Energy Storage Module Research Articles

Computationally effective machine learning approach for modular thermal energy storage design

This research presents an innovative approach that integrates computational fluid dynamics (CFD) and machine learning (ML) for the design and optimization of thermal energy storage (TES) systems. Heat discharging parametric analyses conducted using CFD serve as the basis for training ML models, including linear regression, K-nearest neighbor (KNN) regression, gradient boost regression (GBR), XGBoost, LightGBM, and neural network (NN). NN emerges as the most suitable for predicting time-dependent variations of concrete and heat transfer fluid (HTF) temperatures. The trained ML models offer an efficient alternative to traditional CFD simulations, enabling the prediction of temperatures in concrete thermal energy storage (CTES) modules under varying inlet conditions, velocities, and time. Leveraging these ML models, the research demonstrates the design of modular CTES cascaded systems with multiple modules in series and parallel configurations, significantly reducing computational cost and time by over 99% compared to full-scale CFD simulations. For instance, in predicting 4-hour time-dependent thermal behavior, CFD takes 97 s per data point and 238,500 s for a single module, compared to ML models’ 16-20 ms per data point and around 290 s per module, indicating their efficiency and scalability in predicting thermal discharge, especially for modular CTES system design and optimization. ML models also demonstrate computational efficiency for designing CTES systems involving multiple modules, taking approximately 765 s - 1047 s for various CTES system configurations, indicating their effectiveness over CFD in predicting thermal discharge for modular CTES systems. The integration of CFD and ML provides a streamlined workflow for designing and optimizing CTES systems, reducing computational efforts, cost, and time. Moreover, this workflow can be updated with additional training data to implement it for unique modular designs with different conditions. Such a generalization of this ML-based approach makes it applicable to a wide range of thermal energy storage designs and geometries, offering a promising avenue for future research and development in the field of thermal energy storage.

Enhancing renewable energy utilization and energy management strategies for new energy yachts

Hydrogen energy, due to its clean and efficient nature, has shown great potential during the current transition period in the shipbuilding industry. However, the application of hydrogen energy in ship energy systems is influenced by variations in operational load and the integration of new energy sources during actual navigation. To address these issues, this paper focuses on optimizing and scheduling the operation of ships under various navigation conditions, considering the distributed nature of hydrogen energy. System simulations were conducted to model the photovoltaic (PV), proton exchange membrane fuel cells (PEMFCs), lithium batteries (LIBs), electrolytic cells (ECs), and energy storage modules of yacht energy systems. Component boundaries and objective functions were set, and two cases (excess photovoltaic state and constant power state) were designed to optimize and regulate the energy balance of hydrogen-powered yachts, enhancing their comprehensive utilization of renewable energy. By comparing the changes in ship energy under the two cases, it was concluded that case 1 ensures the maximum utilization of renewable energy. When photovoltaic power generation is insufficient, the PEMFC and LIB in the system provide the required power to achieve a supply-demand balance. Moreover, when PV power generation is sufficient, hydrogen energy is used to store renewable energy. The optimization method designed in this study can, to some extent, maximize the application of renewable energy in new energy yachts, ensuring the efficiency of the comprehensive energy system of new energy yachts, reducing emissions, and improving the sustainability and economic efficiency of the ships.

A SOC balancing adaptive droop control scheme for multiple energy storage modules in DC microgrids

A SOC balancing adaptive droop control scheme for multiple energy storage modules in DC microgrids

Economic dispatching strategy of centralized wind-solar-hydrogen storage station

Abstract Compared to traditional energy storage, hydrogen energy storage is a novel form of energy storage that has exceptional potential in the temporal, energy, and spatial domains and is better suited to the numerous requirements of the new power system. Firstly, the operation mode of centralized wind-photovoltaic-hydrogen energy storage station is described and modeled around the new energy generation module, new energy convergence station and hydrogen energy storage module. On this basis, considering the operating cost and transaction income of the station, an economic dispatch model is established with the goal of optimal economy. An economic dispatch model for wind-photovoltaic-hydrogen energy storage stations is proposed. Finally, the data results show that this station model can bring economic benefits and promote high-proportion grid-connected new energy.

Mimosa plant leaf-inspired 180° foldable lithium-ion batteries with enhanced electrochemical-mechanical behaviors

Developing high-performance batteries with flexibility is crucial for flexible electronic applications. Although various types of flexible battery designs have been proposed in recent years to improve cycling performance and flexibilities, their application is limited in the most widely used flexible device, namely foldable screen smartphones, due to their inability of 180° folding. Here, inspired by the unique dynamic property of the mimosa plant leaf, we design a bio-inspired flexible lithium-ion battery (FLIB) containing thick energy-storage modules, analogous to the leaflets, and electrical contact part, analogous to the leaf stalk. This design resulted in a FLIB with high flexibility (180° folding and bending), cycling stability, and scalability. Notably, our FLIB demonstrated an improved cycling performance, even under harsh dynamic deformations (10,000-times dynamic 180° folding and 7500-times dynamic bending). The potential mechanisms of mechanical protection for the FLIB were investigated through finite element analysis, further proving its remarkable mechanical endurance. Therefore, our flexible battery design meets the demand of flexible devices for stable power supply under various deformation states. This work sheds new light on the structural innovations and practicality of flexible batteries for future applications.

A Magnetically Coupled Piezoelectric Ocean Wave Energy Harvester for Self-Powered Low-Power Appliances

The ocean contains abundant wave energy, which can be used as a new regenerative energy for power generation and provide energy for self-powered low-power appliances, realizing in situ energy utilization. Then, it can effectively promote the sustainable development strategy of the ocean and bring huge energy and social and environmental benefits. This paper proposes a magnetically coupled piezoelectric ocean wave energy harvester (MPWEH) system for wave energy harvesting. The MPWEH system includes four modules: energy harvesting, force magnification, piezoelectric power generation, and energy storage module. The energy harvesting module moves up and down in the tube body with the wave, effectively capturing and absorbing the wave energy and transforming the harvesting module’s motion into the interaction repulsive force between magnets. Then, the force magnification module amplified the magnetic force and applied it to the polarization direction of the piezoelectric ceramic to self-power the low-power appliances. This research carried out the feasibility verification experiment with the MPWEH prototype, and the results show that when the period is 3[Formula: see text]s, and the amplitude is 2[Formula: see text]m, the maximum voltage can reach 15[Formula: see text]V, and the maximum power can reach 12.85[Formula: see text]mW. Take Jiaozhou Bay Bridge as an example. The MPWEH system’s energy harvesting potential is studied, and the annual power generation of all the acquisition devices can reach 55.72[Formula: see text]kWh, which can be enough energy to supply the sensors on the cross-sea bridge.

Performance prediction and analysis of a solar assisted medium-deep geothermal heating system

Abstract The solar assisted medium-deep geothermal heating (SAMGH) system is a novel kind of heating system that can combine the benefits of geothermal and solar energy. However, the variations in borehole heat exchanger (BHE) performance and the intermittency of solar energy pose challenges for predicting the overall performance of the coupled system and designing the operational strategies. To conduct simulation on the SAMGH system for performance prediction and analysis, a coaxial medium-deep borehole heat exchanger coupled with the solar energy heating system for an office building in Xi’an was developed. The TRNSYS software was employed to establish the model of the coupled system. A ground source heat pump (GSHP) heating system was used for comparison. The simulation results showed that with the introduction of the solar energy and heat storage modules, the annual operating time of the geothermal system only accounts for 32.06%. The energy consumption of the coupled system can be reduced from 63585 kW to 44586 kW, and the energy consumption proportion of the geothermal system in total value decreased from 69.10% to 40.58%. Therefore, the average coefficient of performance (COP) of the heat pump and the system were improved by 63.71% and 91.77%, respectively. Moreover, because the solar energy is beneficial to the ground heat recovery, the average ground temperature increased from 42.5 °C to 43.88 °C after ten years of operation. The proposed design method and simulation results can serve as a reference for design method and performance analysis of the geothermal and solar coupled system.

Flexible, Wearable Wireless-Charging Power System Incorporating Piezo-Ultrasonic Arrays and MXene-Based Solid-State Supercapacitors.

With the continuous development of wearable electronics, higher requirements are put forward for flexible, detachable, stable output, and long service life power modules. Given the limited capacity of energy storage devices, the integration of energy capture and storage is a viable approach. Here, we present a flexible, wearable, wireless-charging power system that integrates a piezoelectric ultrasonic array harvester (PUAH) with MXene-based solid-state supercapacitors (MSSSs) in a soft wristband format for sustainable applications. The MSSS as the energy storage module is developed by using Ti3C2Tx nanosheet-loaded inserted finger-like carbon cloth skeletons as electrodes and poly(vinyl alcohol)/H3PO4 gel as electrolytes, with high energy density (58.74 Wh kg-1) and long cycle life (99.37%, 10,000 cycles). A two-dimensional stretchable piezoelectric array as a wireless-charging module hybridizes high-performance 1-3 composite units with serpentine electrodes, which allows wireless power via ultrasonic waves, with a maximum power density of 1.56 W cm-2 and an output voltage of 20.75 V. The overall PUAH-MSSS wireless energy supply system is 2 mm thick and offers excellent energy conversion/storage performance, cyclic stability, and mechanical flexibility. The results of this project will lay the foundation for the development of next-generation wearable electronics.

Solar photovoltaic refrigeration system coupled with a flexible, cost-effective and high-energy-density chemisorption cold energy storage module

Owing to the environmental pollution and high costs associated with lead-acid batteries, this paper proposes a solar photovoltaic (PV) refrigeration system coupled with a flexible, cost-effective and high-energy-density chemisorption cold energy storage module. Its operation mode includes daytime solar PV refrigeration/cold energy charging mode and nighttime cold energy discharging mode. A novel composite sorbent SrCl2 is developed using expanded natural graphite as matrix and carbon coated aluminum as additive, exhibiting superior heat and mass transfer performance. A sorbent performance test bench is constructed, demonstrating that the cold energy storage density reaches 503.6 kJ/kg at an evaporating temperature of −15 °C, 1.5 times of ice storage. Compression-assisted desorption is adopted to regulate desorption temperature, so that 75–90 °C solar hot water from low-cost non-concentrating solar collectors can be utilized as the driving heat source. For an evaporating temperature of −10 °C and a solar hot water temperature of 90 °C, the electrical coefficient of performance for cold energy storage unit reaches 3.72, representing a 33 % improvement compared to conventional solar PV refrigeration systems. This novel system features characteristics such as low cost, high efficiency and eco-friendliness, offering a promising solution for solar refrigeration.

A self-powered smart wave energy converter for sustainable sea

Self-powered smart buoys are widely used in sustainable sea, such as marine environmental monitoring. The article designs a self-powered and self-sensing point-absorber wave energy converter based on the two-arm mechanism. The system consists of the wave energy capture module, the power take-off module, the generator module and the energy storage module. As the core component of the wave energy converter, the power take-off module is mainly composed of a two-arm mechanism, which can convert the oscillation heave motion into unidirectional rotary motion. To evaluate the power generation performance of the system, the kinematic and dynamic models of the wave energy converter with the flywheel are established, and the disengagement and engagement phenomena of the flywheel are analyzed. The effectiveness of the prototype in capturing wave energy is verified through dry experiments in lab and field tests. The dry experiment reveals that the maximum output power of the system is 5.67 W, and the maximum and average mechanical efficiency are 66.63 % and 48.35 %, respectively. Additionally, the field test demonstrates that the peak output power can reach 92 W. Meanwhile, the generated electrical signals can be processed by deep learning algorithms to accurately identify different wave states. This high performance confirms that the proposed wave energy converter can meet its own energy needs by capturing wave energy in the marine environment, while also achieving self-sensing for wave condition monitoring. The system has great potential for promoting the development of intelligent sustainable sea in the future.

A self-regulation blades wind energy harvester system for self-powered wireless monitoring sensors

Using wind energy in the natural environment provides a promising solution for wireless sensor power supply for ecological, meteorological, environmental, and infrastructure monitoring. However, the uncertainty and disorder of natural wind restrict the further development of wind energy harvester systems and self-powered wireless sensor technology. Hence, this paper proposes a self-regulation blade wind energy harvester system (SBWEHS) for self-powered wireless monitoring sensors in remote field areas with power shortages. The system is mainly composed of three parts: wind harvesting mechanism, generator module, and energy storage module. The device can control the blade overlap ratio according to the wind speed while generating electricity to maximize the power coefficient. The system can control the blade’s closure in bad weather to protect the device. Based on the computational fluid dynamics technology of Ansys Fluent software, this study evaluated the impact of wind speed and blade overlap ratio on the two-stage blades. Experiments revealed that when the overlap ratio of the blades is fixed at 0.2 and the wind speed is set at 16 m/s, the maximum average power will reach 0.79 W, which fulfills the power requirements of wireless sensors. These results illustrate that the SBWEHS can effectively supply power for wireless monitoring sensors, especially in remote natural environments.

A Combined Persistence and Physical Approach for Ultra-Short-Term Photovoltaic Power Forecasting Using Distributed Sensors.

This paper presents a novel method for forecasting the impact of cloud cover on photovoltaic (PV) fields in the nowcasting term, utilizing PV panels as sensors in a combination of physical and persistence models and integrating energy storage system control. The proposed approach entails simulating a power network consisting of a 22 kV renewable energy source and energy storage, enabling the evaluation of network behavior in comparison to the national grid. To optimize computational efficiency, the authors develop an equivalent model of the PV + energy storage module, accurately simulating system behavior while accounting for weather conditions, particularly cloud cover. Moreover, the authors introduce a control system model capable of responding effectively to network dynamics and providing comprehensive control of the energy storage system using PID controllers. Precise power forecasting is essential for maintaining power continuity, managing overall power-system ramp rates, and ensuring grid stability. The adaptability of our method to integrate with solar fencing systems serves as a testament to its innovative nature and its potential to contribute significantly to the renewable energy field. The authors also assess various scenarios against the grid to determine their impact on grid stability. The research findings indicate that the integration of energy storage and the proposed forecasting method, which combines physical and persistence models, offers a promising solution for effectively managing grid stability.

Dual Frequency Energy Harvesting System Based on Planar Inverted F-shaped Antenna

<p>With the expansion of Internet of things (IoT) scale and the extension of its application fields, node energy acquisition has become one of the constraints on the development and application of IoT technology. Wireless energy acquisition is faced with the challenge of how to enhance power conversion efficiency under low input power in the broadband range. This study aimed to improve the capability of energy collection and transmission in wireless communication, an efficient dual-frequency energy harvesting system was proposed, moreover a novel dual-frequency planar inverted-f antenna (PIFA) and its energy conversion circuit for Radio frequency (RF) energy harvesting were designed by studying the characteristics of ambient RF energy and antenna. The developed antenna is designed and manufactured for GSM 900mhz or DCS 1.8 GHz to harvest the ambient energy provided by nearby devices. It is proved that the new dual-frequency antenna still has high efficiency when the input power is less than -20 dbm, and can maximize the receiving energy. The system works with an energy conversion and storage module to convert weak signals into required voltages, the simulation and test results show that the maximum conversion efficiency of the prototype is about 65% at 920MHZ and 1.8GHz at -20 dBm input power.</p> <p> </p>

3D printing encouraging desired in-situ polypyrrole seed-polymerization for ultra-high energy density supercapacitors

The tireless pursuit of supercapacitors with high energy density entails the parallel advancement of well-suited electrode materials and elaborately engineered architectures. Polypyrrole (PPy) emerges as an exceedingly conductive polymer and a prospective pseudocapacitive materials for supercapacitors, yet the inferior cyclic stability and unpredictable polymerization patterns severely impede its real-world applicability. Here, for the first time, an innovative seed-induced in-situ polymerization assisted 3D printing strategy is proposed to fabricate PPy-reduced graphene oxide/poly (vinylidene difluoride-co-hexafluoropropylene) (PVDF-HFP) (PPy-rGO/PH) electrodes with controllable polymerization behavior and exceptional areal mass loading. The preferred active sites uniformly pre-planted on the 3D-printed graphene substrates serve as reliable seeds to induce efficient polypyrrole deposition, achieving an impressive mass loading of 185.6 mg cm−2 (particularly 79.2 mg cm−2 for polypyrrole) and a superior areal capacitance of 25.2 F cm−2 at 2 mA cm−2 for a 12-layer electrode. In agreement with theses appealing features, an unprecedented areal energy density of 1.47 mW h cm−2 for a symmetrical device is registered, a rarely achieved value for other PPy/rGO-based supercapacitors. This work highlights a promising route to preparing high energy density energy storage modules for real-world applications.

Performance analysis of a novel façade-based building integrated photovoltaic-thermal system with phase change material for domestic hot water

Since the current contribution of solar thermal energy to the amount of energy consumed for domestic hot water in buildings worldwide is very low (8.4 %, approximately), the potential of this renewable energy to meet the demand for domestic hot water is quite significant. In this context, this paper presents a new façade-based building integrated photovoltaic-thermal system with phase change material which has been patented recently. It is a modular device for installation on façades and roofs, enabling the production of domestic hot water and electricity using solar energy. The main novelty of the system lies in the use of a photovoltaic glass sheet, which improves the building’s aesthetics and facilitates the architectural integration of this type of devices. Thus, a photovoltaic glass is used for the production of electricity, a phase change material for heat storage and a water-phase change material exchanger for the production of domestic hot water. The design and verification stages of the system were developed for a case study under typical usage conditions. Two dimensional numerical models of five different configurations (of the energy harvesting and storage module and two dimensional and three dimensional numerical models of the finned exchanger were carried out to simulate the charge and discharge processes. The most suitable configuration of the system, characterised by a 12 mm vacuum gap and a low emissivity of the absorber, was able to meet the requirements in terms of water flow rate and supply temperature (45 °C) for a shower time of 5 min.

Study on combined optimization technology of wind-solar-storage hybrid power generation based on electricity hydrogen complementarity

The wind-solar-storage hybrid power generation system is mainly composed of wind turbines, solar cell arrays, electrolytic cells, fuel cells, battery packs, intelligent controllers, multi-functional inverters, cables, supports and auxiliary parts to supply power to the load. The system utilizes wind and solar energy for power generation without an external power supply, and an energy storage module composed of an electrolytic cell, fuel cell, and battery is used to assist the power supply. In this paper, a fuel cell model, a wind power generation model and a solar power generation model are respectively constructed, and a small experimental platform was built to validate the model. The pulse width modulation (PWM) control method, combined with the auxiliary regulation of the system by the battery, reduces the impact of the volatility of wind power generation on the electrolytic cell and fuel cell, and makes the load current more stable under different working conditions. The simulation results show that the system has good compression resistance, fast response and good stability.

A DCM-Based Non-Isolated Step-Down DC Transformer

DC transformers have emerged as essential devices for medium voltage DC (MVDC)-low voltage DC (LVDC) distribution systems. However, conventional step-down single-level converters have limits on the voltage level of the MVDC-LVDC distribution system. This paper proposes a non-isolated step-down (NISD) DC transformer based on discontinuous conduction mode (DCM). The proposed structure can withstand high voltage levels by sharing voltages between energy storage modules dividing voltage levels. The proposed NISD DC transformer determines operational modes based on energy storage modules and performs the voltage conversion process. The effectiveness of the proposed NISD DC transformer is verified based on a case study using a power system computer-aided design and electromagnetic transient simulation engine including DC (PSCAD/EMTDC™).

Lighter, long-lasting batteries

The MODALT project is focusing on high-performance energy storage modules made from thermoplastic composites.

A High‐Voltage Mechanical Energy Harvester Using Crank‐Shaft Mechanism for Applications in Toll Stations on Expressways

Due to the continuous increase of expressways and toll stations, there is a high potential for energy harvesting for sideway electronic devices. This article proposes a novel road energy harvester (REH) based on a crank‐shaft mechanism using bidirectional to unidirectional phenomenon to be installed on expressway toll stations. The REH contains four main components: the oscillation input from the suspension, the transfer unit, the generator unit, and the energy storage unit. The REH uses a crank‐shaft with spur gears as a mechanical motion rectifier and one‐way bearings, which can convert the oscillatory vibration into unidirectional generator rotation. In the energy storage module, electrical energy is being stored in supercapacitors. This study covers the design, modeling, and simulation of a crank‐shaft‐based energy harvester for harvesting suspension vibration energy. The energy harvester's dynamic modeling is used to assess the damping features. Simulated tests are conducted to demonstrate the proposed energy harvester's efficacy. Experiments are conducted, and the highest output voltage of 6.9 V peak is recorded for 5 mm/s with an efficiency of 53.66% which is enough for self‐powered applications at expressway toll booths such as traffic lights, caution lights, LED displays, sensors, etc.

Supercapacitor Voltage Doubling Equalization Method Based on Adaptive Grouping

Abstract In order to improve the inconsistency of lithium-ion battery packs, an adaptive grouping supercapacitor voltage-doubling equalization circuit is proposed on the basis of capacitor equalization circuits, which combines switching arrays with clustering algorithms for grouping, and multiple batteries can be equalized at the same moment according to the energy state. The supercapacitor energy storage module can realize parallel energy storage and series energy release, which greatly improves the equalization speed and solves the problem of slowing down the equalization speed at the later stage of equalization. Building six series-connected battery simulation platforms for experiments, the experimental data results show that the scheme proposed in this paper compared with the control group program equalization time is shortened by about 50%, has a faster equalization speed, and can effectively improve the inconsistency of the battery pack, effectively verifying the feasibility of the equalization program and superiority.