Search Results (165)

This study analyzes the impact of thermal and electrical storage solutions coupled with Photovoltaic (PV) and Concentrating Solar Power (CSP) plants, proposing an innovative model to test a Hybrid Energy Storage System (HESS). The work presents an innovative Mixed Integer Linear Programming (MILP) model to determine the optimal configuration and operational strategy of a HESS within a grid-connected Microgrid (MG). The research focuses on the synergistic integration of PV with Lithium-ion Electrical Energy Storage (EES) and CSP with Thermal Energy Storage (TES). The MG includes dynamic residential, commercial, and hospital loads. The MILP model is optimized over a 24 h horizon across four season-representative days, utilizing a multi-criteria objective function that balances economic performance and CO₂ emissions via a weighting factor ω ∈ [0, 1]. Three distinct CSP options such as Parabolic Trough Collectors with varying Heat Transfer Fluids (molten salt or thermal oil) and TES types (direct and indirect dual-tank, or Phase Change Material) are analyzed, each coupled with a Rankine or Organic Rankine Cycle. Key constraints address energy balances, component efficiencies, power limits, and storage dynamics. The comprehensive results identify the most suitable technology portfolio mix and optimal hour-by-hour operational rules, providing transparent decision-making criteria based on storage size, process temperatures, and specific demand profiles. Full article

Wind curtailment in Great Britain (GB) is increasing, leading to underutilisation of low-carbon energy and higher system costs. This paper develops a data-driven techno-economic framework for a hydrogen generation and storage system that converts curtailed wind energy into hydrogen. By modelling curtailment time series and electricity prices, and considering a proton exchange membrane (PEM) electrolyser-based power-to-gas system, The framework explicitly represents the operation and interaction of the PEM electrolyser, hydrogen compression, and high-pressure storage under time-varying curtailment and electricity price conditions using reconstructed GB curtailment time series. The levelised cost of hydrogen (LCOH), net present value (NPV), and delivered hydrogen volumes are evaluated. A new sizing metric, curtailment utilisation, is introduced to link curtailment availability with electrolyser and storage productivity. Using a GB curtailment dataset, two key relationships are identified. First, increasing access to low-cost curtailed energy reduces the LCOH until electrolyser utilisation saturates, beyond which additional energy purchases provide diminishing benefits. Second, hydrogen storage exhibits an economic optimum: Undersized tanks increase costs due to ramping and venting losses, whereas oversized tanks raise capital investment requirements and increase the LCOH. For the best-performing configuration, corresponding to 70.2 MWh of curtailed energy, a 2.3 MW electrolyser, and a 94 m³ high-pressure tank, the system achieves an LCOH of £3.51/kg H₂ (excluding downstream delivery) and an NPV of £2.17 M and meets 98.01% of the hydrogen demand. These results indicate that optimal system design requires not only appropriate component sizing but also explicit consideration of curtailment profiles and pricing structures. The proposed framework provides decision-grade guidance for developers and policymakers evaluating hydrogen production from wind curtailment. Future work will extend the model to hybridise with other energy storage system technologies, enable revenue stacking across multiple markets, address real-gas storage modelling, examine the sensitivity of stack degradation, and incorporate transport and delivery costs. These findings show that viable hydrogen production from curtailed wind depends on both low-cost electricity and coordinated electrolyser storage sizing under realistic curtailment conditions. The framework provides practical guidance for developers and policymakers. Full article

In the context of increasing energy demand and the global transition toward sustainable solutions, the integration of renewable energy sources into power systems is becoming a necessity. Data centers, as major energy consumers, are particularly impacted by this shift. Photovoltaic (PV) panels represent a promising alternative to conventional electricity sources due to their low environmental impact. However, their intermittent nature leads to instability in power supply, requiring efficient energy storage solutions to ensure reliability and self-sufficiency. Among the various storage technologies available, hydrogen stands out as a viable energy carrier due to its high energy density, long-term storage capability, and minimal environmental footprint. To address these challenges, a hybrid energy storage system combining hydrogen production, battery storage, and grid connection is designed in this study to enhance energy autonomy while maintaining cost efficiency. The system relies on a combination of an electrolyzer, hydrogen storage tanks, a fuel cell, and a battery to ensure a continuous and stable energy supply. A simulation-based optimization approach is conducted using Python to determine the optimal configuration of these components. The results show that a self-sufficiency rate of 95% is achieved, with a levelized cost of electricity (LCOE) of 0.47 US$/kWh, demonstrating the feasibility of the proposed system. The environmental impact is also assessed, revealing a significant reduction in carbon emissions, with 8.97 tons of CO₂ saved over the system’s 15-year lifespan, compared to the 10 tons emitted by a conventional grid-powered system over the same period. Furthermore, a detailed analysis of energy flow within the system highlights the role of each storage component in balancing supply and demand. The hybrid design leverages the advantages of both hydrogen and battery storage, where the battery is primarily used to compensate for short-term fluctuations, while hydrogen ensures long-term energy storage. The impact of different electrolyzer and fuel cell sizes on system performance is also evaluated, leading to an optimal configuration with an electrolyzer of 5 kW, a hydrogen storage capacity of 200 L at 350 bars, a fuel cell of 2 kW, and a battery of 50 kWh. Full article

To reduce renewable output volatility and improve system integration efficiency, this study constructs a coordinated wind–solar–storage–hydrogen framework. The proposed MILP model innovatively integrates electrolyzer power-dependent efficiency and start-up dynamics into a coupled capacity-sizing and dispatch framework and differs from existing MILP models in refined dynamic constraint construction, multi-energy flow coupling, and practical engineering logic constraints. Refined mathematical models are formulated for core components, including wind and photovoltaic units, battery energy storage systems (BESS), and electrolyzers with power-dependent hydrogen production efficiency and operational dynamics. The electrolyzer efficiency peak at 0.25 p.u. input power is calibrated by industrial test data, and the optimization results show strong robustness to the slight deviation of this peak point. Independent control strategies are designed for each electrolyzer, and a capacity optimization model is formulated to maximize system performance. Simulation tests using wind and solar profiles from Northwest China show that the optimized system achieves a renewable energy utilization rate of 96.7%, a BESS capacity of 7 MWh, and a hydrogen storage tank of 3500 kg. Adopting a time-of-use (TOU) electricity pricing mechanism combined with hydrogen sales significantly enhances system efficiency, while expanding power and hydrogen transmission capacities further improves renewable energy integration. These results demonstrate the practical potential of the proposed integrated system for large-scale renewable energy deployment. Full article

Mathematical and numerical models for Packed Bed Thermal Energy Storage (PBTES) systems are essential to predict the different parameters that influence their thermodynamic behavior and then optimize their performance and efficiency. In this research paper, an industrial-scale sensible thermocline Packed Bed Thermal Energy Storage system (9.17 m high and 4.72 m in diameter) was modeled and simulated during the heat charging process, based on FEM, CFD one-dimensional, and two-phase analysis. The model rigorously couples the Local Thermal Non-Equilibrium (LTNE) energy formulation with Darcy–Forchheimer hydrodynamics. The developed model was verified and validated using experimental data from the literature. The model was in close agreement with the experiment, with a global mean relative error of 3.62%. The two-dimensional velocity and temperature fields were presented to describe flow and temperature distributions in the hybrid medium (free and porous). The effect of varying flow rates (8–15 kg/s), porosities (0.35–0.55), and particle diameters (5–20 cm) on the thermal behavior of the heat storage system, temperature fields for solid and fluid, thermocline behavior, and charge efficiency were evaluated and presented. The simulation results demonstrate that the system achieves a high charge efficiency of 92.3% at a nominal charging rate of 15 kg/s. Increasing mass flow rate accelerates charging but widens the thermocline thickness and thermal stratification. Furthermore, increasing the porosity from 0.35 to 0.55 reduced charging time, decreased the temperature difference between the HTF and the storage medium by 10 °C, and increased the final heat charging efficiency by 8%. On the contrary, an increase in particle size from 5 to 20 cm leads to a slower rise in temperature within the solid phase, creating an important LTNE lag of ≈34 °C, thereby reducing the final heat charge efficiency by 16%, and prolonging the time required to charge the tank. Full article

In a solid-state hydrogen storage tank, the storage medium is most often in the form of an intermetallic alloy powder. With each cycle of hydrogen absorption/desorption, the particles swell, move, fragment, and segregate. Understanding and modeling these phenomena are essential in order to guide engineers during the tank design process. However, there are little data in the literature on the mechanical behavior of powders for storage applications. This study focuses on the flowability and compression behavior of an intermetallic powder, with the aim of analyzing particle mobility in a confined environment as well as the transmission of forces to the tank walls. In order to represent the evolution of particle size through fragmentation during cycles, five ${\mathrm{T}\mathrm{i}\mathrm{F}\mathrm{e}}_{\left(1-\mathrm{x}\right)}{\mathrm{M}\mathrm{n}}_{\mathrm{x}}\left(\mathrm{x}\approx 0.1\right)$ powders, differing in their average particle size and polydispersity, are studied. Flowability tests on Granutools^® (Awans, Belgium) instruments show that behaviors differ. Fine-grained samples exhibit rheo-thickening behavior, while coarser samples are quasi-Newtonian. These tests highlight variations in cohesion and internal friction, particularly for polydisperse samples. Stepwise cyclic compression tests (in stages 0-10-20-30 kN) were performed to study the elastic response of the powder under confinement and its ability to transfer stresses to the walls. This work highlights the impact of particle size and polydispersity on stress transfer in a confined space. This work therefore presents the mechanical effects of changes in particle size and polydispersity during absorption/desorption cycles on the overall behavior of the powder storage bed, in terms of flowability, cohesion, and stress transmission, in order to better understand, in the long term, its impact on tank deformation. Full article

Microplastic contamination in food systems has emerged as a growing concern for food safety and public health. The presence of microplastics in raw milk may represent a potential exposure pathway for both animals and humans. This study investigated the occurrence and characteristics of microplastics in raw milk collected from smallholder dairy farms in Northeastern Thailand. Hand-milked raw milk and bulk tank milk samples were obtained from ten farms and analyzed for microplastic contamination. Suspected microplastic particles were identified and quantified using stereomicroscopy and characterized according to their shape, color, and size, while polymer composition was confirmed by Fourier Transform Infrared Spectroscopy. Microplastics were detected in both hand-milked and bulk tank milk samples, with fiber-shaped particles being the most frequently observed. The majority of detected particles were 0.05–0.15 mm in size and predominantly yellow in color. Polymer analysis revealed that Polydimethylsiloxane, followed by a semi-synthetic composite of Elastane and Rayon. These findings demonstrate that microplastics can be present in raw milk produced by smallholder dairy farms, highlighting the need for improved farm management and milk-handling practices to reduce contamination risks. From a One Health perspective, reducing plastic use and enhancing hygiene during milking and milk storage may help protect animal health, food safety, and consumer well-being. Full article

Isolated microgrids with green hydrogen storage offer a promising solution for supplying electricity to remote communities where conventional grid expansion is infeasible. Designing such systems requires balancing two conflicting objectives: minimizing installation and operation costs while maximizing supply reliability. This paper proposes a multi-objective optimization methodology, based on the Non-dominated Sorting Genetic Algorithm II, to determine the optimal sizing of multiple microgrid components. This sizing explicitly addresses both the power capacities (kW) (for photovoltaic panels, wind turbines, electrolyzers, and fuel cells) and the energy storage capacities (kWh and kg) (for batteries and hydrogen tanks, respectively), aiming to generate Pareto-optimal solutions that explore this trade-off. The proposed method evaluates the trade-off by minimizing two objectives: the Net Present Value, which includes investment, replacement, and maintenance costs, and the total expected interruption hours, derived from an hourly energy balance analysis. The methodology’s effectiveness is validated using four distinct case studies. Three of these are based on real locations with specific load profiles and climate data. To test the method’s robustness, a fourth case study uses a fictitious load profile, designed with pronounced seasonal variations and a clear distinction between weekday and weekend consumption. Our results demonstrate the method’s ability to identify efficient hybrid renewable topologies combining photovoltaic and/or wind generation, batteries, and hydrogen systems (electrolyzer, storage tank, and fuel cell). The obtained cost–reliability curves provide practical decision-support tools for system planners. Full article

In this study, two types of submerged arc welding (SAW) wires were prepared—one without cerium (Ce) and another containing 0.14 wt.% Ce. Deposition experiments were carried out on corrosion-resistant crude oil storage tank steel plates using a multi-layer, multi-pass welding process. Through a combination of microstructural characterization techniques, including optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM), along with mechanical property testing, a systematic investigation was conducted to evaluate the influence of Ce on the weld metal microstructure and its impact toughness at −20 °C. The results reveal that Ce introduced via the welding wire into the weld seam refines and disperses inclusions, leading to the formation of composite inclusions primarily composed of Ce₂O₃, Ce₂O₂S, and CeS. These Ce-enriched inclusions serve as heterogeneous nucleation sites, increasing the area fraction of acicular ferrite (AF) within the weld columnar grain region from 52% to 83%, and within the heat-affected zone from 20% to 37%. Correspondingly, the proportions of blocky and polygonal ferrite decrease, while the size of martensite/austenite (M/A) constituents is reduced. The addition of Ce thus diminishes the size of hard phase inclusions and M/A constituents in the weld metal, enhancing the critical fracture stress and increasing the energy required for crack initiation. Meanwhile, the higher proportion of AF elevates the density of high-angle grain boundaries, thereby improving crack propagation resistance. These combined effects raise the −20 °C impact energy of the weld metal from 117 J to 197 J. Full article

In response to the International Maritime Organization (IMO)’s greenhouse gas reduction targets and the growing demand for decarbonization in the maritime sector, the development of hydrogen-fueled ship technologies has gained increasing attention. Liquid hydrogen (LH₂) is regarded as a promising marine fuel due to its high energy density per unit volume when liquefied at −253 °C, enabling large-scale storage and transportation. However, critical technical challenges remain in cryogenic storage, transfer, vaporization processes, and safety assurance. This study proposes a conceptual pre-standardization framework for land-based evaluation of LH₂ fuel tank and supply systems, supported by preliminary validation using LN₂ surrogate tests. The protocol is established through a reinterpretation of existing international and domestic standards (KGS AC111, ISO/TR 15916, CGA H-3) and adapted to Korean demonstration environments. Test items were categorized into (i) supply performance (flow and pressure), (ii) vaporization and heating performance (temperature), and (iii) safety functions, with acceptance criteria benchmarked against international guidelines. To overcome the significant safety and cost constraints of handling actual LH₂, liquid nitrogen (LN₂) was applied as a surrogate medium to enable preliminary validation under safe and practical conditions, and process simulations are proposed as a future pathway for comprehensive verification. The results highlight not only the application but also the localization and refinement of global standards into a practical protocol for small- to medium-sized ship applications. This protocol is expected to serve as a critical reference for subsequent sea trials and commercialization, thereby contributing to the advancement of eco-friendly marine fuel technologies and strengthening international competitiveness in the hydrogen powered shipping sector. Full article

To enhance the anti-corrosion performance of storage tanks, Ni–SiC composites were successfully fabricated on the surface of Q345 steel substrate via the ultrasonic electrodeposition technique. The influence of ultrasonic power on the surface morphology, element content, phase structure, and anti-corrosion performance of Ni–SiC composites were explored utilizing a scanning electron microscope (SEM), X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), and an electrochemical workstation, respectively. SEM images showed that the Ni–SiC composites obtained at 120 W had a flat, dense surface morphology, with a uniform distribution of SiC nanoparticles (NPs) and a refined size of nickel grains. Meanwhile, the Si content (7.3 wt.%) of Ni–SiC composites prepared at 120 W was obviously higher than those obtained at 0 W (4.8 wt.%) and 60 W (6.1 wt.%). The thicknesses and adhesion force of Ni–SiC composites manufactured at 120 W were the largest of 103.5 μm and 51.2 N, respectively. XRD patterns presented that the diffraction peaks intensity and width of Ni–SiC composites manufactured at 120 W were lower and broader than that of Ni–SiC composites manufactured at 0 W and 60 W. A corrosion test illustrated that the Ni–SiC composites prepared at 120 W had the lowest corrosion current of 3.5 × 10⁻³ mA/cm², the lowest corrosive weight loss (4.2 mg) and corrosion rate (0.06 mg/h), while the corrosion potential was the highest of −0.41 V, which demonstrated the best anti-corrosion performance. In addition, the co-deposition mechanism of SiC NPs and Ni²⁺ ions was also analyzed. Full article

The storage of different forms of energy is becoming increasingly important in the energy system sector, due to the significant fluctuations that renewable energy sources influence on urban energy systems. Nowadays, these sources have been promoted for the transition towards modern energy systems at different scales, due to their reduced emissions of greenhouse gases. Yet, many doubts remain about their efficacy in urban settlements worldwide. For this reason, to promote the fast implementation of renewable energy technologies around the world, it is of great importance to design and develop free-access and user-friendly tools to help stakeholders in the planning and management of urban energy districts. The present study has proposed an evaluation tool to model decentralised energy storage systems using Urban Building Energy Models, including an optimisation method to size the best capacity in each building of a district. The developed models simulate two storage technologies: battery power banks and heated water tanks. To present the outcomes of the tool, these models have been tested in two scenarios of Portugal, located in a densely populated area and the most isolated region of the country. Among the most important findings of the results are their ability to evaluate the performance of individual buildings by group archetype and total district metrics, using different temporal periods in a single model to identify the buildings taking most advantage of storage technologies. In addition, the optimisation algorithm efficiently estimated the ideal size of each storage technology, reducing the need of unnecessary capacity. Full article

To address the collaborative optimization challenge in multi-microgrid systems with significant renewable energy integration, this study presents a dual-layer optimization model incorporating power-hydrogen coupling. Firstly, a hydrogen energy system coupling framework including photovoltaics, storage batteries, and electrolysis hydrogen production/fuel cells was constructed at the architecture level to realize the flexible conversion of multiple energy forms. From a modeling perspective, the upper-layer optimization aims to minimize lifecycle costs by determining the optimal sizing of distributed PV systems, battery storage, hydrogen tanks, fuel cells, and electrolyzers within the microgrid. At the lower level, a distributed optimization framework facilitates energy sharing (both electrical and hydrogen-based) across microgrids. This operational layer maximizes yearly system revenue while considering all energy transactions—both inter-microgrid and grid-to-microgrid exchanges. The resulting operational boundaries feed into the upper-layer capacity optimization, with the optimal equipment configuration emerging from the iterative convergence of both layers. Finally, the actual microgrid in a certain area is taken as an example to verify the effectiveness of the proposed method. Full article

The solar thermal collector network (SCN) and the thermal energy storage system (TES) represent 90% of the solar thermal installation (STI) total costs. STI occupies 30 hectares, and any reduction is significant for the environment. The proposed approach, which includes a solar thermal plant with recirculation, a mixer, and a heat exchanger, reduces investment costs and environmental impact. It facilitates mixing in a simple tank. The developed methodology reduces the number of collectors and the size of the storage system. An industrial-powdered milk process is the case study. Two scenarios and the base case were evaluated. The four seasons and critical meteorological conditions were considered. Scenario one, without a heat exchanger, presents energy surpluses in three seasons. The second scenario, with a heat exchanger, heats the feedwater and guarantees the heat load and target temperature on critical days of the year. In this second scenario, it is possible to reduce the tank filling time from 8 to 7 h. Up to five parallels were reduced in both scenarios, with mass flow of 0.125 kg/s and up to 3.75% of the total tank volume of 52.65 m³ (mass flow 0.075 kg/s). The optimized system is cost-effective, and 10.20% of the total cost was reduced. This methodology can be applied to any low-temperature STI. Full article

With changing demands in regulation, understanding methane emissions from offshore oil and gas production infrastructure has become increasingly important. Reported emissions from facilities in the Gulf of Mexico range from zero to thousands of tons of methane per hour, but these is currently no clear understanding of how this range compares to expected emissions from normally operating facilities. To generate realistic emission estimates, we create two bottom-up models that simulate emissions from facilities operating in the Gulf of Mexico. We estimate type 1 prototypical facilities (typically unmanned, older, lower-producing platforms in shallow water with little processing equipment, compressors, or storage tanks) to emit an average of 13 kg CH₄ h⁻¹, which corresponds to a loss of 2.7% of the average facility production. Type 2 prototypical facilities (continuously manned, higher production and operate in deeper water with processing equipment, oil storage tanks, compressors and power generation) emit an average of 88 kg CH₄ h⁻¹, which corresponds to a loss of 2.5% of production. The average measured emission from type 1 facilities was 18 kg CH₄ h⁻¹ with a median production loss estimated at 8%. The average measured emission from type 2 facilities was 36 kg CH₄ h⁻¹ with a median production loss estimated at 2.4%. Using emission factors that consider the long-tail emission distribution partly reconciles the difference between modelled and measured emission estimates, but we suggest the current the fugitive emission estimate may be an underestimate and more data on the number and size of fugitive emissions could explain differences between the modelled and measured emission estimate. We suggest the bottom-up approach described here that uses production data coupled with facility equipment could be used to identify facilities that have abnormally large measured emissions, caused by methodological failure or larger than expected fugitive emissions, which should be targeted for further evaluation resulting in remeasurement or identification of source type so that a more accurate estimates can be made on the absolute emission. Full article