Energy Storage最新文献

This paper examines artificial intelligence and blockchain applications for optimizing energy in multi-energy microgrids. It begins with historical energy context and the need for efficient microgrid solutions. The study reviews different energy resources and their conversion processes, followed by an in-depth review of the advanced energy storage systems, including battery, supercapacitor, superconducting magnetic, fuel cell, flywheel, and hybrid energy storage systems. Control of microgrid systems is analyzed for centralized, decentralized, distributed, hierarchical, and predictive controls, discussing their advantages and limitations. Modern control strategies based on artificial intelligence and blockchain are critically reviewed and compared. Artificial intelligence used in microgrid (MG) is discussed in detail, which improves scalability, resilience, and efficiency. Machine learning techniques employed in MG are discussed which enhance the accuracy of predictions in terms of energy distribution, demand, and stability. Finally, around 125 research publications on the subject are also appended for quick reference.

Thermal management of lithium-ion batteries (LIBs) faces challenges in ensuring optimal performance, safety, and lifespan due to excessive heat generation during high power discharging cycles. Recently, nano-enhanced phase change materials have been considered as sustainable passive cooling techniques to enhance the LIBs' performance. Unlike previous studies that focused on single or binary filler systems, this work introduces a novel multicomponent composite phase change material (CPCM) by incorporating varying loadings of expanded graphite (EG), hexagonal boron nitride nanosheets (h-BNNSs), MXene (Ti₃C₂T_x), and epoxy resin (ER) into the matrix of paraffin wax/polyethylene glycol/lauric acid to synergistically enhance thermal performance. Three different CPCM samples (CPCM 1, CPCM 2, and CPCM 3) are synthesized and characterized by XRD, FTIR, and SEM. Thermal properties are evaluated by DSC and TGA. Among all, CPCM 1 results in a maximum latent heat of 153.28 J/g and thermal conductivity of 1.26 W/m K in addition to superior antileakage performance. Additionally, CPCM 1 is applied to a 4S6P LIB module and tested under 1C, 2C, and 3C discharge rates. At 3C, the peak temperature remained within the safe threshold of 50°C with a temperature variation of just 1.91°C between the cells. The battery module retained a capacity of 1207.56 mAh over 50 discharge cycles. The results highlight the potential of the developed CPCM as an effective, lightweight, and energy-efficient passive cooling solution for next-generation LIB thermal management systems.

Underwater Compressed Air Energy Storage (UWCAES) offers a scalable solution for storing intermittent renewable energy. It has high volumetric energy density, does not require cushion gas, provides flexible offshore sites, and requires minimal onshore land use. To date, field-scale validation of such systems in real marine environments, especially at practical depths (> 30 m), remains limited. To address this gap, we present the first field trial of a rigid-tank UWCAES system deployed at depths of 30–70 m in the Red Sea. The system comprises a 294 L rigid PVC tank with an open bottom designed for air–seawater displacement during repeated charging and discharging cycles. Real-time measurements of pressure, temperature, and flow rate were conducted across different outlet nozzle configurations and storage depths. Experimental results demonstrated stable system operation and effective energy delivery. During discharge, the volumetric flow rate remained nearly constant, indicating consistent power output. Increased storage depth led to higher flow rates, highlighting the role of hydrostatic pressure in enhancing system performance. Despite the expected cooling from adiabatic expansion, the compressed air temperature along the submerged hose sections remained close to the local seawater temperature and increased further in the above-water sections. This temperature profile suggested passive thermal buffering from the surrounding seawater and additional warming from ambient air exposure near the outlet. These findings provide new empirical insights into the thermal dynamics, operational stability, and offshore deployment feasibility of UWCAES systems at practical depths.

Perovskite solar cells (PSCs) have rapidly advanced as a next-generation photovoltaic technology due to their high efficiency and flexible fabrication routes; however, the reliance on lead-based absorbers raises concerns regarding toxicity and long-term stability. This study introduces La_0.5Ce_0.5Co_0.9Zn_0.1O₃ (LCCZO), a double perovskite oxide, as a lead-free, stable absorber candidate for eco-friendly PSCs. First-principles calculations validate its crystallographic stability and predict a direct bandgap of ~1.8 eV, suitable for efficient visible-light absorption. Optical analysis reveals strong absorption and favorable dielectric properties, supporting low exciton binding and effective charge separation. Device simulations using SCAPS-1D integrating TiO₂ and NiO as transport layers demonstrate optimal performance upon tuning absorber thickness, carrier density, and defect levels. A maximum power conversion efficiency (PCE) of 23.41% is achieved, with an open-circuit voltage (V_oc) of 1.42 V, short-circuit current density (J_sc) of 18.56 mA cm⁻², and fill factor (FF) of 88.92%. The device exhibits robust tolerance to bulk and interfacial defects, attributed to favorable band offsets and intrinsic defect chemistry. A machine learning model trained on simulated datasets accelerates performance prediction across parameter regimes, achieving ~82.5% accuracy and reducing computation time significantly. These results position LCCZO as a promising lead-free absorber and highlight the synergy of computational design and machine learning for sustainable solar energy development.

Doping ZnFe₂O₄ with Magnesium (Mg) and Manganese (Mn) promotes beneficial defects by tuning the bandgap and enhances the electronic conductivity, along with improvement in the electrochemical performance. Incorporating these dopants optimizes the crystal structure and provides additional active sites, leading to a superior rate capability and improved charge storage capacity compared to pristine ZnFe₂O₄ for the supercapacitors (SCs). Zn_(1−x)Mg_xFe_(2−x)Mn_xO₄ (ZMFMO), with x = 0.00, 0.05, and 0.10, was synthesized using the sol–gel autocombustion technique and confirmed with the physical characterizations, including the detailed X-ray diffraction (XRD), Raman and UV–visible spectroscopy, field emission scanning electron microscopy (FESEM), and energy dispersive X-ray spectroscopy (EDX) analysis. Brunauer–Emmett–Teller (BET) isotherms were analyzed, which show the impact of doping on the surface area. The electrochemical performance of the prepared symmetric coin cell and three-electrode system was explored using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and galvanostatic charging and discharging (GCD) studies. The three-electrode characterization suggests high specific capacitance (C_sp) of 121.5, 130.2, and 162.5 F g⁻¹ for ZMFMO_00, ZMFMO_05, and ZMFMO_10, respectively, while the C_sp was found to be 34.8, 36.4, and 47.3 F g⁻¹ at 1 mV s⁻¹ for ZMFMO_00, ZMFMO_05, and ZMFMO_10 in symmetric coin cells, respectively. It also shows excellent charge–discharge characteristics with a 23.9, 28.6, and 43.6 s discharging time for ZMFMO_00, ZMFMO_05, and ZMFMO_10, respectively, at 392 mA g⁻¹. It illustrates the energy and power density 5.01, 5.08, 8.19 Wh kg⁻¹ and 29.52, 28.09, 28.11 W kg⁻¹ at 39 mA g⁻¹ for ZMFMO_00, ZMFMO_05, and ZMFMO_10 symmetric coin cell devices, respectively. Ex situ XRD analysis was performed to check the electrode stability after long-term cycling. The results indicated that the developed doped nanomaterial exhibits excellent charge storage characteristics, followed by an LED light demonstration.

The rationale for designing cathode material for a high-performance lithium-sulfur (Li-S) battery, which offers high-rate capability and stability for energy storage applications, has been adopted in this work. Sodium carbonate solution was utilized as a catalyst to prepare porous carbon aerogels from resorcinol and formaldehyde via freeze-drying and carbonization at 800°C in an N₂ atmosphere. The synthesized materials were used as a composite with sulfur to fabricate electrodes for Li-S batteries. The prepared carbon/sulfur composite (HG-40%) delivered an initial capacity of 1510 mAh/g at 0.25 C with a very high level of reversibility. The cycling tests showed very good stability at 1 C, maintaining a discharge specific capacity of about 71% of the initially recorded value (from 639 to 455 mAh/g) after 500 cycles. These performances can be attributed to the improvement in accommodating more active species, resulting in a shorter ionic path within the aerogel-based carbon matrix. This research opens a new avenue for synthesizing and fabricating cathode materials for high-performance Li-S batteries, benefiting the electrochemical industry.

The increasing global population and rapid depletion of energy resources have intensified the demand for renewable energy and advanced energy storage solutions. Supercapacitors, with their high power density, long cycle life, and fast charging capability, are emerging as a promising alternative to conventional batteries. This study reports, for the first time, the capacitive performance of a bimetallic FeNi metal-organic framework (MOF) combined with multi-walled carbon nanotubes (MWCNTs) on a carbon felt electrode. The composite was synthesized via a hydrothermal route and applied through a drop-casting method. Electrochemical performance was evaluated using cyclic voltammetry, electrochemical impedance spectroscopy, and galvanostatic charge–discharge techniques. The resulting electrode demonstrated a specific capacitance of about 180 F/g over a wide current density range, nearly 100% coulombic efficiency, a power density up to 3600 W/kg, and an energy density of about 91 Wh/kg. Moreover, it retained 90% of its capacity after 700 charge–discharge cycles, underscoring its stability. These findings highlight the FeNi MOF-MWCNT composite as a promising candidate for high-performance supercapacitor electrodes.

In deregulated power systems, maintaining stable load frequency control (LFC) is increasingly challenging due to the integration of diverse energy sources and the unpredictable nature of demand and generation. Traditional control strategies often struggle to provide robust performance under these dynamic conditions, especially when contract violations occur. Additionally, ensuring frequency stability across multi-area grids with mixed energy profiles especially integration of hybrid energy storage systems, requires advanced and adaptive control mechanisms. This paper proposes a novel application of the Slime Mold Algorithm (SMA) to optimize a novel TIIDN-P controller under a deregulated environment. This paper also proposes a novel three-area hybrid power system. Each area comprises a thermal power plant integrated with a renewable energy source and a dedicated energy storage system (ESS): Area 1 includes a wind turbine, Area 2 features geothermal energy, and Area 3 incorporates biogas. The proposed system is chosen since it has not yet been investigated and those energy sources are easily available in India. By leveraging the adaptive search capabilities of SMA, the proposed TIIDN-P control strategy achieves significantly improved frequency regulation performance compared to other controllers. In comparison to PSO (Particle Swarm Optimization), FA (Firefly Algorithm), GWO (Grey Wolf Optimizer) and MBA (Mine Blast Algorithm), the proposed algorithm reduced settling time significantly up to 40% for different areas' frequency. Simulation results confirm that TIIDN-P controllers offer superior dynamic response, reduced overshoot, and enhanced robustness under varying system conditions. The integration of hybrid ESS configurations not only stabilizes system frequency but also effectively mitigates the impact of uncontracted power fluctuations. Sensitivity analysis further validates the resilience of the proposed approach. The sensitivity analysis proved that the proposed system as well as the controller, is robust enough in various cases. The stability analysis using eigenvalue analysis revealed that the proposed system is stable in various conditions. Moreover, this paper presents an intensive comparison of various types of Energy Storage Systems and their hybrid systems to find out the best ESS and the best hybrid system which is the first-ever of its kind. An investigation reveals that RFBESS and FWESS hybrids are the best option from the case study.

The most prominent transition has all to do with the electric vehicles within the evolving technological environment facing rapid advancement today. Effective thermal performance of an electric vehicle battery pack is of utmost importance, in terms of both safety and performance, longevity. In this review a context of conductive composite materials in battery heat exchange systems (BHES) is explored, thus giving indication into the importance of architecture in optimizing heat transfer within EV battery modules. The ultimate aim is to present up-to-date developments in material science that will improve the thermal performance of battery thermal management systems (BTMS), achieve uniform heat distribution, and increase battery efficiency. In this regard, future aspects' emphasis is put on porous foam composites incorporating phase change materials (PCM), which are highly promising in improving thermal regulation under variable operational conditions. This study is something different from previous reviews because this article particularly highlights conductive composite phase change materials in thermal regulation for EV battery packs and recent advances. The review will also give a comparative account of conventional and advanced cooling methods, the challenges of which mainly lie in material integration and costs and will point toward possible futures of research and development in thermal management strategies for EV batteries.

Charging strategy optimization for lithium-ion batteries is crucial to improve the efficiency of new energy devices. In this study, three conventional methods are compared: constant-current constant-voltage (CCCV) charging is the most efficient but slowest, pulse charging (PC) is the fastest but least efficient, and multistage constant-current (MSCC) is a compromise between speed and efficiency. To this end, we propose a dynamic optimal charging strategy based on model predictive control (MPC) that balances rapid-charging speed with battery safety. By integrating a low-order electrochemical–thermal–aging coupled model with real-time state estimation provided by an extended Kalman filter (EKF), a rolling-horizon framework is established to track both state-of-charge (SOC) and temperature reference trajectories. Experiments show that EKF has stronger initial error robustness (maximum deviation < 2%) than unscented Kalman filter (UKF) and unscented Kalman Bucy filter (UKBF), which provides reliable feedback for MPC. The new strategy achieves an optimal balance between charging efficiency and safety by dynamically adjusting the charging profile and significantly improves the charging speed under closed-loop control compared to the CCCV method, while controlling the temperature rise within 5°C.