Hybrid Energy Storage Devices Research Articles

Sequential oxygen evolution and decoupled water splitting via electrochemical redox reaction of nickel hydroxides

Alkaline water electrolysis is a promising low-cost strategy for clean and sustainable hydrogen production but is largely limited by the sluggish anodic oxygen evolution reaction and the challenges in maintaining adequate separation between H2 and O2. Here, we reveal an anodic-cathodic sequential oxygen evolution process via electrochemical oxidation and subsequent reduction of Ni hydroxides, enabling much lower overpotentials than conventional anodic oxygen evolution. By using (isotope-labeled) differential electrochemical mass spectrometry and in situ Raman spectroscopy combined with density functional theory calculations, we evidence that the sequential oxygen evolution originates from the electrochemical oxidation of Ni hydroxides to NiOO– active species while undergoing a different, reductive step of NiOO– for the final release of O2 due to weakened Ni–O covalency. Based on this sequential process, we propose and demonstrate a hybrid water electrolysis and energy storage device, which enables time-decoupled hydrogen and oxygen evolution and electrochemical energy storage in the Ni hydroxides.

Implementation of SOC-based power management algorithm in a grid-connected microgrid with hybrid energy storage devices

Implementation of <i>SOC</i>-based power management algorithm in a grid-connected microgrid with hybrid energy storage devices

CuS modified graphite from spent Li-ion batteries towards building high energy Na-ion capacitors via solvent-co-intercalation process

Sodium-ion capacitors (NICs) are one of the most modern hybrid energy storage devices, and they involve two different energy storage mechanisms (faradaic and non-faradaic). The NICs are bridging the gap between the Na-ion batteries and the capacitors with enhanced power and energy densities. This work explores a new combination electrode material, i.e., recovered graphite (RG) decorated with copper sulphide (CuS, CS) as the anode for the NIC application, in which graphite undergoes the solvent-co-intercalation process, and CuS adopts the conversion reaction. We also report the possibility of efficient direct recovery of the anode of dead/spent Li-ion batteries and upcycling as a battery-type component for NIC with commercially available activated carbon (AC) as the capacitor-type cathode. First, the Na-storage property is analyzed in the half-cell configuration, where the Na/RG-CS half-cell displayed excellent cyclic stability with a stable specific capacity of 113 mAh g−1 after 500 cycles with >96% coulombic efficiency in ether solutions. With a pre-sodiated form of RG-CS as anode and mass-balanced AC as a cathode, the NIC is fabricated. The NIC displayed a superior energy density of 64.6 Wh kg−1 with ultra-long cyclability for more than 10,000 cycles with >85% capacity retention. The compatibility of the NIC in different environmental conditions is also studied, and the cell renders better performance in all temperature conditions.

Optimized control of hybrid energy storage systems for microgrids

Abstract The development of new energy sources is considered to be one of the important ways to solve the current energy shortage problem. Clean energy sources such as wind and light have attracted much attention. Still, the volatility and uncertainty of their output power create difficulties for the large-scale connection of the system to the power grid. Based on the microgrid system, this paper focuses on the energy optimization control problem of storage batteries and supercapacitors. A low-pass filter is used based on the charge state SOC expressed as a formula. The working state of the supercapacitor charge is divided into five regions, with each region having a corresponding reference value for output power correction. The capacity optimization model of the hybrid energy storage device is constructed, and the Gaussian variational quantum particle swarm algorithm (GM-QPSO) is used to optimize the capacity of the hybrid energy storage device. It is found that the capacity optimization method proposed in this paper not only improves the stability of the operation of the system but also ensures the overall economy of the system.

Zeolitic Imidazolate Framework-8 enhanced with tungsten carbide for high-performance hybrid supercapacitors and hydrogen evolution

A promising metal-organic framework (MOF) called Zeolitic Imidazolate Framework-8 (ZIF-8) stands out for its electrochemical applications. Its versatility in physicochemical properties makes it a strong candidate for breakthroughs in energy storage and electrochemical water splitting. The electrode nanomaterials lower specific capacity, small charging/discharging rate, and low conductivity limit its supercapacitor and hydrogen evaluation reaction (HER) applications. The ZIF-8 zeolite structure was decorated with tungsten carbide (WC) to overcome these issues. These modifications result in improved porosity, surface area, density, and pore size, shape, and structure. These characteristics contribute significantly to enhanced electrochemical activity. ZIF-8 MOF/WC nanocomposites have excellent dispersion and stability due to their porosity and strong connection between embedded WC nanoclusters and the framework. The prepared electrode showed a 118.11 mV overpotential and 36.45 mV/dec Tafel slope throughout HER activity. ZIF-8 MOF/WC was used for electrochemical studies and to make a hybrid energy storage device using activated carbon (AC). The hybrid supercapacitor had higher energy and power densities (87 W h/kg and 850 W/kg). The theoretical technique (Dunn model) was also employed to analyze experimental results more thoroughly.

Adaptive VSG-Based power allocation strategy for hybrid energy storage

Abstract Aiming at the stochasticity of photovoltaic output and the problem of power, voltage, and frequency fluctuation caused by the lack of system inertia and damping parameters, a photovoltaic storage microgrid is constructed as a research object. Firstly, a virtual synchronous motor VSG is used to control the grid-connected inverter and to improve the dynamic performance of the system further. The inertia and damping parameters of the VSG are adjusted adaptively. Secondly, the hybrid energy storage device composed of a supercapacitor and battery adopts a second-order filter to avoid the integrating effect of the first-order filter on the high-frequency power and improve the poor performance of the first-order filter at the cutoff frequency to improve the accuracy of power distribution. Moreover, two negative feedback links of power error are added in the power distribution link to correct the reference power of the energy storage device, which further improves the power tracking effect of the energy storage system. Finally, the effectiveness of the above strategy is verified by a Matlab simulation session.

Implementation of the Electric Wheelchair using Hybrid Energy Storage Devices

Implementation of the Electric Wheelchair using Hybrid Energy Storage Devices

Synergistic effect of co-sputtered tungsten-titanium nitride as electrode material for efficient hybrid supercapacitors

The dawn of bimetallic transition metal nitrides has attracted considerable interest as battery grade electrode material for potential energy storage applications. In addition, it is essential to investigate binder-free processes to improve the performance of the fabricated electrodes. In this study, binder-free tungsten‑titanium nitrides (W-TiN) are deposited through RF/DC magnetron co-sputtering onto the conducting nickel foam (NF). SEM, EDX and X-ray diffraction are exploited to investigate surface morphology, elemental composition, and structural properties of sputtered materials. The W-TiN electrodes are characterized through electrochemical investigation in half-cell configuration. The tested W-TiN electrode is further utilized with activated carbon (AC) electrode to develop hybrid supercapacitor device W-TiN//AC. The hybrid device revealed a maximum energy density (Es) of 88.8 Wh/kg and power density (Ps) 1700 W /kg. To further understand the mechanism of hybrid devices, the capacitive and diffusive contributions are computed using linear and quadradic models. This study provides a new direction to integrate co-sputtered binder-free electrode materials and devices for large scale production of advanced hybrid energy storage devices.

Exploring the Synergistic Potential of Bimetallic Sulfide (SrCuS) as Battery‐Grade Electrode Material for Hybrid Supercapacitor Applications

State‐of‐the art hybrid energy storage devices, owing to their attractive electrochemical features of high specific energy, power, and great stability, have earned incredible attention throughout the world. Herein, bimetallic sulfide (SrCuS) composites with different concentration are electrochemically analyzed for hybrid supercapacitor applications. In half‐cell assembly, amidst all compositions, Sr0.5Cu0.5S reveals relatively better performance demonstrating specific capacity “Qs” of 596.48 C g−1. To assess the hybrid device's (Sr0.5Cu0.5S//AC) electrochemical performance, positive electrode (Sr0.5Cu0.5S) along with activated carbon as negative electrode is utilized. The device displayed energy density “Ed” of (51.28 W h kg−1) and power density “‘Pd” of 6800 W kg−1. Furthermore, the device is examined for capacitive‐ and diffusive‐controlled processes employing a semi‐empirical approach, using linear and quadratic models, respectively.

State of Charge and State of Health Coestimation for Lithium-Ion Capacitor Based on Multi-innovation Filters

The lithium-ion capacitor (LIC) is a new type of hybrid energy storage device, which combines the advantages of lithium-ion battery and electric double layer capacitor. To achieve efficient and reliable application of LIC in practical scenarios, accurate model and state estimation method are needed. In this work, the electrical behavior of LIC is studied, which is then described by the Thevenin model. A multi-innovation filter- (MIF-) based coestimation method is proposed, in which the multi-innovation linear Kalman filter (MI-LKF) is used for model parameter identification, the multi-innovation cubature Kalman filter (MI-CKF) is used for state of charge estimation, and the multi-innovation extended Kalman filter (MI-EKF) is used for state of health estimation. Compared to traditional methods, this method can significantly improve estimation accuracy by only expanding the innovation used to update the state from a single moment to multiple moments. The experimental results indicate that the estimation errors of SOC and SOH can be constrained within ±0.5%. In addition, the proposed method has good robustness and can achieve high-precision state estimation even in the face of noise interference, uncertain initial values of the algorithm, and uncertain starting operating points.

An integrated energy storage framework with significant energy management and absorption mechanism for machine learning assisted electric vehicle application

Regarding environmental friendliness, low maintenance needs, and statuses as a renewable technology, Hybrid Electric Vehicles (HEV) have become more and more popular around the world. In this, the energy management system is crucial for the effective storage of power and regulation of the energy flow system. As a result, Hybrid Energy Storage Systems (HESS) has increased interest due to their superior capabilities in system performance and battery capacity when compared to solo energy sources. Additionally, the primary problem interaction applications, including such battery electric vehicles, are the energy storage system. Multiple energy storage technologies, including battery packs, flywheels, super-capacitors and fuel cells, are combined into a HESS due to their complementing properties. The goal of this setup is to make renewable energy sources more reliable by storing power generated from intermittent sources or by providing backup energy generation from traditional energy sources. A HESS could be utilized as an alternate energy storage system to help them make up for their lack of power density. HESS needs a smart Energy Management System (EMS) to function properly since it combines the dynamic characteristics of a battery and a SuperCapacitor (SC). The motive of the study is to suggest an actual power management control system to accomplish these objectives. The plan is built using a wavelet transform, deep learning mechanism, and fuzzy logic together. A useful tool for separating the various frequency elements of a load's power requirements to reflect the properties of a battery or supercapacitor is the wavelet transform. It is challenging to immediately apply it in a system, though. Because of this, the traditional optimization-model-based facility energy management system encounters substantial difficulties with online forecast and calculation. To solve this problem, the paper proposes a ML technique dependent on a Long Short-Term Memory (LSTM). The suggested control system structure allows for the separation of the offline and online stages of the LSTM technique. The LSTM is being used to map states (inputs) to decisions (outputs) based on system training during the offline stage. As a result, the supercapacitor receives an online calculation and distribution of the high-frequency power requirement. The SOC of the supercapacitor is kept within the appropriate range via fuzzy logic control. To evaluate the efficacy of the suggested energy management control technique, a 70 V battery with 92 V supercapacitor hybrid energy storage devices for hardware platforms have been created.

Crystallinity transformation engineering of hydrous cobalt nickel phosphate cathodes for hybrid supercapacitor devices: Extrinsic/battery to intercalation type pseudocapacitors

The necessitating strategies of rationalizing nanostructures and crystallinity of electrode material are crucial to developing high-efficiency hybrid energy storage devices. To enhance the energy storage performance of bimetal phosphates, it is important to have a strategic blend of metal cations that can work together synergistically. So, this work describes the scalable preparation of binder-free cobalt nickel phosphates thin film cathodes with cations variation (Co/Ni) via the facile Successive Ionic Layer Adsorption and Reaction (SILAR) process. The distinct roles of cations in cobalt nickel phosphate electrodes resulted in a noteworthy structural transformation from crystalline to amorphous with an increment of Ni content. The change in cations composition influences the pseudocapacitive performance from extrinsic/battery to intercalation type, and cobalt nickel phosphate electrode with an ideal cations composition (Co:Ni) ratio of approximately 1:1 attain the highest specific capacitance (SCs) of 2142 F g−1 (1071 C g−1). To fulfil the demand for high-performance hybrid supercapacitor devices, aqueous (HASC) and solid-state (HSSC) supercapacitors are assembled using optimized cobalt nickel phosphate (S-CNP5) as a cathode. The HASC device represents maximum SCs of 120 F g−1 with specific energy (SE) and specific power (SP) of 42.59 Wh kg−1 and 1600 W kg−1, respectively. The flexible HSSC device shows impressive SCs of 89 F g−1 and SE of 31.54 Wh kg−1 at SP of 2057.14 W kg−1. The practical demonstration of an HSSC device to power a 12-white LED lamp suggests that the SILAR strategy offers commercializing insights for fabricating high-specific capacity hydrous cobalt nickel phosphate thin film cathodes.

Long-term cost planning of data-driven wind-storage hybrid systems

—To address the long-term cost planning problem accurately, typically a significant number of formulas are required. However, this increases computational complexity and limits the generalizability of the approach to practical problems. To overcome these challenges, this study adopts a data-driven approach that considers uncertainties to evaluate the long-term cost planning problem accurately for wind power generation with hybrid energy storage. A method for predicting wind power output is proposed using temporal convolutional networks to handle long-term uncertainties. Additionally, an instantaneous phase-synchronous wind power output feature extraction method based on Hilbert transform theory is introduced to capture time-series fluctuation characteristics and address short-term uncertainties. Furthermore, the long-term operational costs and planning of high-percentage new energy wind farms with hybrid energy storage are discussed by combining the wind power output characteristics with the operating characteristics and lifespan of hybrid energy storage devices. The experimental results demonstrate the significant advantages of the deep learning probabilistic prediction model combined with wind power feature extraction. The algorithm validates the effectiveness of considering multiple uncertainties in the planning of microgrids with hybrid energy storage, particularly in considering the uncertainty of the decreasing trend in the investment cost of battery energy storage.

High performance MnNbS@MXene hybrid electrode for battery-supercapacitor hybrid device and biomedical applications

Hybrid energy storage devices have obtained a lot of interest because of their remarkable capacitance, high stability and multiple applications. The energy-storage capabilities of transition metal sulfides, such as MnNbS, have expanded beyond the domain of oxide-based materials. Transition metal sulfides and the MXene-based nano-architecture materials have been praised because of their synergistically enhanced conductivity and redox flexibility. Manganese niobium sulfide (MnNbS) binary electrode material was synthesized using the hydrothermal method. The MnNbS-MXene nanocomposite electrode was designed to improve the electrochemical characteristics. It exhibited a superior specific capacity (Qs) of 1094 C/g or 1562.85F/g at 1.5 A/g. The hybrid material (MnNbS-MXene) and activated carbon (AC) were used to make the asymmetric hybrid supercapacitors (MNS-MXene//AC). The hybrid device delivered extraordinary Qs of 153.23 C/g, energy density of 35.77 Wh/kg, and power density of 2800 W/kg. To estimate the capacity retention (CR), the device was measured up to 6000 cycles. It also revealed an astonishing CR of 91 %, which is much greater than that of pure MXene//AC and MnNbS//AC. Besides, the MnNbS-MXene//AC nanocomposite electrode is used as a chemical sensor to detect hydrogen peroxide (H2O2). The MnNbS-MXene showed high sensitivity against the H2O2. The device showed the response up to a wide range of H2O2 (1 mM-5mM). Our research presents a perspective and practical application for producing high-performance electrode material based on transition metal sulfide composites and chemical sensors to detect cancerous cells in the body.

Multifunctional Iron Selenate Sheath of Fe-Based Anode Achieving High-Rate Capacity-Durability Combination of Aqueous Hybrid Energy Storage Devices.

The introduction of battery-type cathode has been commonly considered a preferred approach to boost the energy density of aqueous hybrid energy storage devices (AHESDs) in alkalic systems, but AHESDs with both high energy density and power density are rare due to the great challenge in designing battery-type anode materials with high rate and durability comparable to capacitive-type carbon anodes. In this paper, a well-hydrated iron selenate (FeSeO) sheath is constructed around FeOOH nanorods by a facile electrochemical activation, demonstrating the unique multifunction in fasting charge diffusion, promoting the dissociation of H2O, and inhibiting the irreversible phase transition of FeOOH to inert γ-Fe2O3, which endow the hydrated sheath coated Fe-based anodes with an impressive rate capability and superior durability. Thanks to the comprehensive performance of this Fe-based anode, the assembled AHESD delivered a high energy density of 117Whkg-1 with the extraordinary durability of almost 100% capacity retention after 40000 cycles. Even at an ultrahigh power density of 27000Wkg-1, an impressive energy density of 65Whkg-1 can be achieved, which rivals previously reported energy-storage devices.

Effects of interlayer space engineering and surface modification on the charge storage mechanisms of MXene nanomaterials: A review on recent developments.

Two-dimensional MXenes were discovered in 2011 and, because of their outstanding properties, have attracted significant attention as electrode materials for supercapacitors, rechargeable batteries, and hybrid energy storage devices. Numerous studies were dedicated to identifying feasible charge storage mechanisms in MXenes and investigating the effects of structural and superficial properties on the corresponding mechanisms. The results clarify that interlayer distance and surface termination groups in MXenes significantly determine the deliverable energy and power density in respective energy storage devices. Additionally, due to van der Waals interactions, adjacent MXene sheets tend to aggregate and restack during electrode preparation or charge and discharge cycling, reducing the MXene interlayer distance and deteriorating its energy storage ability. In this review, we first summarize the different charge storage mechanisms applicable to MXenes in different energy storage devices and describe the effect of interlayer spacing and surface termination groups. Then, different interlayer space engineering methods are reviewed in terms of materials and procedures, and their impact on the electrochemical behavior and restacking tendency of MXene is described.

Study on energy efficiency improvement strategy of photovoltaic-hybrid energy storage DC microgrid considering green energy saving concepts

Abstract In this paper, the development of microgrid technology is discussed in close connection with the growing energy demand and the real needs of energy structure adjustment in the context of the times. Guided by green energy saving, the research focuses on constructing a hybrid energy storage DC microgrid model, especially the integrated photovoltaic power generation model and the related control strategy and power characteristics. The article further adopts a fuzzy PID control strategy to optimize the energy efficiency configuration of hybrid energy storage devices in DC microgrids. By carefully analyzing and optimizing the energy storage system in the DC microgrid, remarkable results are obtained: the optimized capacitive charge states range from 0.1 to 0.9, indicating a significant fluctuation of capacitive charge states, but at the same time avoiding the phenomenon of light abandonment and ensuring the reliability of power supply. More notably, during the increase of SOC (state of the energy storage system) from 0.40 to 0.70, the system can perform mode transitions under continuous load changes. This point shows the effectiveness of the optimization method in improving the energy storage efficiency and enhancing the system performance of the DC microgrid. Overall, the optimization method proposed in this paper provides a practical energy storage optimization scheme for developing microgrids, which is of great practical significance in promoting the research and application of microgrid technology. This not only helps to improve the efficiency of energy use, but also is a crucial step to realize sustainable energy development.

Pyridine 3,5-dicarboxylate-based metal-organic frameworks as an active electrode material for battery-supercapacitor hybrid energy storage devices.

Efficient energy storage and conversion is crucial for a sustainable society. Battery-supercapacitor hybrid energy storage devices offer a promising solution, bridging the gap between traditional batteries and supercapacitors. In this regard, metal-organic frameworks (MOFs) have emerged as the most versatile functional compounds owing to their captivating structural features, unique properties, and extensive diversity of applications in energy storage. MOF properties are governed by the structure and topological characteristics, which are influenced by the types of ligands and metal nodes. Herein, MOFs based on pyridine 3,5-dicarboxylate (PYDC) ligand in combination with copper and cobalt are electrochemically analyzed. Owing to the promising initial characterization of Cu-PYDC-MOF, a battery supercapacitor hybrid device was fabricated, comprising Cu-PYDC-MOF and activated carbon (AC) electrodes. The device showcased energy and power density of 17 W h kg -1 and 2550 W kg -1, respectively. Dunn's model was employed to gain deeper insights into the capacitive and diffusive contributions of the device. With their performance and versatility, the PYDC-based MOFs stand at the forefront of energy technology, ready to power a brighter future for upcoming generations.

Developing Hybrid Aqueous Li/Na-Ion Capacitors by Electrodes Synthesized by Facile Recycling and Reuse Process: Waste to Wealth

The explosive evolution of industrialization and technologies has grabbed eyeball attention inthe current scenario for improving the living standard of the human beings irrespective of the threat and risk possessed by the environment. So to overcome this catastrophe, there has been a significant focus on progressive development of electrochemical energy storage and conversion systems to resolve the intermittency nature of renewable energy sources. The electrochemical energy storage devices such as batteries and supercapacitors have been relied upon the ability to store the charge in the wide potential region with high Coulombic efficiency and long-term stability. However, transition metal oxides are well known, for their high theoretical specific capacity but suffer from low electronic conduction and capacity fading during cycling. To address these shortfalls metal oxides are usually, embedded within a conductive carbon-based matrix (for instance graphene). The use of graphene would afford easy pathway for electron movement and increases the surface area for higher interaction of active electrode materials with electrolyte. Subsequently, graphene based transition metal oxides composites have attracted active research pursuits in synthesizing the low cost effective electrode materials for energy storage devices. And if graphene is recycled and reused then it’s very much cheap and efficient electrodes for hybrid energy storage devices. In this work, electrode materials are developed by facile and economic approach with an aim to achieve improved electrochemical activity. The conversion of utilized electrode materials (e-waste) to efficient graphene electrodes (wealth) is validated in this research. The challenges in this work are (i) recycling pure samples, (ii) resynthesizing the graphene and tuning its layers, (iii) stability and efficiency of electrode materials, (iv) optimization of electrode materials and (v) practical demonstration of hybrid-ion capacitors. The fascinating part of the research finding is both the electrode materials are derived via. recycling, for which device can be promise to be sustainable and clean energy. The details will be presented in ECS conference. Such scheme could serve as precedent to the development of potential electrode materials for energy storage devices.

A power-speed hierarchical optimization framework of diesel/battery/supercapacitor vehicular hybrid propulsion systems

Ships' fuel consumption has emerged as the primary contributor to energy use and pollution in maritime transportation. This paper presents a novel marine vehicular hybrid propulsion system (VHPS) comprising a diesel generator and a hybrid energy storage device (HESD) that integrates batteries and supercapacitors (SCs). However, variations in the power and energy characteristics of the three sources result in heightened intricacies in energy management and system control. Therefore, a power-speed hierarchical optimization framework is proposed to optimize the fuel consumption and stability of the system. Within this framework, an AECMS-GRNN energy management strategy (EMS) is proposed to reduce the fuel consumption of VHPS. Based on the AECMS-GRNN strategy's power distribution results, a multi-zone target speed power hysteresis control strategy is proposed to ensure that the speed of the diesel generator is stable, so as to improve the stability of the system. Finally, an experimental hardware-in-the-loop (HIL) platform is employed to validate the proposed framework's performance. From experimental results, the AECMS-GRNN strategy demonstrates precise load prediction with a minimal predictive ARMSE value of 1.5886 kW. Compared with a conventional rule-based (RB) strategy, AECMS-GRNN strategy can reduce the fuel consumption by 0.077 kg, about 7.7%. Additionally, the proposed speed control strategy ensures a stable speed for the DG, contributing to the system's consistent power supply.