Storage Array Research Articles

MIL-88-derived porous carbon rod-supported FePS3 nanosheet arrays for robust sodium storage

Ternary metal phosphorus trisulfide (MPS3) has emerged as an excellent candidate for use as an anode in sodium-ion batteries, characterized by its unique layered structure, easily tunable physicochemical properties, and high theoretical capacity. However, its intrinsic challenges such as low electrical conductivity and susceptibility to fragmentation have led to unsatisfactory rate and cyclic capability. Herein, the intriguing microcomposite structure of porous carbon rod-supported FePS3 nanosheet arrays (FePS3@CR) is ingeniously constructed in situ via the phospho‑sulfurization of MIL-88. FePS3@CR showcases multiple structural advantages, including enhanced electrical conductivity, increased surface area, accelerated electron transfer rate, and mitigated structural stress. These combined benefits endow FePS3@CR with improved rate capability (808.0 and 474.3 mAh g−1 at 0.1 and 10 A g−1, respectively) and cyclic life (94.5 % retention after 1500 loops at 2 A g−1). The assembled full battery also demonstrates robust cycling stability, retaining 94.2 % of its capacity after 1100 loops at 0.5 A g−1. The specific sodium storage process of the FePS3 electrode is investigated through ex-situ structure analysis. This work presents innovative structural designs potentially improving the energy storage performance of MPS3 material system.

Research on Energy Management Technology of Photovoltaic-FESS-EV Load Microgrid System

This study focuses on the development and implementation of coordinated control and energy management strategies for a photovoltaic–flywheel energy storage system (PV-FESS)-electric vehicle (EV) load microgrid with direct current (DC). A comprehensive PV-FESS microgrid system is constructed, comprising PV power generation, a flywheel energy storage array, and electric vehicle loads. The research delves into the control strategies for each subsystem within the microgrid, investigating both steady-state operations and transitions between different states. A novel energy management strategy, centered on event-driven mode switching, is proposed to ensure the coordinated control and stable operation of the entire system. Based on the simulation results, the PV system cannot cope with the load demand power when it is increased to a maximum of 2800 W, the effectiveness of the individual control strategies, the coordinated control of the subsystems, and the overall energy management approach are confirmed. The main contribution of this research is the development of a coordinated control mechanism that integrates PV generation with FESS and EV loads, ensuring synchronized operation and enhanced stability of the microgrid. This work provides significant insights into optimizing energy distribution and minimizing losses within microgrid systems, thereby advancing the field of energy management in DC microgrids.

Short-cycle borehole thermal energy storage: Impact of thermal cycle duration on overall performance

Borehole thermal energy storage arrays are a common form of seasonal underground energy storage which relies on the thermal mass of subsurface rock or sediment to store hot or cold thermal energy. However in practice, typical seasonal operation seldom leads to cyclic energy recovery factors greater than 50%–60% due to significant thermal losses during prolonged periods between consecutive charges. In this paper, the impact of short cycle operation (down to a few days) on energy recovery and overall performance is investigated. Analytical and numerical models are used to estimate energy recovery as a function of cycle length for a typical array and for two distinct charging and discharging scenarios (constant temperature or thermal charge load), which is novel and has not been done before. The results show that shorter cycle duration yields increased recovery factors and storage capacity, which is ascribed to a greater rate of charge to rate of thermal loss ratio. In particular, short-cycle operation at the scale of days unlocks recovery factors in excess of 85 %. The results, supported by a numerical subsurface analysis of the temperature distribution, also show that the recovery efficiency increases with time as losses approach, but never fully reach, a steady-state.

Energy management strategy and operation strategy of hybrid energy storage system to improve AGC performance of thermal power units

With the continuous increase of the renewable energy power generation penetration, the intermittency and fluctuation of renewable energy power generation make the traditional thermal power units (TPU) which play the main role of regulation need to undertake more frequent and more severe regulation tasks. In order to improve the automatic generation control (AGC) command response capability of TPU, an operation strategy of hybrid energy storage system (HESS) is proposed in this paper. While assisting TPU to complete the regulation tasks, it gives full play to the advantages of power-type and energy-type energy storage. Moreover, an energy management strategy of energy storage array (ESA) is proposed to improve the overall operation efficiency of ESA while making the state of charge (SOC) of all energy storage subunits consistent. Finally, the effectiveness of the proposed strategy is verified by simulation experiments. The results show that after using HESS to assist TPU operation, the comprehensive regulation performance index of TPU increased from 4.0198 to 7.8112, which significantly improved the operational flexibility of TPU. Meanwhile, the strategy proposed in this paper makes different types of energy storage systems in HESS operate in a relatively healthy SOC range, and the SOC of the flywheel energy storage system (FESS) reaches the limitation value decrease from 6 times to once, ensuring the overall charge and discharge capacity of HESS.

Adaptive VSG control of flywheel energy storage array for frequency support in microgrids

The application of virtual synchronous generator (VSG) control in flywheel energy storage systems (FESS) is an effective solution for addressing the challenges related to reduced inertia and inadequate power supply in microgrids. Considering the significant variations among individual units within a flywheel array and the poor frequency regulation performance under conventional control approaches, this paper proposes an adaptive VSG control strategy for a flywheel energy storage array (FESA). First, by leveraging the FESA model, a variable acceleration factor is integrated into the speed-balance control strategy to effectively achieve better state of charge (SOC) equalization across units. Furthermore, energy control with a dead zone is introduced to prevent SOC of the FESA from exceeding the limit. The dead zone parameter is designed based on the SOC warning intervals of the flywheel array to mitigate its impact on regular operation. In addition, VSG technology is applied for the grid-connected control of the FESA, and the damping characteristic of the VSG is decoupled from the primary frequency regulation through power differential feedback. This ensures optimal dynamic performance while reducing the need for frequent involvement in frequency regulation. Subsequently, a parameter design method is developed through a small-signal stability analysis. Consequently, considering the SOC of the FESA, an adaptive control strategy for the inertia damping and the P/ω droop coefficient of the VSG control is proposed to optimize the grid support services of the FESA. Finally, the effectiveness of the proposed control methods is demonstrated through electromagnetic transient simulations using MATLAB/Simulink.

Research on the strategy for average consensus control of flywheel energy storage array system based on lifecycle

In the domain of clean energy, the flywheel energy storage array system (FESAS) is widely employed for efficient and renewable energy storage to stabilize power grids and smooth power variations. However, managing the lifecycle of FESAS and achieving coordinated control presents a considerable challenge. This study integrates a lifecycle parameter based on the average consensus algorithm, enabling flywheels with longer lifecycles to handle additional charging and discharging tasks, while those with shorter lifecycles participate less. This approach effectively balances flywheel lifecycles and extends the overall lifespan of FESAS. Experimental findings reveal that when the P matrix satisfies the condition of equal row sums or column sums, the power distribution parameters tend toward average consensus, enabling FESAS to efficiently smooth unbalanced power. In undirected graphs, the symmetry of the P matrix causes the auxiliary variables to tend toward average consensus, effectively suppressing unbalanced power. For directed unbalanced graphs, this study proposes Error Balancing Iterative Algorithm (EBTA) to construct a doubly stochastic matrix P, facilitating the convergence of auxiliary variables to average consensus and effectively suppressing unbalanced power. The experimental results validate the efficacy of our proposed approach. This research establishes a theoretical foundation for the intelligent coordinated control of FESAS, highlighting the pivotal role of lifecycle parameters, and offers valuable insights for enhancing the performance and lifespan of FESAS.

Phosphorization Engineering of CoP/NiCoP Nanoneedle Arrays for Energy Storage

Phosphorization Engineering of CoP/NiCoP Nanoneedle Arrays for Energy Storage

A hybrid energy storage array group control strategy for wind power smoothing

AbstractWith the increase of wind power generation, the safety and economy of power system operations are greatly influenced by the intermittency and fluctuation of wind power. To take the advantage of the complementary characteristics between different energy storage devices, a Hybrid Energy Storage System (HESS) consisting of Battery Energy Storage System (BESS) and Flywheel Energy Storage System (FESS) can alleviate the uncertainty of wind power. This article has proposed a coordinated control strategy through group consensus algorithm based on Model Predictive Control (MPC) for Hybrid Energy Storage Array (HESA) to smooth wind power fluctuations. To allocate power commands to the FESS and BESS, the fluctuation of wind power output is extracted with different frequency domain characteristics as instructions by Empirical Mode Decomposition (EMD) technology. Moreover, a group consensus algorithm based on MPC is proposed to complete the adaptive power allocation of energy storage units. Eventually, the actual wind farm data is used for the simulation to verify the effect of control strategy proposed in this paper. It can be seen that the developed group consensus algorithm based on MPC can cope with different frequency power commands, avoid overcharging and discharging of energy storage media, and smooth wind power effectively.

Stress factors affecting protein stability during the fabrication and storage of dissolvable microneedles

Abstract Objectives The current review summarizes product and process attributes that were reported to influence protein integrity during manufacturing and storage of dissolvable microneedle arrays. It also discusses challenges in employing established protein characterization methods in dissolvable microneedle formulations. Methods Studies on dissolvable microneedles loaded with protein therapeutics that assess protein stability during or after fabrication and storage were collected. Publications addressing other types of microneedles, such as coated and vaccine-loaded microneedles, are also discussed as they face similar stability challenges. Key findings To date, various researchers have successfully incorporated proteins in dissolvable microneedles, but few publications explicitly investigated the impact of formulation and process parameters on protein stability. However, protein therapeutics are exposed to multiple thermal, physical, and chemical stressors during the fabrication and storage of microneedles. These stressors include increased temperature, shear and interfacial stress, transition to the solid state during drying, interaction with excipients, and suboptimal pH environments. While analytical methods are essential for monitoring protein integrity during manufacturing and storage, the performance of some well-established protein characterization techniques can be undermined by polymer excipients commonly employed in dissolvable microneedle formulations. Conclusions It is essential to understand the impact of key process and formulation parameters on the stability of protein therapeutics to facilitate their safe and effective administration by dissolvable microneedles.

Reactive P and S co-doped porous hollow nanotube arrays for high performance chloride ion storage

Developing stable, high-performance chloride-ion storage electrodes is essential for energy storage and water purification application. Herein, a P, S co-doped porous hollow nanotube array, with a free ion diffusion pathway and highly active adsorption sites, on carbon felt electrodes (CoNiPS@CF) is reported. Due to the porous hollow nanotube structure and synergistic effect of P, S co-doped, the CoNiPS@CF based capacitive deionization (CDI) system exhibits high desalination capacity (76.1 mgCl– g–1), fast desalination rate (6.33 mgCl– g–1 min–1) and good cycling stability (capacity retention rate of > 90%), which compares favorably to the state-of-the-art electrodes. The porous hollow nanotube structure enables fast ion diffusion kinetics due to the swift ion transport inside the electrode and the presence of a large number of reactive sites. The introduction of S element also reduces the passivation layer on the surface of CoNiP and lowers the adsorption energy for Cl– capture, thereby improving the electrode conductivity and surface electrochemical activity, and further accelerating the adsorption kinetics. Our results offer a powerful strategy to improve the reactivity and stability of transition metal phosphides for chloride capture, and to improve the efficiency of electrochemical dechlorination technologies.

Temperature- and variability-aware compact modeling of ferroelectric FDSOI FET for memory and emerging applications

In this paper, we present a temperature and variability-aware Verilog-A-based compact model for simulating Ferroelectric FET. The model captures the rich physics of ferroelectric materials and the important electrical characteristics, such as the history effect, the impact of pulse width and amplitude on threshold voltage, and temperature-dependent degradation of polarization. The impact of variability is also explored regarding reliable operation of the FeFET. The developed model is robust and can accurately capture the experimentally observed trends, such as the change in polarization due to temperature, increased memory window on reading from the back-gate, etc. Further, we discuss two applications of our developed model viz. (a) multi-level-cell storage and (b) FeFET-based array for MAC operations. The designs are tested using the proposed model in commercial SPICE simulator at different temperatures including the effect of variation. Analysis presented in this article reveals that variability and temperature can be detrimental for operation of FeFET-based systems.

Assessing the impact of copper wools on a phase change material-based TES tank prototype

Phase Change Materials (PCMs) stand out as a promising solution within the current array of Thermal Energy Storage (TES) technologies, thanks to their superior energy storage capacities (compared to sensible solutions) and technological readiness. Nonetheless, the limited thermal conductivity of these materials may lead to incomplete phase transitions during use, resulting in a decrease in their effective energy storage capabilities. The major solutions to mitigate this issue that are present in literature either require a significant modification in the heat exchanger design (e.g. by fins) or are costly and still lack robustness and reliability (e.g. by additivities). In this study, the use of copper wools is proposed as fillers within a PCM-based heat exchanger prototype, and the assessment of its impact on the heat transfer behaviour of the material is evaluated by performing charging and discharging processes. This type of inclusion was chosen as it is relatively cheap, it can be implemented within an already existing heat exchanger, and it does not suffer from segregation. Two different wools were tested in two configurations, thus resulting in five test cases (four containing the wools and one containing solely PCM). The promising results, especially the remarkable decrease in the time needed for the complete solidification of the PCM within the tank (up to 67%), open the opportunity to additional numerical analyses regarding different configurations and/or materials, thus possibly targeting further optimizations in terms of the specific energy density and the specific power density.

Control of DFIG-based microgrid and seamless transition from stator connected and disconnected modes

This study aims to ameliorate the contribution capability of doubly-fed induction generator (DFIG) to participate in standalone microgrid operation. The islanded microgrid consists of a solar photovoltaic array for solar energy conversion and battery energy storage in addition to DFIG-based wind energy conversion system. Using a simplified control approach, the study describes multi-mode operation of a DFIG-based AC/DC microgrid using a stator-side solid-state transition switch (SSTS). Using SSTS operation, the DFIG stator can be seamlessly disconnected and reconnected from the point of common coupling without interrupting power to the loads in the microgrid. Additionally, non-ideal AC loads can be handled efficiently without the need for computationally exhaustive approaches to enhance stator voltages and currents.

Engineering Heterostructured Fe-Co-P Arrays for Robust Sodium Storage.

Transition metal phosphides attract extensive concerns thanks to their high theoretical capacity in sodium ion batteries (SIBs). Nevertheless, the substantial volume fluctuation of metal phosphides during cycling leads to severe capacity decay, which largely hinders their large-scale deployment. In this regard, heterostructured Fe-Co-P (FeP/Co2P) arrays are firstly constructed in this work for SIBs. The novel self-supported construction without insulated binders favors fast charge migration and Na+ ion diffusion. In addition, the special heterostructure with abundant heterointerfaces could considerably mitigate the volume change during (de)sodiation and provide increased active sites for Na+ ions. Density functional theoretical (DFT) calculations confirm the built-in electric field in the heterointerfaces, which greatly hastens charge transfer and Na+ ion transportation, thereafter bringing about enhanced electrochemical performance. Most importantly, the FeP/Co2P heterostructure discloses higher electrical conductivity than that of bare FeP and Co2P based on the theoretical calculations. As anticipated, the heterostructured Fe-Co-P arrays demonstrate superior performance to that of Fe-P or Co-P anode, delivering high reversible capacities of 634 mAh g-1 at 0.2 A g-1 and 239 mAh g-1 at 1 A g-1 after 300 cycles.

Driving Sustainable Energy Dispatch for Remote Communities Using Levy Flight Salp Swarm Algorithm

This study evaluates three energy dispatch algorithms to find the best way to improve hybrid energy systems in rural areas: load following (LF), cycle charging (CC), and a novel customized strategy (CS). The study examined solar and wind resources as well as projected patterns of energy consumption with a particular focus on Bambur village in Taraba State, Nigeria. The Levy Flight Salp Swarm Algorithm (LFSSA) was used in the study to assess system configurations for each method, accounting for battery storage, wind turbines, diesel generators, and photovoltaic (PV) arrays. The most cost-effective and efficient approach was determined to be the Customized Strategy (CS), which produced the lowest Net Present Cost (NPC) of 0.119/kWh. The Load Following (LF) technique had the highest costs at 0.134/kWh, while the Cycle Charging (CC) method had intermediate costs with an NPC of 0.127/kWh. With a 580-kWh battery bank, a 10 kW wind turbine, 332 kW of PV capacity, and a 78 kW diesel generator, the CS approach showed better component sizing balance. The trade-offs between energy output, storage, and backup power in real-time were optimized using this design. Sensitivity analysis revealed that increasing interest rates from 10% to 18% led to a rise in LCOE, while diesel cost fluctuations showed a non-monotonic impact on LCOE, peaking at $0.79/L before declining due to increased reliance on renewable sources and storage. CS strategy’s balance of investment and efficiency makes it ideal for remote energy management, offering key insights for rural electrification.

High-efficiency activated phosphorus-doped Ni2S3/Co3S4/ZnS nanowire/nanosheet arrays for energy storage of supercapacitors

Transition metal sulfides (TMS) have been considered as a promising group of electrode materials for supercapacitors as a result of their strong redox activity, but high volumetric strain of the materials during electrochemical reactions causes rapid structural collapse and severe capacity loss. Herein, we have synthesized phosphorus-doped (P-doped) Ni2S3/Co3S4/ZnS battery-type nanowire/nanosheet arrays as an advanced cathode for supercapacitor through a two-step process of hydrothermal and annealing treatments. The material has a one-dimensional nanowire/two-dimensional nanosheet-like coexisting microscopic morphology, which facilitates the exposure of abundant active centers and promotes the transport and migration of ions in the electrolyte, while the doping of P significantly enhances the conductivity of the electrode material. Simultaneously, the element phosphorus with similar atomic radii and electronegativity to sulfur may act as electron donors to regulate the electron distribution, thus providing more effective electrochemically active sites. In gratitude to the synergistic effect of microstructure optimization and electronic structure regulation induced by the doing of P, the P-Ni2S3/Co3S4/ZnS nanoarrays provide a superior capacity of 2716 F g−1 at 1 A/g, while the assembled P-Ni2S3/Co3S4/ZnS//AC asymmetric supercapacitor exhibits a high energy density of 48.2 Wh kg−1 at a power density of 800 W kg−1 with the capacity retention of 89 % after 9000 cycles. This work reveals a possible method for developing high-performance transition metal sulfide-based battery-like electrode materials for supercapacitors through microstructure optimization and electronic structure regulation.

Rich-grain-boundary Ni–Co–Se nanowire arrays for fast charge storage in alkaline electrolyte

In this work, the one-dimensional (1D) Ni–Co–Se nanowire arrays with rich grain-boundaries were prepared through the solvothermal method and gas-phase selenizaiton. The results showed that the structure and crystallization of the Ni–Co–Se nanowire arrays could be modulated through the optimization of selenizaiton time. The optimal Ni–Co–Se electrode sample displayed an area specific capacitance of 242.6 μAh cm−2 at 30 mA cm−2 with a current retention rate of 68.34%. The assembled Ni–Co–Se/Active carbon (AC) electrode-based asymmetric supercapacitor (ASC) showed the area specific capacitances of 329.2 μAh cm−2 and 225.8 μAh cm−2 at 3 mA cm−2 and 30 mA cm−2, respectively. A 73.33% retention rate of capacitance was observed after 8000 charge/discharge cycles. Besides, the further fabricated all-solid ASC delivered the power densities of 342.94 W kg−1 and 3441.33 W kg−1 at the energy densities of 37.62 Wh kg−1 and 25.81 Wh kg−1, respectively. Those results suggested the potentials of the obtained Ni–Co–Se nanowire arrays as electrode material for the high-performance pseudocapacitors.

Some studies on functional behavior of novel multi-layered material for integrated structural application

Fused deposition modeling (FDM) is a prominent technique in additive manufacturing (AM), widely employed for the construction of intricate prototypes through successive layer-by-layer deposition. Among the thermoplastic matrices used, polylactic acid (PLA) stands out as an environmentally friendly and hydrophobic polymer derived from organic sources. PLA boasts properties like biocompatibility, biodegradability, and high strength, making it a favored choice in diverse industries, including medical, food packaging, and textiles. The incorporation of wood flour into the thermoplastic matrix, referred to as Wood-PLA, has demonstrated increased material strength, leading to its adoption in sectors like automobile and aircraft interiors, fencing, flooring, musical equipment, and various other consumer goods. Additionally, the introduction of multi-material, an innovative material with varying multi-phase properties across different structural regions, has found application in a wide array of industries, including biomedical, energy storage, optoelectronics, aerospace, automobile, and defense. This study aims to investigate the impact of different build orientations (0˚, 45˚, and 90˚) on the mechanical properties of Wood-PLA, pure PLA, and multi-layered material (MLM) fabricated through FDM. Finite element analysis of tensile and compressive test has performed using ABAQUS software and compared with experimental outcomes. Additionally, fracture morphology are examined to gain insights into the modes of failure during fracture. Results reveal significant variations in the mechanical properties of Wood-PLA, PLA and MLM, depending on the build orientation. Furthermore, the examination of fracture morphology provides valuable insights into the failure mechanisms in these materials. Hence this study contributes to the growing body of research on advanced materials and additive manufacturing techniques, paving the way for improved material selection and design considerations.

Characterization of Single Event Effect in a Radiation Hardened Programmable Read-Only Memory in a 130 nm Bulk CMOS Technology

The concept of memory that can only be read but cannot be changed seems strange at first. In reality, it is found that it has great application potential, such as the processor with a fixed purpose, the initial set value of the microprocessor BIOS, and these data are stored in Programmable Read-Only Memory (PROM) to quickly realize system functions. The PROM storage content is fixed, greatly simplifying his design. The radiation of space particles is the main factor causing the failure of the electronic system of spacecraft. The PROM storage array of the space electronic system is the most basic guarantee for the normal operation of the electronic system. The chip adopts domestic 130 nm standard technology of Complementary Metal Oxide Semiconductor (CMOS), Muller-C digital filter is used in the peripheral subsystem of PROM storage array, and the core cell uses Dual Interlocked Cell (DICE) and ring gate and other radiation hardening technologies to design a 32Kx8bit radiation resistant asynchronous programmable PROM. Pre-silicon of devices was verified by Technology Computer Aided Design (TCAD), and post silicon radiation verification was completed through radiation experiment. The post silicon radiation experiment showed that the total ionizing Dose (TID) capacity of the PROM chip was ≥100 Krad (Si), the critical value of single event upset (SEU) was ≥37.1 MeV·cm2/mg, the critical value of single event latch up was ≥98 MeV·cm2/mg, meeting the life requirements of the initial value storage of aerospace electronic systems. These performances ensure the reliable operation of the space electronic system after restart.

Revolutionizing Warehousing: Unleashing the Power of Machine Learning in Multi-Product Demand Forecasting

Abstract: Amidst the swift-paced digital transformation and intricate web of global markets, the imperative of astute and adaptive demand forecasting is brought into sharp focus, particularly within the context of multi-product warehousing environments. These warehouses, tasked with the meticulous management and storage of a wide array of products, are deeply entwined with the accuracy and foresight provided by proficient future demand predictions—these being crucial in streamlining inventory, curtailing waste, and amplifying profitability. While traditional forecasting approaches provide a fundamental backbone, they often exhibit shortcomings when navigating the multifaceted dynamics present, especially as data proliferates both in volume and complexity. This paper aims to illuminate the pivotal, transformative role of incorporating Machine Learning (ML) methodologies into demand forecasting practices. By delving into a meticulous examination, we seek to elucidate not only the inherent benefits and challenges but also the wider global repercussions of synthesizing avant-garde ML models with the wellentrenched practices prevalent in multi-product warehousing. Ultimately, this exploration aspires to proffer a progressive viewpoint, illustrating how warehouses might adeptly wield technological advancements to fuel efficiency, fortify resilience, and carve out a competitive edge in a perpetually evolving digital milieu.