Search Results (6,158)

Hydrogen energy is pivotal to the global energy transition, and the development of high-efficiency, safe hydrogen storage technologies constitutes a prerequisite for its large-scale commercialization. Kinetic bottlenecks including slow reactions, delayed front propagation, and marked spatial heterogeneity driven by strong thermal–mass transfer coupling restrict the engineering application of solid-state metal hydrides. However, the current research mainly focusing on overall performance lacks a systematic understanding of the spatiotemporal evolution mechanisms and their intrinsic links to internal structural control. In this work, a 3D multiphysics model of a LaNi₅-based reactor is developed to systematically elucidate spatiotemporal evolution patterns, facilitating the proposal of a structural decoupling framework based on synergistic thermal–mass resistance reconfiguration. Both absorption and desorption show distinct three-stage evolution, shifting from kinetic dominance to transfer limitation: absorption causes core self-inhibition via heat-hydrogen supply mismatch, leading to much lower core than surface storage capacity; desorption results in significant inner-layer lag due to endothermic cooling-driven pressure drops. Thermal–mass coupling-induced inverted spatiotemporal evolution is identified as the root cause of spatial heterogeneity. Quantitative comparison of straight-pipe, spiral-tube, and honeycomb structures reveals that internal architectures achieve effective thermal–mass decoupling through expanded heat-exchange areas, reconstructed diffusion pathways, and optimized heat source distribution. Notably, the honeycomb structure with a parallel micro-unit network achieves 89.1% and 86.6% reductions in absorption and desorption times, respectively, showing superior dynamic performance and field uniformity. This study provides a theoretical basis for the mechanism-driven design and synergistic performance optimization of high-efficiency solid-state hydrogen storage reactors. Full article

The increasing number of vehicles in cities reduces the efficiency of parking infrastructure and increases traffic congestion, making it challenging to achieve sustainable transportation goals. This situation necessitates a re-evaluation of urban mobility systems in conjunction with spatial organization and digital technologies. This article examines smart parking systems as “data-oriented spaces”, analyzing their impact on urban mobility, energy efficiency and spatial organization from a multidimensional perspective. The research adopts a qualitative, multi-level approach, structured through a comprehensive literature review, a comparative analysis of five international case studies and a conceptual synthesis of the findings. The data obtained were evaluated using criteria such as technological infrastructure, spatial structure, sustainability performance and user interaction. The findings reveal that smart parking systems not only serve as vehicle storage but can also function as digital–spatial interfaces that direct urban data flows. This study presents a conceptual framework that treats smart parking systems as data-oriented architectural spaces, offering a holistic approach to the design of sustainable urban mobility infrastructures. This perspective allows for redesigning parking structures as adaptable, data-oriented architectural systems that optimize circulation patterns, reduce search-related emissions, increase spatial efficiency and support sustainable urban mobility networks. Full article

To address voltage over-limit and transformer overload issues in distribution grids caused by large-scale distributed PV integration, this paper proposes a distributed cooperative-based intelligent load optimization technique for distribution grids. First, by analyzing the limitations of traditional centralized control in communication burden, response speed, and fault tolerance, the necessity of distributed cooperative control is demonstrated. Subsequently, leveraging the bidirectional power regulation capability of energy storage systems, a distributed PV-storage system cooperative control model based on a consensus algorithm is constructed. This model comprehensively considers PV output fluctuations, energy storage state of charge, and grid regulation demands. Through multi-node information exchange and iterative updates of consensus variables, the model achieves coordinated power allocation among systems and voltage overlimit mitigation. Simulation results demonstrate that the proposed method effectively smooths PV fluctuations and alleviates local overloads in distribution grids. It simultaneously accommodates capacity differences and operational constraints across energy storage systems, enhancing system response speed and robustness. This provides effective technical support for the safe operation of distribution grids under high penetration of distributed renewable energy. Full article

In this paper, the dynamic modeling and integrated simulation of a ship microgrid system designed to enhance power quality and energy efficiency in electric propulsion vessels are proposed. The proposed system consists of a photovoltaic (PV) array, a battery energy storage system (BESS), a diesel generator, and a propulsion system, all of which are organically integrated through power conversion devices. To compensate for the intermittent nature of solar power, a control strategy featuring Maximum Power Point Tracking (MPPT) for the PV system and bidirectional DC/DC converter control for the battery was implemented. Specifically, a control logic to stabilize the system output in response to the fluctuating loads of the electric propulsion system was developed using PSCAD (v50) software. The simulation results demonstrate that the proposed control strategy maintains DC-link voltage deviation within ±1.8% and achieves a settling time of less than 0.8 s while optimizing propulsion efficiency (peak-shaving ratio 25–30%) under both constant and variable speed operating conditions. Battery SOC variation is limited to 18–88%, preventing overcharge or discharge. This research provides a foundational framework for the design of energy management systems (EMSs) and grid stability assessments for future eco-friendly electric propulsion ships. Full article

Nanoemulsions are widely recognized as versatile delivery platforms capable of stably loading lipophilic active ingredients. Although low-energy phase inversion methods enable nanoemulsion formation under ambient and low-shear conditions, their scalability and applicability in practical formulation environments remain insufficiently validated. Here, we develop oil-in-water (O/W) nanoemulsions via a low-energy phase inversion process and systematically investigate their composition-dependent formation, scalability, and formulation stability. By precisely tuning the composition of a mixed nonionic surfactant system, monodisperse nanoemulsions with an average droplet size of ~110 nm and a polydispersity index (PDI ≤ 0.20) are reproducibly obtained under ambient, low-shear conditions. The optimized nanoemulsions maintain their nanoscale dispersion characteristics over 30 days of storage and exhibit consistent droplet size and distribution upon scale-up to 1 L. Furthermore, the nanoemulsions retain structural stability when incorporated into polymer-based formulations under various temperature conditions and repeated thermal cycling. These results demonstrate that low-energy phase inversion enables a scalable and formulation-compatible nanoemulsion platform, providing practical guidelines for industrial formulation and manufacturing of delivery systems for lipophilic active ingredients. Full article

In recent decades, microalgae biodiesel has been repeatedly presented as a fundamental pillar of future bioenergy systems in relation to fossil diesel. This is largely due to the high photosynthetic efficiency of microalgae, their high growth rates, and their ability to accumulate neutral lipids—particularly triacylglycerols (TAGs)—which constitute the main raw materials for biodiesel production. However, this route has not yet become economically competitive with conventional fuels and vegetable oils. In this context, the simultaneous increase in biomass productivity and TAG content remains essential to reduce the cost difference, but achieving these goals depends on a detailed understanding of lipid metabolism and its regulation under different environmental and nutritional conditions—and on overcoming the intrinsic trade-offs between growth and storage. Thus, this article aims to critically analyze the viability of microalgae biodiesel, seeking to identify the main factors that explain why this route has not yet become competitive with conventional fuels after decades of research. In parallel, the growing trend of multi-product microalgae biorefineries is examined, highlighting bottlenecks in downstream processing and product purification, as well as the inherent trade-offs between production strategies. Practical limitations related to biomass productivity per area, culture dilution, intracellular lipid storage, and vital steps such as transesterification are also discussed, which together impose high energy and operational penalties throughout the production chain. Finally, emerging trends and integrated approaches are discussed, with emphasis on strain and process co-optimization, as well as greater integration between cultivation and downstream operations, aiming to enable more efficient and realistically consistent microalgae biodiesel concepts. Full article

The increasing penetration of intermittent renewable energy demands innovative solutions to maintain grid stability, resilience, and security in the body of smart cities. This paper presents a novel framework that redefines Bitcoin mining as a form of virtual energy storage, a flexible and controllable load capable of delivering large-scale demand response services, positioning it as a competitive alternative to traditional energy storage systems, including electrical, mechanical, thermal, chemical, and electrochemical storage solutions. By strategically aligning mining activities with grid conditions, Bitcoin mining can absorb excess electricity during periods of oversupply, converting it into digital assets, and reduce operations during times of scarcity, effectively emulating the behavior of conventional energy storage systems without the associated capital expenditures and material requirements. Beyond its operational flexibility, this paper explores the cyber–physical benefits of integrating Bitcoin mining into the power transmission systems as a defensive mechanism against false data injection (FDI) cyberattacks in smart city infrastructure. To achieve this goal, a decentralized and adaptive control strategy is proposed, in which mining loads dynamically adjust based on authenticated grid-state information, thereby improving system observability and hindering adversarial efforts to disrupt state estimation. In addition, to handle the proposed approach, this paper introduces a high-performance algorithm, a combination of quantum-augmented particle swarm optimization and wavelet-oriented whale optimization (QAPSO-WOWO). Simulation results confirm that strategic deployment of mining loads improves grid sustainability by utilizing curtailed renewables, enhances resilience by mitigating load-generation imbalances, and bolsters cybersecurity by reducing the impacts of FDI attacks. This work lays the foundation for a transdisciplinary paradigm shift, positioning Bitcoin mining not as a passive energy consumer but as an active participant in securing and stabilizing the future power grid in smart cities. Full article

With the rapid development of smart cities, coordinating diverse distributed energy resources through storage-centric shared management has become a critical challenge. This paper proposes a bi-level energy management framework to support peer-to-peer energy trading among multiple virtual power plants (VPPs) under multidimensional uncertainties. The interaction is modeled as a Stackelberg–Nash equilibrium framework, in which OK, we will make the necessary revisions as per the requirements.a public energy storage operator and a natural gas company act as leaders to maximize social welfare and design differentiated trading strategies for VPPs. The VPPs act as followers and participate in cooperative energy trading based on a generalized Nash equilibrium scheme, sharing surplus energy and allocating cooperative benefits according to their contributions. To address uncertainty, Conditional Value at Risk (CVaR) is adopted to quantify the expected loss of the upper-level decision makers. The lower-level VPP problem is formulated as a three-stage stochastic robust optimization model considering renewable generation uncertainty. To solve the resulting nonlinear bi-level problem, a two-stage solution approach combining particle swarm optimization and KKT-based reformulation is developed to transform it into a tractable mixed-integer linear programming model. Numerical case studies verify the effectiveness of the proposed framework. Full article

‘Mollar de Elche’ pomegranate is highly valued for its sweet flavor but faces significant commercial hurdles due to pale coloration and sensitivity to postharvest disorders. This study investigates the impact of preharvest foliar applications of L-α-amino acids, applied alone (AA) or combined with 2.5% sorbitol (Sor–AA), on secondary metabolism and physiological resilience, defined here as the fruit’s capacity to maintain metabolic homeostasis and stabilize antioxidant pigments during cold storage (7 °C). Our results show that both treatments triggered a substantial shift in secondary metabolism, doubling anthocyanin concentrations at harvest and effectively overcoming the cultivar’s color deficit. While the AA treatment maximized fruit quantity per tree, the Sor–AA combination achieved the highest total yield (83.58 ± 6.82 kg) and individual fruit weight (469.00 ± 16.00 g) through a ‘metabolic bypass’ that optimizes energy use. Crucially, the physiological resilience of the fruit was uniquely bolstered by the Sor–AA treatment, which was the only strategy to stabilize anthocyanin levels (~108 mg L⁻¹) and maximize free ellagic acid in the husk (371.72 mg kg⁻¹) throughout 42 days of storage. Multivariate PCA (explaining 79.79% of variance) confirmed that the synergy of amino acids and sorbitol triggers systemic metabolic reprogramming. Consequently, this targeted agronomic approach could provide significant economic benefits by increasing the proportion of export-grade fruit and extending the commercial window for the pomegranate sector. Full article

Many countries rely on coal for energy security during renewable transitions. This study conducts a technical, economic, and environmental analysis of hybridizing a supercritical coal-fired power unit with photovoltaics (PV) to create a sustainable hybrid system at a plant in Silesian Voivodeship, Poland. The goal is to assess costs and optimal operating conditions for a coal–PV hybrid under varying scenarios, using a decision-support model that integrates fuel prices, CO₂ emission charges (EUA), and technical parameters. Two main scenarios are modeled. In auxiliary-only PV (112 MW system), real-time power supplies pumps and fans, cutting coal consumption without storage; LCOE decreases with annual hours (2800–7000), outperforming conventional coal across EUA prices (20–50 EUR/t). In PV surplus export, excess generation (1300 h/year) is grid-fed for revenue, amplifying LCOE reductions—hybrid superiority emerges above 34 EUR/t EUA, per equivalence thresholds. Results show coal electricity exceeds low-emission costs above 34 EUR/t CO₂, with maximum disparity at 50 EUR/Mg. The hybrid leverages existing infrastructure, mitigates solar intermittency via auxiliary supply, ensures baseload continuity, boosts flexibility, and prolongs asset life—reducing >123,000 EUA/year at 145,000 MWh PV output. This sustainable hybrid promotes energy transition, reduces fossil fuel dependence, and aligns with global sustainability goals. Full article

Phase-change materials (PCMs), such as paraffin wax, are widely used in latent heat storage (LHS) because they store substantial thermal energy at nearly constant temperature; however, their low thermal conductivity limits heat transfer and slows melting/solidification. In this work, two flat-plate solar collectors are coupled with a paraffin-based LHS unit for low-temperature solar heating, and the design is optimized by introducing improved fin-geometry combinations on both the heat transfer fluid (HTF) tube and shell side. The M-shaped fins combined with rectangular fins significantly enhanced convective heat transfer by generating localized vortices, while the extended surface area improved conduction within the solid PCM, facilitating efficient heat dissipation and accelerating the phase transition. The LHS unit without fins showed complete melting in 67 min. However, fin introduction remarkably mitigated charging duration to 44 min, 52.3% faster than bare tubes having no fins. The experimental melting process exhibited a 7 min delay by comparing experimental and numerical results, achieving complete melting in 51 and 44 min, respectively. Discharging was completed in 48 min. During PCM charging, sensible heating produces a rapid temperature rise with only a small energy increase, but once the PCM entered into the melting range (320–324 K), the energy changed more steeply. Adding fins boosts stored energy from 2.10 MJ to 3.25 MJ (54.8%) and exergy from 0.15 MJ to 0.27 MJ (80.0%), yet exergy remains far smaller than energy (92.9% lower without fins and 91.7% lower with fins), indicating fins enhance total heat storage more than recoverable work potential. Full article

The transition of modern power systems is going through the challenges of uncertainties originating from equipment unavailability, forecasting errors, market fluctuations, prosumer behaviors, regulatory and policy changes, and extreme weather conditions. These uncertainties can cause deviations from the planned operating points leading to non-optimal and even infeasible operation conditions. Energy storage systems (ESSs) can address these challenges in active distribution networks by compensating deviations caused by uncertainties. Consequently, aggregating distributed energy resources (DERs) and ESSs in active distribution networks is a key research area. This paper first introduces these uncertainties and their imposed challenges on aggregated systems. Moreover, correlations and interdependencies among uncertainties and their impacts on aggregating DERs and ESSs are thoroughly investigated. Subsequently, a critical review of the state-of-the-art aggregation optimization approaches is presented, and the comparison is made between static and dynamic DER-ESS aggregation processes. Next, the practical requirements and applications of DER-ESS aggregation are investigated. Finally, conclusions and future research directions in the area of DER-ESS aggregation are presented. Full article

Carnot batteries based on the coupling of high-temperature heat pumps (HTHPs) and Organic Rankine Cycles (ORCs) emerge as promising solutions for large-scale and long-duration energy storage, enabling sector coupling and the valorization of industrial waste heat. In such systems, the charging subsystem plays a dominant role, as variations in heat pump performance influence the round-trip efficiency more strongly than comparable variations in the ORC. This work presents a thermodynamic assessment of Rankine-based HP–ORC Carnot batteries focusing on the influence of heat pump configuration and working fluid selection. System performance is evaluated using the heat pump coefficient of performance, volumetric heat capacity, ORC efficiency, and Carnot battery round-trip efficiency through a grid-search optimization over a wide range of storage outlet and waste heat source temperatures. The results show that single-stage configurations are optimal at low to moderate temperature lifts, while two-stage and cascade systems become advantageous at higher lifts. Among the investigated fluids, R-601 provides the highest round-trip efficiencies at elevated storage temperatures, whereas R-600 enables more compact systems due to its higher volumetric heat capacity. These findings provide design guidance for selecting heat pump configurations and working fluids in industrial waste-heat-assisted Carnot battery applications. Full article

Aqueous zinc-ion batteries (AZIBs) are promising for large-scale grid storage due to inherent safety, low cost, environmental compatibility, high theoretical capacity (820 mAhg⁻¹), and suitable redox potential (−0.763 V vs. SHE). However, practical deployment is hindered by coupled challenges at the zinc anode–hydrogen evolution, dendrite growth, and corrosion/passivation, which severely limit cycle life and coulombic efficiency. This review systematically summarizes key advances in AZIB research. It first elucidates working principles and four cathode energy storage mechanisms: Zn²⁺ insertion/extraction, H⁺/Zn²⁺ co-insertion, chemical conversion, and dissolution/deposition. Second, it examines four mainstream cathodes (manganese-based, vanadium-based, Prussian blue analogs, and organic compounds), analyzing performance bottlenecks and corresponding optimization via structural modification. Third, it explores functional mechanisms of advanced separators (polymer, inorganic/ceramic composite, MOF-based, and cellulose-based) in regulating uniform Zn²⁺ deposition and suppressing dendrites. Fourth, it summarizes anode optimization strategies: artificial protective layers for interface stabilization, electrolyte additives to modulate Zn²⁺ solvation/deposition, and 3D porous structures to reduce local current density and provide nucleation sites. Finally, key scientific challenges and future directions are discussed—multi-strategy synergy, in situ characterization, practical battery construction, and sustainable technological development, offering theoretical guidance for advancing AZIBs toward large-scale applications. This review aims to provide a comprehensive perspective spanning from materials to systems, and from mechanisms to applications. Its core objective is not merely to list the types of cathode materials, but to establish a logical bridge directly connecting “key challenges” to “optimization strategies,” with a particular emphasis on the issues and solutions related to the cathode side. Full article

Autonomous mobile robots are transforming industries from e-commerce logistics to field exploration, but their effectiveness depends on onboard energy storage. This study addresses the challenge of selecting optimal battery technologies for autonomous mobile robots, balancing performance, energy efficiency, thermal stability, and cost across diverse applications. We focus on lithium-ion, lithium-polymer, and nickel-metal hydride batteries, the most common power solutions, each with distinct advantages and disadvantages in energy density, form factor, thermal stability, and cost. A dynamic modeling and simulation framework in MapleSim evaluated these chemistries under defined and representative operating conditions, tracking state of charge and temperature during charging and discharging. A Particle Swarm Optimization algorithm evaluated 37 battery configurations by thermal stability, energy efficiency, and cost across five use cases. Key results indicate that for logistics and warehousing, lithium nickel manganese cobalt oxide with graphite is optimal; for healthcare, lithium nickel manganese cobalt oxide with lithium titanate oxide excels; for manufacturing, lithium nickel cobalt aluminum oxide with graphite leads; for agricultural robots, lithium manganese oxide with graphite is best; and for exploration and mining, lithium iron phosphate with graphite is most reliable. These results provide a structured basis for battery selection, showing how simulation-driven, multi-criteria decision-making enhances energy management and operational reliability. Full article