoirs, where natural fractures play a critical role in improving permeability and enhancing storage capacity. Foreland basins, such as the Dibei area in the northern Kuqa Depression of the Tarim Basin, are typical hosts for tight gas reservoirs, but the complex fracture development induced by multiple tectonic movements restricts natural gas exploration. This study employs core observation, imaging logging analysis, and thin-section microscopy to characterize the genetic types and development features of natural fractures in the Ahe Formation. Results show that 54% of natural fractures in the Dibei area are structurally originated, predominantly high-angle and open. The highest fracture density (0.351 fractures/m), six times that of other regions, occurs in the upper horst zones. Three fracture patterns are identified, namely fault–fold, fault-related, and monocline types. Fault–fold fractures are most developed due to folding and thrusting, while monocline zones are poorly fractured. Structural fractures are best developed in horst crests with fault–fold patterns. Fracture development is jointly controlled by folds, faults, stress, and lithology, with distinct characteristics across different structural positions and lithological combinations. Clarifying the development characteristics and distribution patterns of natural fractures in the Ahe Formation of the Dibei area facilitates accurate evaluation of high-quality reservoirs, providing crucial geological basis for optimizing hydrocarbon sweet spots and refining accumulation models in the region. Full article