Design Of Energy Storage System Research Articles

High Performance Sodium‐Ion Hybrid Capacitor Based on Graphene‐Tin Pyrophosphate Nanocomposite Anode

AbstractThe development of alternative energy storage technologies such as sodium‐ion hybrid capacitors, which do not rely on critical raw materials such as cobalt or nickel, for the replacement of conventional lithium‐ion batteries for some niche applications, is extremely important to successfully achieve a sustainable development in our planet. In this work, we introduce a novel sodium‐ion hybrid capacitor system formed by the combination of an optimized nanostructured composite material containing reduced graphene oxide and tin pyrophosphate as negative electrode, and a high specific surface area graphene‐carbon composite as positive electrode. The electrochemical performance of each material has been individually evaluated using NaPF6 in EC/DMC as electrolyte, showing impressive specific capacity values above 100 mAh g−1 at 2 A g−1, for both faradaic and capacitive‐type electrodes. The integration of the electrodes in an optimized full cell with anode‐to‐cathode mass balance of 1.5 : 1, enabled stable full cells that can provide energy densities of almost 60 Wh kg−1 at 3,000 W kg−1, showcasing the potential of these type of materials in the design of next generation energy storage systems.

Thermal runaway comparison and assessment between sodium-ion and lithium-ion batteries

Sodium-ion batteries (SIBs) have attracted significant attention in the field of electrochemical energy storage. However, limited research exists on the thermal runaway (TR) phenomenon of SIBs. To address this gap, the TR behaviors of Sodium-ion, LiFePO4 (LFP), and LiNi0.5Co0.2Mn0.3O2 (NCM523) batteries of the same size under different heating powers (300W, 400W, and 500W) are investigated in this paper. Compared to prior studies, the main contribution of this work lies in studying and evaluating the effect of heating power on the thermal and gas production hazards of SIBs. Two significant conclusions are drawn: (Ⅰ) the effect of heating power on gas production and heat generation in SIBs is not consistent, with the increase of heating power, the thermal hazard of SIBs increases significantly, while the internal TR propagation and gas production hazard are reduced; (Ⅱ) the TR hazard of SIBs is between NCM523 and LFP batteries as shown by TR hazard assessment model based on radar map. This study reveals the influence of heating power on the TR propagation and gas production behavior of SIBs and provides valuable insights for the safety design of sodium-based energy storage systems.

Design and economic analysis of compressed air energy storage systems for enhanced energy output

ABSTRACT This research explores the optimization of Compressed Air Energy Storage systems (CAES). It focuses on finding the ideal combination of input factors, namely the motor size and gearbox ratio (GBR), to maximize energy output. The study employs factorial design of experiments and analyzes the impact of the previously mentioned factors on system performance. Additionally, the study utilizes the output results recorded after optimizing these factors to compare the Levelized Cost of Storage between CAES and Lithium Iron Phosphate battery technologies. The findings suggest that a medium-sized motor paired with a 2:1 gear ratio is optimal for CAES, offering enhanced energy output. The research underscores the importance of precise component selection in CAES system design and highlights the economic advantages of CAES with $4/kWh over battery storage with $28.66/kWh, particularly in large-scale energy storage applications.

Experimental validation of the design and control of a compressed air energy storage system

Experimental validation of the design and control of a compressed air energy storage system

Optimal capacity determination of photovoltaic and energy storage systems for electric vehicle charging stations

With the growing interest in integrating photovoltaic (PV) systems and energy storage systems (ESSs) into electric vehicle (EV) charging stations (ECSs), extensive research has focused on methods to increase the profits of ECS operators (ECSOs). Conventional studies have primarily relied on empirical methods, such as assuming a constant value for the power conversion system (PCS) capacity or modeling it as being dependent on the battery capacity, to design ESSs. However, such empirical methods can lead to suboptimal or excessive determinations of the capacity of a facility. This study proposes a battery-independent PCS model that independently models the battery and PCS capacities in ESS design to overcome the limitations of the conventional model and maximize the profit for ECSOs. The proposed model determines the optimal capacity of ESS and PV to maximize ECSO's profit. The nonlinearities that arise from using a battery-independent PCS model are linearized by the BIG-M method to effectively solve the optimization problem. The proposed model achieved an additional profit of up to 1.5 % compared to the conventional model. Additionally, the proposed model was simulated under various conditions (e.g., decreasing capital investment costs of ESS, changing EV charging demand, changing time-of-use rates, and applying real-time price rates). Accordingly, it is confirmed that the proposed model greatly contributes to improving ECSO profit even under various conditions. Moreover, the proposed model offers a means to determine the optimal capacities of PV and ESS in an ECS, ultimately maximizing ECSO profits.

A Machine Learning Approach for Understanding the Oxygen Vacancy Formation Energies within DRX Cathode Structures

Disordered Rock-Salt (DRX) cathode structures are materials where lithium and transition metal atoms are arranged in a disordered solid solution. These structures are currently under intensive study [1] due to their potential higher energy density, bigger capacity than the typical layered cathode structure, and improved flexibility in the selection of raw materials. Driven by this, we have recently compiled a DFT-based database of DRX structures with over 6,000 different metal oxide compositions. Moreover, since oxygen loss is linked to voltage degradation, intergranular cracks, and irreversible phase transformation, developing a descriptor that allows us to understand and reflect the stability of oxygen within the DRX anion lattice is crucial. It represents a significant research challenge that our study aims to address.In this work, we study two things: First, since the generation of oxygen vacancies holds a critical value in elucidating the stability of cathode material oxides[2], our methodology focuses on generating an extensive DFT database of over 1,400 oxygen vacancy formation energies (Evf(O)) from selected DRX structures. We then employ a machine learning (ML) model to predict the Evf(O) and their distribution for a variety of different compositions. The ML model incorporates site-specific features, such as the maximum reduction potential of the cations neighboring the O vacancy, the O p-band center of mass, and information from atomic population analysis (such as the bond order and the bond spin polarization between each O and its nearest neighbors). This approach is necessary because the DRX structure contains different local environments where O vacancies could be created, and recent work from Baldassarri et al. has highlighted the limitations of ML models that only include global features and lack their ability to differentiate the behavior of compounds containing the same elements but in different oxidation states [3]. This allows us to predict the O vacancies energetics with an accuracy comparable to DFT and to develop a descriptor to classify different compositions of DRX structures.Second, given that oxygen destabilizes during delithiation, we analyze the impact and relationship of the Li vacancy formation energies (Evf(Li)) and Evf(O) of each O able to create a vacancy. The results show a strong interaction between these energetics, and in particular, an inverse correlation between Evf(O) of a specific O site and the Evf(Li) of the Li atoms that surround this O, which within these DRX prototypes the number of surrounding Li varies from 1 to 5. In line with what others proposed [4], there is a strong interaction between these two vacancy types. However, we expect that the generation of O vacancies is determined not only by their thermodynamic driving force but also by the displacement/migration of the nearest neighbor lithium (NN-Li) that surrounds each O.The methodology and fundamental understanding developed in this study about DRX O-vacancies and their relationship with NN-Li during delithiation could help investigate and describe compositionally similar transition metal oxide cathodes belonging to the same crystal structure family (layered, spinel-like, γ-LiFeO2). Hence, this research not only enhances our understanding of these materials but also paves the way for the design and development of more flexible and stable energy storage systems.[1] S. Anand, B. Ouyang, T. Chen, G. Ceder, Impact of the energy landscape on the ionic transport of disordered rocksalt cathodes, Physical Review Materials 7(9) (2023) 095801.[2] H. Zhang, B.M. May, F. Omenya, M.S. Whittingham, J. Cabana, G. Zhou, Layered Oxide Cathodes for Li-Ion Batteries: Oxygen Loss and Vacancy Evolution, Chemistry of Materials 31(18) (2019) 7790-7798.[3] B. Baldassarri, J. He, A. Gopakumar, S. Griesemer, A.J.A. Salgado-Casanova, T.-C. Liu, S.B. Torrisi, C. Wolverton, Oxygen Vacancy Formation Energy in Metal Oxides: High-Throughput Computational Studies and Machine-Learning Predictions, Chemistry of Materials 35(24) (2023) 10619-10634.[4] C. James, Y. Wu, B.W. Sheldon, Y. Qi, The impact of oxygen vacancies on lithium vacancy formation and diffusion in Li2-xMnO3-δ, Solid State Ionics 289 (2016) 87-94.

Design and thermodynamic performance analysis of a novel adiabatic compressed air energy storage system based on liquid piston re-pressurization

Compressed air energy storage (CAES) is a crucial technology for integrating renewable energy into the grid and supporting the “dual carbon” goals. To further utilize compressed heat and reduce throttling losses, this paper proposes a novel A-CAES energy storage system with liquid piston re-pressurization (LP-A-CAES). During the energy release process, the air in the air storage tank enters the liquid piston directly without passing through the throttle valve, then undergoes further pressurization and expansion. This approach avoids throttling losses while increasing the expansion ratio of the expander, facilitating the efficient use of compressed heat. By establishing thermodynamic models for both the proposed re-pressurized A-CAES and the traditional A-CAES systems, we compare their performance variations with changes in key parameters. Results indicate that under design conditions, the system's energy efficiency is 70.74 %, a 5.07 % improvement over traditional throttle-based A-CAES systems. The total exergy loss of the system is 1.42 × 1010 J, with the compressor and expander units accounting for the largest exergy losses, at 32 % and 31.6 %, respectively. The liquid piston exhibits excellent isothermal performance, maintaining air and water temperature rises within 20 K and 2.5 K, respectively. Reducing the maximum pressure difference in the air storage tank enhances system performance, although the performance improvement of the re-pressurized A-CAES system compared to the traditional A-CAES system diminishes. Increasing the height of the thermal energy storage and reducing the diameter of the thermal storage material both contribute to higher system energy efficiency. When the height of the thermal energy storage increases from 4 m to 8 m, the system's efficiency rises from 70.04 % to 70.74 %. Similarly, reducing the diameter of the thermal storage material from 0.05 m to 0.01 m increases the system's efficiency from 68.85 % to 71.47 %.

Ultra-high rate and long cycle life sodium-based dual-ion batteries enabled by Li2TiO3-modified cathode-electrolyte-interphase

Sodium-based dual-ion batteries (SDIBs) have received widespread attention due to their high voltage, low cost, safety, and eco-friendliness. Nevertheless, the irregular spherical graphite cathodes are limited by the mass transfer non-uniformity and sluggish reaction kinetics due to uneven anion migration through the highly tortuous pathways and the inductive anisotropic electric fields. Herein, we report a facile dissolution-precipitation-carbonation optimized modification strategy to synthesize a series of nano-Li2TiO3/C-modified graphite flake (GF-LTx, x = 1, 2.5, and 5) as cathode for SDIBs. The Li2TiO3-C-Cathode Electrolyte Interphase (Li2TiO3-C-CEI) trinity layer by in situ reactions shows good cycling performance. The intrinsic mechanism of Li2TiO3-C-CEI was further explored by DFT molecular orbital theory and distribution relaxation time (DRT) analysis. Notably, the GF-LT2.5 achieves 10,000 stable cycles at 3–5.2 V (vs. Na/Na+) with a initial capacity of 91.1 mAh g−1 and a decay rate of only 0.00217 % per cycle. Furthermore, GF-LT2.5 demonstrates an ultra-high rate performance of 100C with only 30 s for a single charge and 86 % capacity for low current density. Infrared thermography confirms the good thermal stability and safety of the gel-based flexible pouch cells. This work provides new insights into the design of high-rate performance, long-cycle stability, and high-safety energy storage systems.

Controller design and optimal sizing of battery energy storage system for frequency regulation in a multi machine power system

Frequency regulation is one of the key components needed to keep the power grid stable and reliable in the case of an imbalance between generation and load. This study looks at several control techniques for Battery Energy Storage Systems (BESSs) to keep the frequency stable in the power system during generation/load disruptions. This research aims to build several BESS controllers, including the proportional-integral (PI), proportional integral derivative (PID), and Tilt-Integral Derivative (TID) controllers. Also, the BESS controller parameters are optimized and compared by using metaheuristics based particle swarm optimization (PSO) and the BAT algorithm. However, for practical power systems with high MVA ratings, the size of the battery energy storage systems has to be increased considerably to offset frequency deviations. Additionally, by utilizing PSO to reduce the frequency deviations within prescribed limits, this work presents the optimal BESS sizing for multimachine power systems. Furthermore, the research study examines the impact of BESS connected to various voltage levels, such as LV, MV, and HV subgrids. It also examines BESS's role in frequency management, which is an area of expertise that needs further investigation and is anticipated to have a big influence on the frequency stability of the system. Time domain simulations are carried out, which shows that the PSO based controller design is capable of stabilizing the system frequency with superior performance as well as the BESS's capability to participate effectively in frequency regulation. Additionally, this paper also implements the experimental verification through Hardware-in-the-Loop (HIL) simulations to validate the performance and robustness of the proposed control system. The WSCC 9-bus test system is used to demonstrate the BESS's efficacy. The system is modelled and simulated using the DIgSILENT PowerFactory software.

Explosion characteristics of two-phase ejecta from large-capacity lithium iron phosphate batteries

When a thermal runaway accident occurs in a lithium-ion battery energy storage station, the battery emits a large amount of flammable electrolyte vapor and thermal runaway gas, which may cause serious combustion and explosion accidents when they are ignited in a confined space. With the gradual development of large-scale energy storage batteries, the composition and explosive characteristics of thermal runaway products in large-scale lithium iron phosphate batteries for energy storage remain unclear. In this paper, the content and components of the two-phase eruption substances of 340Ah lithium iron phosphate battery were determined through experiments, and the explosion parameters of the two-phase battery eruptions were studied by using the improved and optimized 20L spherical explosion parameter test system, which reveals the explosion law and hazards of the two-phase battery eruptions. Studies have shown that in a two-phase system explosion, EMC can make the two-phase system more explosive and more powerful, and the thermal runaway gas expands its explosion concentration range. The coupling explosion of the two enhanced the sensitivity and explosive power of the two-phase ejecta. Increasing the concentration of any combustible in a two-phase system will cause the explosion intensity parameters of the system to increase. However, when the combustible concentration exceeds the optimal explosion concentration, the explosion intensity parameters will decrease or even no explosion will occur. Both explosion intensity parameters and sensitivity parameters are more sensitive to EMC concentration, and the higher the EMC concentration, the stronger its dominant role in the explosion of the two-phase system. This work can lay the foundation for revealing the disaster-causing mechanism of explosion accidents in lithium-ion battery energy storage power stations, guide the safe design of energy storage systems and the prevention and control of explosion accidents, and provide theoretical and data support for the investigation of explosion accidents in energy storage power stations.

3D printing and micro-spring architecting to reconcile ultra-high areal and volumetric energy density in highly loaded supercapacitors

The rigorous demand for significantly enhanced performance gains in metrics of areal and volumetric energy density from futuristic energy storage devices is driving current technological endeavors towards the design of highly-loaded energy storage systems. The advancement of supercapacitors has faced a formidable challenge in reconciling ultra-high areal (>1 mWh cm−2) and volumetric performance (>10 mWh cm−3) due to the intricate issue of efficient mass transport in a highly loaded environment. Here, the capability of 3D printing technology to architect open frameworks is well leveraged in conjunction with material interface decoration to create a heavily loaded pseudocapacitive MnO2 electrode of low structural tortuosity and fast surface reaction. By harnessing the potential of self-assembly, a robust electrode composed of ubiquitous micro-springs is developed, permitting elastic strain engineering that exceptionally augmented the volumetric performance while preserving efficient mass transport pathways for reasonable kinetics. Coupling with these features, a groundbreaking achievement is attained as an individual supercapacitor unit now boasts an unprecedented ultrahigh areal energy density of 2.83 mWh cm−2 and volumetric energy density of 37.3 mWh cm−3. The proposed strategy provides an informative roadmap benefiting the construction of next-level electrochemical energy storage devices.

Design of photovoltaic and battery energy storage systems through load demand characterization: A case study in Thailand

The integration of photovoltaic (PV) system at behind the meter has gained popularity due to the growing trend toward environmentally friendly energy solutions. Coupling PV systems with battery energy storage systems (BESS) addresses the uncertainties of PV energy production while enhancing energy management. Load characteristics have influence on PV and BESS design both in technical and economic aspects. This paper presents a comprehensive analysis of load demand characterization methodologies tailored for the design of PV and BESS. The fundamental load properties such as daily maximum power, minimum power, and load energy, categorizing loads based on their daily and annual variation degrees are investigated. The techno-economic performance of PV-only and PV+BESS systems is analyzed, focusing on metrics such as excess energy, peak limiting performance, and economic feasibility using the levelized cost of energy (LCOE). The findings of this study reveal three distinct load characteristics based on daily variation: moderate (50–70 %), moderate to high (70–80 %), and high (80–90 %). Load profiles with moderate variation (50–70 %) demonstrate economic feasibility when sized with a PV-only system matching maximum power demand. With BESS prices reduced to less than 140 USD/kWh, these loads could also integrate a 1C-BESS sized at half capacity under the same control strategy, resulting in lower excess energy and LCOE. Conversely, loads with higher variation (>70 %) and lower self-consumption rates (<70 %) face fewer viable options for both PV-only and PV+BESS configurations, especially if BESS costs remain high. These loads require custom-designed solutions and more extensive load analysis. Through analysis, this study establishes the relationship between load characteristics and system design suitability for the loads studied. The findings underscore the importance of incorporating load demand characterization techniques in the design systems, highlighting the need for tailored approaches based on specific load characteristics and economic viability.

Thermal equalization design for the battery energy storage system (BESS) of a fully electric ship

The adoption of fully electric ships represents a significant step forward in addressing the environmental challenges of climate change and pollution in the shipping industry. This research details the optimized design of a battery energy storage system (BESS) and its air-cooling thermal management system for a 2000-ton bulk cargo ship. In comparison to the conventional flow splitter (FS-I), which divides airflow into 8 transverse branches, two novel designs—FS-II (dividing airflow into 2, 4, and 8 branches) and FS-III (dividing into 2, 4, 8, and 16 longitudinal and transverse branches)—were introduced. FS-II improves flow uniformity from 0.42 (FS-I) to 0.86 but results in an increased pressure drop up to 881.47 Pa. FS-III further enhances flow uniformity to 0.97 while reducing pressure drop to 191.99 Pa. Under extreme conditions and the entire voyage cycle, the comprehensive assessment of thermal performance was conducted on three battery boxes with FS-I, FS-II, and FS-III, respectively. FS-III exhibited superior thermal regulation, maintaining Tmax consistently below 33.9 °C during the entire voyage. These findings provide valuable insights for designing thermal management systems in electric ships.

Proposal design and thermodynamic optimization of an afterburning-type isothermal compressed air energy storage system integrated with molten salt thermal storage

The isothermal compressed air energy storage is a potential technique for large-scale energy storage. In this study, the molten salt thermal storage is integrated with the afterburning-type isothermal compressed air energy storage system, which uses liquid piston compression technique, to enhance the thermal performances. Thermodynamic models of the hybrid energy storage system were developed, and the genetic algorithm was used to optimize multiple parameters to enhance the energy efficiency. Four operation modes, i.e., the high, medium-high, medium-low, and the low output power modes were proposed, to enhance the operational flexibility of the hybrid energy storage system. When the system operates in the operation mode of medium-low output power, a portion of afterburning heat is stored in the molten salt and used in the operation mode of low output power. Results show that the roundtrip efficiency of high, medium-high, medium-low, and the low output power modes are 63.57 %, 59.33 %, 57.13 %, and 83.28 %, respectively. Exergy analysis was carried out to quantify the irreversibilities of key components. In the three modes of operation with afterburning, the combustion chamber has the highest portion of exergy loss, and in the operation mode without afterburning, the exergy loss of heat exchangers is higher than that of expanders.

Thermal analysis of packed bed thermal energy storage system with dimpled spherical capsules

The thermal storage potential of a packed bed filled with paraffin wax capsules was examined. Heat transfer fluid (HTF) at 70 °C inlet temperature for dimpled and plain stainless-steel capsules was compared for three different flow rates, 1 L/min, 3 L/min and 5 L/min. In general, dimpled spherical capsules sustain more heat than plain spherical capsules at the same flow rate, according to instantaneous and cumulative heat stored. Spherical capsules with dimples exhibited a 30 % improvement in charging rate compared to smooth spheres, particularly at elevated flow rates. Specifically, at a flow rate of 5 L/min, dimpled capsules achieved faster charging and sustained higher temperature compared to plain capsules. Higher flow rates (3 and 5 L/min) result in steeper temperature increases and an earlier peak temperature phase compared to the lower flow rate (1 L/min). Key dimensionless heat transfer numbers were examined. The Stefan number was found to be 0.1966 for an HTF inlet temperature of 70 °C and a latent heat of fusion (Lm) of 213 kJ/kg. Heat transfer increases when Reynolds numbers increased from laminar (123.8 at 1 L/min) to turbulent (619.1 at 5 L/min). Rayleigh number decreased over time but increased for dimpled capsules, indicating improved convection. Dimpled capsules had higher Nusselt numbers and increases with flow rate, indicating better convective heat transfer. Dimpled capsules absorbed heat faster and stored more energy, giving them a viable and efficient Packed Bed Latent Thermal Energy Storage system design.

A Perspective on the Process and Turbomachinery Design of Compressed Air Energy Storage Systems

Abstract The present paper will describe the Baker Hughes experience in the development of the turbomachinery equipment for Hydrostor's advanced compressed air energy storage (A-CAES) system. At the core of a compressed air energy storage (CAES) plant, there is an air compressing system, followed by an air expander used to recover the stored energy. To achieve a reliable and effective solution, the expander is obtained from the architecture of Baker Hughes steam turbines, which was adapted to match the specific process needs. The criticalities that were addressed and solved to derive the expanders from the original steam turbine are presented. Specifically, the paper describes the activities performed to optimize the inlet and exhaust sections of each segment, the development of the blades for high atmospheric volume flow, and the implications that thermal transients have on the machine reliability. The inlet and exhaust sections were arranged according to the layout constraints, which were set to mitigate the effects of the thermal stresses and to reduce the weight to facilitate the machine transportation, while maintaining high aero-performance. As for the expander, a single-body configuration was selected to optimize capital expenditures and reduce leakage to atmosphere. A new set of blades derived from Baker Hughes's Steam Turbine stages were developed. This new stage is characterized by rotating blades with high radius ratio (HRR); therefore, an optimization strategy was adopted to include the mechanical constraints from the beginning of the design cycle and obtain a final geometry that can be used with different flow path and operating conditions. Finally, the three-dimensional full Navier Stokes Computational fluid dynamics analysis was used to assess the performance of the new stages in nominal and off-design conditions. A detailed analysis of the thermal transient of the expander parts with finite element analysis methods was performed to assess the life expectations of the equipment. The finite element analysis results are discussed in the paper to show the capability of the machine to sustain an extremely fast start up sequence. Compressor train is characterized by a multiple body configuration. A detailed optimization was performed to improve the efficiency and the availability of the selected solution. The low-pressure axial compressor discharge section has been optimized to reduce losses and a detailed study of rotor has been performed to evaluate the capability to withstand a high number of start and stop cycles.

Application of hydrogen storage in polygeneration microgrids: Case study of wind microgrid in India

Renewable energy based stand-alone microgrids are highly promising to supply electricity to isolated communities and remote locations. However, both buffer and long-term energy storage are essential due to the highly intermittent nature of renewable sources. By employing hydrogen energy storage with fuel cell and electrolyser in these microgrids, multiple outputs such as electricity, heat, water, and fuel, can be achieved. Design, development and optimization of efficient energy storage system remain a key challenge for the stand-alone microgrid technology. One must ensure that the microgrid satisfies the required electric load but is not over-designed, which is achieved by limiting the two performance parameters i.e., unmet electrical load fraction and excess electricity fraction. The capacities of wind turbine, electrolyser and hydrogen storage are optimized corresponding to the limiting values of unmet electrical load (fUL) and excess electricity (fEX) below 10 %. For the location of Ladakh which has rich availability of wind resource, the optimum size of microgrid is observed to be smallest as WT-20 kW, El-20 kW, H2-15 kg with fUL and fEX as 6.4 % and 8.9 % respectively. The Levelised Cost of Energy (LCOE) is also minimum as 0.89 $/kWh for the location of Ladakh. The distribution of wind resource has significant impact on the size of hydrogen storage. Uniform wind energy with higher velocity round the year reduces the capacity of hydrogen energy storage. Kanyakumari has non-uniform wind resource across different months of the year corresponding to which the capacity of H2 storage is as high as 370 kg.

Analysis and characterization of residual salts from lithium carbonate industry: Their potential uses for thermal storage systems

The increasing demand for clean energy and the urgent need to reduce greenhouse gas emissions have led to a growing awareness of the importance of thermal energy storage systems in the diversification of the electric matrix. Sensible heat and latent heat storage are the two main techniques, and the choice of storage system depends on the melting point of the substances and the thermal energy required for the processes. This study focused on waste salts obtained from the production process of lithium carbonate. The thermophysical properties of these salts, including specific heat, density, and thermal stability, were examined through various characterization techniques such as X-ray diffraction, chemical analysis, scanning electron microscopy, thermogravimetry, and differential scanning calorimetry. The results revealed promising thermal properties, chemical stability, and physical availability of the waste salts. Additionally, the study explored the potential benefits of reutilizing these waste salts, such as reducing environmental impact, promoting circular economy principles, and creating new market opportunities for commercial products. Overall, this research provides valuable insights into the thermophysical properties of waste salts from lithium carbonate production. The main results are heat capacity in the solid phase (0.767–3.143 J/g°C) and storable thermal energy (114–1153 TWht). These findings contribute to the design and optimization of thermal energy storage systems, highlighting the potential for sustainable and efficient energy storage solutions in the context of global clean energy transitions.

Hierarchical CuO nanosheets encasing nanorods via a singular potential-cycling activation: Innovations in supercapacitor energy density and longevity

Copper oxides (CuO), by virtue of their exceptional electrical conductivity, benign environmental profile, and economic viability, have emerged as indispensable constituents in the design and development of binder-free electrodes for advanced supercapacitor systems. The ongoing quest for the synthesis of CuO nanomaterials through gentle yet economically feasible methodologies held considerable promise for broadening their applicability within the domain of energy storage devices. In this investigation, a novel architectural innovation was achieved through the integration of carbon nanotubes (CNTs) within the framework of an in-situ electrooxidation process, culminating in the formation of a distinctive CuO-CNT nanorod configuration. Subsequent to this fabrication, the electrode material was subjected to an extensive cyclic voltammetry (CV) activation for 2000 cycles, which precipitated a profound morphological evolution. This process resulted in the emergence of 2D hierarchical nanosheet arrays enveloping 1D nanorods, a configuration herein designated as CuO-CNT-2000. This meticulously engineered lamellar structure conferred upon the material an extraordinary specific surface area, quantified at 219.6 m2 g⁻1, and an impressive specific capacitance of 709.1 F g⁻1. Moreover, the asymmetric supercapacitor (ASC) assembled utilizing this advanced material exhibited a remarkable energy density, measured at 38.09 Wh kg⁻1. Notably, even after enduring 60,000 charge-discharge cycles, the device demonstrated a retention of 82.36 % of its initial energy density, coupled with a Coulombic efficiency of 99.43 %, thus attesting to its superior electrochemical stability and longevity. The efficacy of the CV activation technique in facilitating significant morphological refinement, augmenting the specific surface area, and enhancing the electrochemical performance of the material suggests a broad applicability of this method to a diverse array of other electrode materials, potentially revolutionizing the design and fabrication of next-generation energy storage systems.

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.