Intelligent Energy Storage Research Articles

Organic Dye Molecule Intercalated Prussian Blue for Simultaneously Enhancing Coloration Efficiency and Energy Storage Capacity in Electrochromic Battery.

The dual-functional device combining electrochromic properties and energy storage has gained numerous attentions in the field of energy-saving smart electronics. However, achieving simultaneous optimization of coloration efficiency and energy storage capacity of materials poses a significant challenge. This study presents a novel approach by incorporating methyl orange into Prussian blue channels (PB-MO films) to adjust the internal electronic structure of Prussian blue. This modification allows the active layer to simultaneously improve the electrochromic and energy storage performance. The introduction of methyl orange not only alters the ratio of Fe3+/Fe2+ within the framework through the coordination reaction of Fe3+ with methyl orange, but also improves the reaction kinetics after intercalating organic dye molecules, including charge transfer resistance, diffusion capability of ions and capacitive contribution. The PB-MO films demonstrate remarkable properties: high optical contrast (81.4% at 670nm), excellent coloration efficiency (265 cm2C-1), and significant specific capacity (84 mAh m-2 at 0.05 A m-2), outperforming pure PB films. The PB-MO films are ideally suited for applications in displays and intelligent energy storage fields, boasting both high coloration efficiency and substantial energy storage capacity, thus advancing promote the development of dual-functional electrochromic devices.

Photo-thermal effects initiate multi-level energy conversion in “solid-solid” phase-changing fibers

The current textiles primarily employ passive heat barriers to minimize heat loss and achieve effective thermal insulation for human beings. Accordingly, intelligent fibers with energy storage and temperature control capabilities have garnered significant attention due to their potential to revolutionize textile technology. The study integrates the photo-thermal effect and phase change energy storage materials onto a fiber, thereby fabricating a fully intelligent energy storage fiber. This innovation enables the multi-level conversion of sunlight: “Optical energy - Thermal energy - Phase transition energy - Thermal energy”. The intelligent fiber efficiently converts solar energy into heat energy through the photo-thermal coupling of CuNPs, subsequently inducing a spatial conformational change in the solid-solid phase change material within the fiber for effective heat storage. The hybrid fiber possesses enhanced mechanical properties but also exhibits a significantly high phase transition enthalpy value of 49.75 J g−1 and a phase transition temperature suitable for human body temperature (20.19–30.21 °C), especially the fiber is more durable. The photo-thermal conversion test vividly demonstrates the systematic transformation of four distinct forms of energy within the composite fiber. This approach holds significant potential for advancing the field of smart fiber technology.

A Perspective of Bioinspired Interfaces Applied in Renewable Energy Storage and Conversion Devices.

The natural world renders a large number of opportunities to design intriguing structures and fascinating functions for innovations of advanced surfaces and interfaces. Currently, bioinspired interfaces have attracted much attention in practical applications of renewable energy storage and conversion devices including rechargeable batteries, fuel cells, dye-sensitized solar cells, and supercapacitors. By mimicking miscellaneous natural creatures, many novel bioinspired interfaces with various components, structures, morphology, and configurations are exerted on the devices' electrodes, electrolytes, additives, separators, and catalyst matrixes, resorting to their wonderful mechanical, optical, electrical, physical, chemical, and electrochemical features compared with the corresponding traditional modes. In this Perspective, the principles of designing bioinspired interfaces are discussed with respect to biomimetic chemical components, physical morphologies, biochemical reactions, and macrobiomimetic assembly configurations. A brief summary, subsequently, is mainly focused on the recent progress on bioinspired interfaces applied in key materials for rechargeable batteries. Ultimately, a critical comment is projected on significant opportunities and challenges existing in the future development course of bioinspired interfaces. It is expected that this Perspective is able to provide a profound perception into some underlying artificial intelligent energy storage and conversion device design as a promising candidate to resolve the global energy crisis and environmental pollution.

SREM: Smart renewable energy management scheme with distributed learning and EV network

In this article, aiming to develop the Green Internet of Vehicles (G‐IoV), we propose a smart energy management system that leverages the intelligence edge clients and the distributed electric vehicles (EVs). The system proposed in this article incorporates the benefits of both software, specifically in terms of the user interface, and hardware, specifically in terms of edge clients. In particular, this system integrates intelligence edge clients with an EV CAN bus network as an electronic control unit. By leveraging the intelligent edge clients recommendation system, EVs can make informed decisions on battery charging or discharging actions. As a result, a virtual‐power‐plant (VPP) can treat the EVs network as a vast intelligent energy storage facility, efficiently managing the battery energy of all distributed EVs connected to the platform and fully utilizing the electricity generated from renewable energy sources. We experimentally verify that using federal learning to train models in EV networks versus training models directly in EVs, using federal learning in EV networks yields better experimental results.

Biologically Inspired Machine Learning-Based Trajectory Analysis in Intelligent Dispatching Energy Storage System

The present work expects to explore the application effect of biologically inspired Plasticity Neural Network in the industrial intelligent dispatching energy storage system, and highlight the intelligence and fault detection performance of the control system. To address the faults in intelligent dispatching energy storage system, the present work implements a fault diagnosis model of intelligent dispatching energy storage system based on Deep Belief Network (DBN), and simulates and analyzes the model. The results show that the transmission probability of the fault diagnosis model of the constructed intelligent energy storage scheduling system is 100% and when the parameters <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> is between 0.01 and 0.05, the real-time performance of data transmission is the highest. Compared with other classical algorithm models, the success rate and detection accuracy of the proposed algorithm are about 85%, the energy consumption is lower, and the detection effect is more obvious. Therefore, the constructed system obviously has higher real-time performance and more accurate fault detection performance, and significantly better system detection and protection performance. The results provide an experimental basis for the operation and fault detection of intelligent dispatching energy storage system.

Intelligent energy storage management trade-off system applied to Deep Learning predictions

The control of the electrical power supply is one of the key bases to reach the sustainable development goals set by United Nations. The achievement of these objectives encourages a dual strategy of creation and diffusion of renewable energies and other technologies of zero emission. Thus, meet the emerging necessities require, inevitably, a significant transformation of the building sector to improve the design of the electrical infrastructure. This improvement should be linked to advanced techniques that allows the identification of complex patterns in large amount of data, such as Deep Learning ones, in order to mitigate potential uncertainties. Accurate electricity and energy supply prediction models, in combination with storage systems will be reflected directly in efficiency improvements in buildings. In this paper, a branch of Deep Learning models, known as Standard Neural Networks, are used to predict electricity consumption and photovoltaic generation with the purpose of reduce the energy wasted, by managing the storage system using Reinforcement Learning technique. Specifically, Deep Reinforcement Learning is applied using the Deep Q-Learning agent. Furthermore, the accuracy of the predicted variables is measured by means of normalized Mean Bias Error (nMBE), and normalized Root Mean Squared Error (nRMSE). The methodologies developed are validated in an existing building, the School of Mining and Energy Engineering located on the Campus of the University of Vigo.

Preparation of hierarchical porous microspheres composite phase change material for thermal energy storage concrete in buildings

Phase change materials with high latent heat significantly reduce building energy consumption. However, the serious leakage issue, low thermal conductivity, and the poor photothermal response utterly hinder their wide application in architecture. We reported an effective strategy for constructing hierarchical porous composite microspheres (PCN) through spray drying, calcination, and acid activation, using palygorskite (Pal) as the raw material. PCN presented a spherical hierarchical porous structure constructed by crosslinking Pal nanofibers and cellulose nanocrystals in a particular proportion. Paraffin-PCN (P-PCN) composite phase change materials (PCMs) with high shape stability, excellent photothermal conversion ability and latent heat storage capacity were synthesized. The heat preservation time of the P-PCN natural cooling from 35 °C to 30 °C is approximately twice that of the P-Pal. The P-PCN indicates obvious advantages in building thermal management, with the melting enthalpy promoted to 130.2 J/g. Further, the P-PCN-based building materials (P-PCN-B) with the P-PCN and the building aggregate maintain superior light-thermal energy conversion and thermal properties after multiple cycles. The P-PCN-B indicates outstanding mechanical properties (compression strength reaching 14.2 MPa) and flame-retarded properties. This work provides an innovative design strategy for developing multifunctional intelligent energy storage concrete and paves the way for the sustainable utilization of energy storage materials.

Plasmonic fiber-optic sensing system for in situ monitoring the capacitance and temperature of supercapacitors.

Compared with ex situ measurement, the in situ measurement is more suitable for inspecting complex electrochemical reactions and improving the intelligent energy storage management. However, most of the in situ investigation instruments are bulky and expensive. Here we demonstrate a miniaturized, portable, and low-cost fiber-optic sensing system for in situ monitoring the capacitance and temperature. It can help evaluate the self-discharge rate in supercapacitors (SCs). The fiber-optic sensing system with two probes are implanted inside the SCs to monitor the capacitance and temperature, respectively. The dual fiber-optic probes can work independently and avoid cross-interference through structure design. The fiber-optic localized surface plasmon resonance (LSPR) probe near the electrode surface can detect the capacitance in real-time by monitoring ion aggregation on the opposite electrode. The fiber-optic surface plasmon resonance (SPR) probe encapsulated in the thermosensitive liquid can independently detect the temperature change. The measurement uncertainties of the two sensing probes are 5.6 mF and 0.08 ℃, respectively. The proposed tiny and flexible fiber-optic sensing system provides a promising method for in situ monitoring the critical parameters. It is also a powerful tool for investigating electrochemical reactions in various energy storage devices.

In-situ electronics and communications for intelligent energy storage

Lithium-ion batteries are increasingly common in high-power, safety–critical applications such as aerospace, spaceflight, automotive and grid storage. The voltage and power specifications of such applications usually require large numbers of individual cells combined in series and parallel to form a battery pack. It is then the role of the Battery Management System (BMS) to monitor these cells condition and ensure they remain within safe operating limits. To minimise cost and complexity, it is typical to monitor only a fraction of the cells in a battery pack. This creates potential safety and reliability issues and requires conservative limits imposed on the overall system to ensure safe operation. This is insufficient in high-power, safety–critical applications and thus alternative approaches to battery management are required. Here we demonstrate the development of novel miniature electronic devices for incorporation in-situ at a cell-level during manufacture. This approach enables local cell-to-cell and cell-to-BMS data communication of sensor data without the need for additional wiring infostructure within a battery module assembly. The electronics firmware and hardware integration within the cell’s electrode stack is demonstrated to function after triggering post cell formation and through cycling and electrochemical impedance analysis. This work shows that the proposed approach has a negligible impact on the cells’ performance and highlights a new technique for active monitoring of the cell’s in-situ conditions. This research will enable new methods of cells characterization and monitoring for optimum electrochemical and thermal performance while improving system safety.

Ferroelectric Materials Based Coupled Nanogenerators

Innovations in nanogenerator technology foster pervading self-power devices for human use, environmental surveillance, energy transfiguration, intelligent energy storage systems, and wireless networks. Energy harvesting from ubiquitous ambient mechanical, thermal, and solar energies by nanogenerators is the hotspot of the modern electronics research era. Ferroelectric materials, which show spontaneous polarization, are reversible when exposed to the external electric field, and are responsive to external stimuli of strain, heat, and light are promising for modeling nanogenerators. This review demonstrates ferroelectric material-based nanogenerators, practicing the discrete and coupled pyroelectric, piezoelectric, triboelectric, and ferroelectric photovoltaic effects. Their working mechanisms and way of optimizing their performances, exercising the conjunction of effects in a standalone device, and multi-effects coupled nanogenerators are greatly versatile and reliable and encourage resolution in the energy crisis. Additionally, the expectancy of productive lines of future ensuing and propitious application domains are listed.

Development of an intelligent energy storage device for distributed distribution area

In order to solve the problem of seasonal distribution transformer overload in distribution network, especially in rural power grid, an intelligent energy storage device for distributed distribution station area is developed in this paper. The device is connected in parallel to the main line of 380V low voltage line in the distribution station area. The device can compensate the power of the overload distribution transformer, and alleviate the low voltage problem at the head end of the substation area caused by 10kV line overload or distribution transformer heavy overload. This paper introduces the working principle, control strategy, software and hardware design scheme of intelligent energy storage device in distributed distribution station area. The correctness and effectiveness of the device are verified by field operation.

Electromechanical drive management energy

The development of an intelligent energy storage management system is an up-to-date scientific and technical challenge. This system should ensure maximum efficiency of energy storage in power networks for various purposes. The article discusses the use of energy storage in distribution networks of an industrial enterprise and substantiation of the vector control method of the inverted synchronous motor of the energy storage SPENE-1, shows a block diagram of the vector system for controlling the energy accumulator motor and the results of its simulation in MatLab.

Research on Intelligent Energy Storage Control Method with Ethernet Communication

The increasingly severe global energy crisis has brought great challenges to the energy field, and renewable energy power generation system has been widely concerned because of its characteristics of green and inexhaustible. However, renewable energy also has some limitations in its specific application, and affects the grid-connected power generation of new energy. In this paper, based on the background of photovoltaic power station, the intelligent energy storage control method for single inverter is put forward to assist a single inverter, and the DC component of fluctuating power is extracted by using the moving average function; furthermore, the intelligent energy storage control method for the bidirectional DC/DC converters both the lead-acid battery side and the super capacitor side is put forward to ensure the stability of the voltage. Then, by using the Ethernet communication technology of the computer, the energy of the station-level intelligent energy storage is allocated reasonably to preserve the energy of the battery in a reasonable boundary. Finally, the system verification and experimental analysis illustrates that the intelligent energy storage control methods with Ethernet communication proposed in this paper can effectively achieve the intelligent control performance.

Direct Ink Writing of Wearable Thermoresponsive Supercapacitors with rGO/CNT Composite Electrodes

AbstractDeveloping intelligent wearable energy storage devices that can endure harsh conditions is of interest for emerging applications in next‐generation electronics. Despite recent success in exploring functional materials for sophisticated self‐adaptivity in energy storage devices, it remains challenging to obtain both high reliability and superior performance. Herein, a novel method for fabricating micropatterned wearable thermoresponsive supercapacitors via direct ink writing (DIW) technique is reported. Thermal runaway of typical electrochemical storage devices with high power delivery capability can cause serious safety problems. The proposed temperature‐dependent structure works as self‐protection against the common thermal runaway issues of electrochemical energy storage devices. Such construction provides an automatic adjustment as high as 8 F g−1 in specific capacitance, resulting in an overall heat reduction by up to 40%. The printing resolution of the electrodes (175 µm) is among the best in recently reported planar carbon‐based energy storage devices by DIW technique. Manufacturing‐related parameters such as time‐dependent printing speed and curing temperature are also investigated to fabricate this integrated design with varied materials and accuracy. This strategy shows tremendous promise for future intelligent energy storage devices.

Quadruple thiophene based electrochromic electrodeposited film as high performance hybrid energy storage system

Conducting polymers are considered as an attractive option for energy storage system. In this paper, a unique quadruple thiophene-based polythiophene derivative (pPHBT) film was prepared through the electrochemical deposition from a star-shaped tri(bithiophene)benzene (PHBT). The electrodeposited pPHBT film may possess the microporous structure owing to the effective polymerization of star-shaped PHBT monomer. Also, the electrochemical, UV-vis and theoretical characterization of pPHBT film show that the oxidation reaction for this film should occur on the quadruple thiophene units. The unique structure of pPHBT may enable it with interesting electrochromic and energy storage properties. The pPHBT film shows the multicolor electrochromic character from yellow to green, and finally to blue color. The charging/discharging curves show that pPHBT film exhibits a high capacity of 96.7 mAh g−1, which is viewed as a high value among the reported p-doped conducting polymer energy storage materials. Besides, the pPHBT film shows more symmetrical charging-discharging curves and relatively better cycling stability than the linear-structure poly(bithiophene) film. The combination of these fascinating properties results in an intelligent energy storage device changes its color based on its charged state so that the state of charge can be monitored by simple visual inspection.

High-Performance Asymmetric Electrochromic-Supercapacitor Device Based on Poly(indole-6-carboxylicacid)/TiO2 Nanocomposites.

A difunctional porous network of poly(indole-6-carboxylicacid) (PICA)/TiO2 nanocomposites is first prepared using TiO2 nanorod arrays as the scaffold. Because of the synergistic effect of PICA and TiO2, the nanocomposites show good electrochemical performance, a high specific capacitance value (23.34 mF cm-2), and excellent galvanostatic charge-discharge stability. Meanwhile, this nanocomposite can be reversibly switched (yellow, green, brown) with a high coloration efficiency (124 cm2 C-1). An asymmetric electrochromic-supercapacitor device (ESD) is also constructed using the PICA/TiO2 nanocomposites as the anode material and poly(3,4-ethylenedioxythiophene) as the cathode material. This ESD has robust cycle stability and a high specific capacitance value (9.65 mF cm-2), which can be switched from light green to dark blue. After charging, the device can light up a single LED for 108 s, and the energy storage level can also be monitored by the corresponding color changes. This constructed ESD will have great potential applications in intelligent energy storage and other smart electronic fields.

Smart Power Gen using Renewable Sources with Intelligent Energy Storage System in Grid

Smart Power Gen using Renewable Sources with Intelligent Energy Storage System in Grid

Smart Electrochemical Energy Storage Devices with Self-Protection and Self-Adaptation Abilities.

Currently, with booming development and worldwide usage of rechargeable electrochemical energy storage devices, their safety issues, operation stability, service life, and user experience are garnering special attention. Smart and intelligent energy storage devices with self-protection and self-adaptation abilities aiming to address these challenges are being developed with great urgency. In this Progress Report, we highlight recent achievements in the field of smart energy storage systems that could early-detect incoming internal short circuits and self-protect against thermal runaway. Moreover, intelligent devices that are able to take actions and self-adapt in response to external mechanical disruption or deformation, i.e., exhibiting self-healing or shape-memory behaviors, are discussed. Finally, insights into the future development of smart rechargeable energy storage devices are provided.

Control of Energy Storage Systems for Aeronautic Applications

Future aircraft will make more and more use of automated electric power system management onboard. Different solutions are currently being explored, and in particular the use of a supercapacitor as an intelligent energy storage device is addressed in this paper. The main task of the supercapacitor is to protect the electric generator from abrupt power changes resulting from sudden insertion or disconnection of loads or from loads with regenerative power capabilities, like electromagnetic actuators. A controller based on high-gain concepts is designed to drive a DC/DC converter connecting the supercapacitor to the main electric bus. Formal stability proofs are given for the resulting nonlinear system, and strong robustness results from the use of high-gain and variable structure control implementation. Moreover, detailed simulations including switching devices and electrical parasitic elements are provided for different working scenarios, showing the effectiveness of the proposed solution.

A Responsive Battery with Controlled Energy Release.

A new type of responsive battery with the fascinating feature of pressure perceptibility has been developed, which can spontaneously, timely and reliably control the power outputs (e.g., current and voltage) in response to pressure changes. The device design is based on the structure of the Zn-air battery, in which graphene-coated sponge serves as pressure-sensitive air cathode that endows the whole system with the capability of self-controlled energy release. The responsive batteries exhibit superior battery performance with high open-circuit voltage (1.3 V), and competitive areal capacity of 1.25 mAh cm-2 . This work presents an important move towards next-generation intelligent energy storage devices with energy management function.