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Keywords = Battery Energy Storage System

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20 pages, 5514 KiB  
Article
The Tailored Surface Oxygen Vacancies and Reduced Optical Band Gap of NiO During the Development of NiO@Polyaniline Hybrid Materials for the Efficient Asymmetric and Oxygen Evolution Reaction Applications
by Fida Hussain, Wanhinyal Dars, Rabia Kanwal, Jethanand Parmar, Ghansham Das, Ahmed Raza, Haresh Kumar, Rameez Mangi, Masroor Ali Bhellar, Ambedker Meghwar, Kashif Ali, Aneela Tahira, Muhammad Ali Bhatti, Elmuez Dawi, Rafat M. Ibrahim, Brigitte Vigolo and Zafar Hussain Ibupoto
Catalysts 2025, 15(6), 508; https://doi.org/10.3390/catal15060508 (registering DOI) - 22 May 2025
Abstract
This study employed a simple and cost-effective method for developing NiO with reduced optical band gaps that can be combined with nanostructured polyaniline (PANI). The composite systems were used as electrocatalytic and electrode materials in oxygen evolution reactions (OER) and in supercapacitor applications. [...] Read more.
This study employed a simple and cost-effective method for developing NiO with reduced optical band gaps that can be combined with nanostructured polyaniline (PANI). The composite systems were used as electrocatalytic and electrode materials in oxygen evolution reactions (OER) and in supercapacitor applications. We prepared the composite material in two stages: NiO was prepared with a reduced optical band gap by combining it with wheat peel extract. This was followed by the incorporation of PANI nanoparticles during the chemical oxidation polymerization process. A variety of structural characterization techniques were employed, including scanning electron microscopy (SEM), powder X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, UV-visible spectroscopy, and X-ray photoelectron spectroscopy (XPS). A surface-modified NiO/PANI composite with enhanced surface area, fast charge transfer rate, and redox properties was produced. When NiO/PANI composites were tested in KOH electrolytic solution, 0.5 mL of wheat peel extract-mediated NiO/PANI demonstrated excellent electrochemical performance. It was found that the asymmetric supercapacitor (ASC) device had the highest specific capacitance of 404 Fg−1 at a current density of 4 Ag−1. In terms of energy density and power density, the ASC device was found to have 140 Whkg−1 and 3160 Wkg−1, respectively. The ASC device demonstrated excellent cycling stability and charge storage rates, with 97.9% capacitance retention and 86.9% columbic efficiency. For the OER process, an overpotential of 320 mV was observed at a current density of 10 mA/cm2. It was found that the NiO/PANI composite was highly durable for a period of 30 h. A proposed hypothesis suggested that reducing the optical band gap of NiO and making its composites with PANI could be an appealing approach to developing next-generation electrode materials for supercapacitors, batteries, and fuel cells. Full article
(This article belongs to the Special Issue Advances in Biomass-Based Electrocatalysts)
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22 pages, 2159 KiB  
Article
Energy Cost Centre-Based Modelling of Sector Coupling in Local Communities
by Edvard Košnjek, Boris Sučić, Mojca Loncnar and Tom Smolej
Energies 2025, 18(11), 2688; https://doi.org/10.3390/en18112688 - 22 May 2025
Abstract
This paper presents an analysis of energy use and sector coupling in a local energy community using a model based on energy cost centres (ECCs), functional units for decentralised responsibility and optimisation of energy use within defined system boundaries. The ECC model enables [...] Read more.
This paper presents an analysis of energy use and sector coupling in a local energy community using a model based on energy cost centres (ECCs), functional units for decentralised responsibility and optimisation of energy use within defined system boundaries. The ECC model enables structured identification and optimisation of energy and material flows in complex industrial and urban settings. It was applied to a case study involving an energy-intensive steel plant and its integration with the surrounding community. The study assessed the potential for renewable electricity production (7914 MWh annually), green hydrogen generation, battery storage, and the reuse of 11,440 MWh of excess heat. These measures could offset 9598 MWh of grid electricity through local production and savings, reduce natural gas use by 4,116,850 Nm3, and lower CO2 emissions by 10,984 tonnes per year. The model supports strategic planning by linking sectoral actions to measurable sustainability indicators. It is adaptable to data availability and stakeholder engagement, allowing both high-level overviews and detailed analysis of selected ECCs. Limitations include heterogeneous data sources, uneven stakeholder participation, and the need for refinement of sub-models. Nonetheless, the approach offers a replicable framework for integrated energy planning and supports the transition to sustainable, decentralised energy systems. Full article
(This article belongs to the Section B: Energy and Environment)
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31 pages, 8151 KiB  
Review
A Comprehensive Review of Sulfide Solid-State Electrolytes: Properties, Synthesis, Applications, and Challenges
by Bin Man, Yulong Zeng, Qingrui Liu, Yinwen Chen, Xin Li, Wenjing Luo, Zikang Zhang, Changliang He, Min Jie and Sijie Liu
Crystals 2025, 15(6), 492; https://doi.org/10.3390/cryst15060492 - 22 May 2025
Abstract
Traditional lithium-ion batteries (LIBs) utilize liquid electrolytes, which pose significant safety risks. To address these concerns and enhance energy density, all-solid-state batteries (ASSBs) have emerged as a safer and more efficient alternative to conventional liquid electrolyte-based systems. ASSBs offer notable advantages, including higher [...] Read more.
Traditional lithium-ion batteries (LIBs) utilize liquid electrolytes, which pose significant safety risks. To address these concerns and enhance energy density, all-solid-state batteries (ASSBs) have emerged as a safer and more efficient alternative to conventional liquid electrolyte-based systems. ASSBs offer notable advantages, including higher energy density and improved safety, driving growing interest from both industry and academia. A key component in all-solid-state battery (ASSB) development is the solid-state electrolyte (SSE), which plays a crucial role in determining the overall performance and safety of these batteries. Sulfide SSEs are characterized by distinctive attributes, including notably high ionic conductivity and remarkably low interfacial resistance with lithium metal anodes, which renders them particularly advantageous for advancing ASSB technology. This paper systematically examines sulfide-based SSEs, with particular emphasis on their underlying physicochemical properties, structural characteristics, and essential functional attributes relevant to ASSB applications. Additionally, we explore preparation methods for sulfide SSEs and analyze their potential applications in next-generation ASSBs. Considering current challenges (e.g., interfacial instability or air sensitivity) we summarize strategies to address these obstacles, aiming to facilitate their integration into future energy storage systems. Full article
(This article belongs to the Special Issue Advances in Materials for Energy Conversion and Storage)
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17 pages, 4176 KiB  
Article
An Operational Optimization Model for Micro Energy Grids in Photovoltaic-Storage Agricultural Greenhouses Based on Operation Mode Selection
by Peng Li, Mengen Zhao, Hongkai Zhang, Outing Zhang, Naixun Li, Xianyu Yue and Zhongfu Tan
Processes 2025, 13(6), 1622; https://doi.org/10.3390/pr13061622 - 22 May 2025
Abstract
Addressing the urgent need for sustainable energy transitions in rural development while achieving the dual carbon goals, this study focuses on resolving critical challenges in agricultural photovoltaic (PV) applications, including land-use conflicts, compound energy demands (electricity, heating, cooling), and financial constraints among farmers. [...] Read more.
Addressing the urgent need for sustainable energy transitions in rural development while achieving the dual carbon goals, this study focuses on resolving critical challenges in agricultural photovoltaic (PV) applications, including land-use conflicts, compound energy demands (electricity, heating, cooling), and financial constraints among farmers. To tackle these issues, a dual-mode cost–benefit analysis framework was developed, integrating two distinct investment models: self-invested construction (SIC), where farmers independently finance and manage the system, and energy performance contracting (EPC), where third-party investors fund infrastructure through shared energy-saving or revenue agreements. Then, an integrated photovoltaic-storage agricultural greenhouse (PSAG) microgrid optimization model is established, synergizing renewable energy generation, battery storage, and demand-side management while incorporating operational mode selection. The proposed model is validated through a real-world case study of a village agricultural greenhouse in Gannan, China, characterized by typical rural energy profiles and climatic conditions. Simulation results demonstrate that the optimal system configuration requires 27.91 kWh energy storage capacity and 18.67 kW peak output, with annualized post-depreciation costs of 81,083.69 yuan (SIC) and 74,216.22 yuan (EPC). The key findings reveal that energy storage integration reduces operational costs by 8.5% compared to non-storage scenarios, with the EPC model achieving 9.3% greater cost-effectiveness than SIC through shared-investment mechanisms. The findings suggest that incorporating an energy storage system reduces costs for farmers, with the EPC model offering greater cost savings. Full article
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21 pages, 2359 KiB  
Article
Peak Shaving Strategy in the Context of the Charging Process of a Battery Energy Storage System in the Railway Microgrid
by Piotr Obrycki, Krzysztof Perlicki and Marek Stawowy
Energies 2025, 18(11), 2674; https://doi.org/10.3390/en18112674 - 22 May 2025
Abstract
Peak shaving is one of the key mechanisms implemented in technically advanced power grids, including rail networks, to reduce the demand for costly power generation during peak hours. Energy storage systems are commonly used for this purpose. This article presents an analysis of [...] Read more.
Peak shaving is one of the key mechanisms implemented in technically advanced power grids, including rail networks, to reduce the demand for costly power generation during peak hours. Energy storage systems are commonly used for this purpose. This article presents an analysis of peak load reduction using energy storage considering the specifics of the energy operation of the railway network. Two methods of peak shaving are proposed: a variable threshold value and a constant threshold value. The choice of one of them depends on the relationship between the frequency of occurrence of peak loads on the railway line and the charging time of the energy storage system. An innovative predictive analysis of the temporal characteristics of the railway line load was carried out to determine the likelihood of a peak load occurring during the charging of the energy storage system. The Poisson distribution and Long Short-Term Memory method were used to accomplish this task. The first experiment in Poland on peak shaving using a large-scale energy storage system is presented. It was also one of the first high-power installations of this type in the world to directly cooperate with a 3 kV DC traction network. Full article
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19 pages, 2246 KiB  
Review
Diatomaceous Biosilica: A Multifunctional Resource for Biomedicine and Sustainable Applications
by Letícia Guerreiro da Trindade, Monize Bürck, Eduarda Lemos de Souza, Letícia Zanchet, Marcelo Assis and Anna Rafaela Cavalcante Braga
Ceramics 2025, 8(2), 62; https://doi.org/10.3390/ceramics8020062 - 22 May 2025
Abstract
Diatomaceous biosilica has emerged as a functional material with unique properties, driving innovations in energy storage, therapeutic systems, and environmental catalysis. This article critically reviews recent advances in using natural biosilica in lithium-ion battery anodes, emphasizing how its hierarchical morphology and high porosity [...] Read more.
Diatomaceous biosilica has emerged as a functional material with unique properties, driving innovations in energy storage, therapeutic systems, and environmental catalysis. This article critically reviews recent advances in using natural biosilica in lithium-ion battery anodes, emphasizing how its hierarchical morphology and high porosity contribute to ion insertion and transport efficiency. Its surface chemistry enables controlled drug release and tissue regeneration in biomedical applications. Its synergy with metal catalysts enhances pollutant degradation in photocatalytic systems, especially via surface biofunctionalization. By linking these areas, this review highlights the potential of diatom biosilica as a viable and sustainable alternative to synthetic materials, promoting technological solutions aligned with circular economy and materials engineering. Full article
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150 pages, 10258 KiB  
Review
Metal-Free Graphene-Based Derivatives as Oxygen Reduction Reaction Electrocatalysts in Energy Conversion and Storage Systems: An Overview
by Laura Crociani
Molecules 2025, 30(10), 2248; https://doi.org/10.3390/molecules30102248 - 21 May 2025
Abstract
Oxygen reduction reaction (ORR) is one of the most important reactions in electrochemical energy storage and conversion devices. To overcome the slow kinetics, minimize the overpotential, and make this reaction feasible, efficient, and stable, electrocatalysts are needed. Metal-free graphene-based systems are considered promising [...] Read more.
Oxygen reduction reaction (ORR) is one of the most important reactions in electrochemical energy storage and conversion devices. To overcome the slow kinetics, minimize the overpotential, and make this reaction feasible, efficient, and stable, electrocatalysts are needed. Metal-free graphene-based systems are considered promising and cost-effective ORR catalysts with adjustable structures. This review is meant to give a rational overview of the graphene-based metal-free ORR electrocatalysts, illustrating the huge amount of related research developed particularly in the field of fuel cells and metal–air batteries, with particular attention to the synthesis procedures. The novelty of this review is that, beyond general aspects regarding the synthesis and characterization of graphene, above 90% of the various graphene (doped and undoped species, composites)-based ORR electrocatalysts have been reported, which represents an unprecedented thorough collection of both experimental and theoretical studies. Hundreds of references are included in the review; therefore, it can be considered as a vademecum in the field. Full article
(This article belongs to the Section Materials Chemistry)
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27 pages, 5967 KiB  
Article
Accuracy-Enhanced Multi-Variable LSTM-Based Sensorless Temperature Estimation for Marine Lithium-Ion Batteries Using Real Operational Data for an ORC–ESS
by Bom-Yi Lim, Chan Roh, Seung-Taek Lim and Hyeon-Ju Kim
Processes 2025, 13(5), 1605; https://doi.org/10.3390/pr13051605 - 21 May 2025
Abstract
Driven by increasingly stringent carbon emission regulations from the International Maritime Organization (IMO), the maritime industry increasingly requires eco-friendly power systems and enhanced energy efficiency. Lithium-ion batteries, a core component of these systems, necessitate precise temperature management to ensure safety, performance, and longevity, [...] Read more.
Driven by increasingly stringent carbon emission regulations from the International Maritime Organization (IMO), the maritime industry increasingly requires eco-friendly power systems and enhanced energy efficiency. Lithium-ion batteries, a core component of these systems, necessitate precise temperature management to ensure safety, performance, and longevity, especially under high-temperature conditions owing to the inherent risk of thermal runaway. This study proposes a sensorless temperature estimation method using a long short-term memory network. Using key parameters, including state of charge, voltage, current, C-rate, and depth of discharge, a MATLAB-based analysis program was developed to model battery dynamics. The proposed method enables real-time internal temperature estimation without physical sensors, demonstrating improved accuracy via data-driven learning. Operational data from the training vessel Hannara were used to develop an integrated organic Rankine cycle–energy storage system model, analyze factors influencing battery temperature, and inform optimized battery operation strategies. The results highlight the potential of the proposed method to enhance the safety and efficiency of shipboard battery systems, thereby contributing to the achievement of the IMO’s carbon reduction goals. Full article
(This article belongs to the Special Issue Energy Storage and Conversion: Next-Generation Battery Technology)
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21 pages, 2925 KiB  
Article
Flexible Green Ammonia Production: Impact of Process Design on the Levelized Cost of Ammonia
by Cecilia Pistolesi, Alberto Giaconia, Claudia Bassano and Marcello De Falco
Fuels 2025, 6(2), 39; https://doi.org/10.3390/fuels6020039 - 21 May 2025
Abstract
This study evaluates the economic feasibility of flexible, renewable ammonia production in Italy through a comprehensive sensitivity analysis of the levelized cost of ammonia (LCOA). Ammonia is produced through Haber–Bosch synthesis from green hydrogen and nitrogen coming from alkaline electrolysis and cryogenic air [...] Read more.
This study evaluates the economic feasibility of flexible, renewable ammonia production in Italy through a comprehensive sensitivity analysis of the levelized cost of ammonia (LCOA). Ammonia is produced through Haber–Bosch synthesis from green hydrogen and nitrogen coming from alkaline electrolysis and cryogenic air separation, respectively. The analysis examines the impact of key parameters such as renewable source peak power, Haber–Bosch reactor flexibility, energy mix, electrochemical and hydrogen storage, on the final production cost. The location considered for the PV and wind power output is Southern Italy. The results show that a wind-driven system with minimal battery storage and a flexibility factor (ratio between the minimum operating capacity and the nominal capacity of the plant) of 20% offers the most cost-effective solution, but production is scaled down to 64 tpd. With the 2030 cost structure, battery storage offers better integration with wind systems and flexible operation, even at low levels of turndown. For different combinations of process design choices and flexibility, the optimal LCOA for a green ammonia production is approximately 0.59 USD/kgNH3 in 2050. This cost of production could be competitive with grey ammonia, provided that a carbon emission allowance of USD 0.12/kgCO2 is applied. Full article
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23 pages, 3765 KiB  
Article
Data-Driven Capacity Modeling of 18650 Lithium-Ion Cells from Experimental Electrical Measurements
by Víctor Olivero-Ortiz, Ingrid Oliveros Pantoja and Carlos Robles-Algarín
Sustainability 2025, 17(10), 4718; https://doi.org/10.3390/su17104718 - 21 May 2025
Abstract
The prediction of lithium-ion battery capacity degradation is crucial for enhancing the reliability, efficiency, and sustainability of energy storage systems. This study proposes a data-driven approach to model capacity degradation in 18650 lithium-ion cells, supporting the long-term performance and responsible management of battery [...] Read more.
The prediction of lithium-ion battery capacity degradation is crucial for enhancing the reliability, efficiency, and sustainability of energy storage systems. This study proposes a data-driven approach to model capacity degradation in 18650 lithium-ion cells, supporting the long-term performance and responsible management of battery technologies. A systematic search was conducted to identify publicly available experimental datasets reporting charge/discharge processes, leading to the selection of the MIT-BIT Battery Degradation Dataset (Fixed Current Profiles and Arbitrary Use Profiles). This dataset was chosen for its extensive degradation data, variability, and adaptability to real-world applications. Of the 77 tested cells, 73 were included after filtering data completeness; cells with missing critical information, such as temperature, were excluded. A subset of cells tested under a 1C–2C charge/discharge profile was analyzed, and cell 52 was selected for its comprehensive structure. Using this dataset, a predictive model was developed to estimate the battery capacity based on the current, voltage, and temperature, with capacity as the target variable. A neural network was implemented using TensorFlow and Keras, incorporating ReLU activation, Adam optimization, and multiple loss functions. The dataset was standardized using MinMaxScaler, StandardScaler, and RobustScaler, and the training–test split was 75–25%. The model achieved a prediction error of 3.35% during training and 3.48% during validation, demonstrating robustness and efficiency. These results highlight the potential of data-driven models in accurately predicting lithium-ion battery degradation and underscore their relevance for promoting sustainable energy systems through improved battery health forecasting, optimized second-life use, and extended operational lifetimes of storage technologies. Full article
(This article belongs to the Section Energy Sustainability)
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19 pages, 2510 KiB  
Article
Efficiency Optimization Control Strategies for High-Voltage-Ratio Dual-Active-Bridge (DAB) Converters in Battery Energy Storage Systems
by Hui Ma, Jianhua Lei, Geng Qin, Zhihua Guo and Chuantong Hao
Energies 2025, 18(10), 2650; https://doi.org/10.3390/en18102650 - 20 May 2025
Abstract
This article introduces a high-efficiency, high-voltage-ratio bidirectional DC–DC converter based on the Dual-Active-Bridge (DAB) topology, specifically designed for applications involving low-voltage, high-capacity cells. Addressing the critical challenge of enhancing bidirectional power transfer efficiency under ultra-high step-up ratios, which is essential for integrating renewable [...] Read more.
This article introduces a high-efficiency, high-voltage-ratio bidirectional DC–DC converter based on the Dual-Active-Bridge (DAB) topology, specifically designed for applications involving low-voltage, high-capacity cells. Addressing the critical challenge of enhancing bidirectional power transfer efficiency under ultra-high step-up ratios, which is essential for integrating renewable energy sources and battery storage systems into modern power grids, an optimized control strategy is proposed. This strategy focuses on refining switching patterns and minimizing conduction losses to improve overall system efficiency. Theoretical analysis revealed significant enhancements in efficiency across various operating conditions. Simulation results further confirmed that the converter achieved exceptional performance in terms of efficiency at extremely high voltage conversion ratios, showcasing full-range Zero-Voltage Switching (ZVS) capabilities and reduced circulating reactive power. Specifically, the proposed method reduced circulating reactive power by up to 22.4% compared to conventional fixed-frequency control strategies, while achieving over 35% overload capability. These advancements reinforce the role of DAB as a key topology for next-generation high-performance power conversion systems, facilitating more efficient integration of renewable energy and energy storage solutions, and thereby contributing to the stability and sustainability of contemporary energy systems. Full article
(This article belongs to the Special Issue Advances in Energy Storage Systems for Renewable Energy: 2nd Edition)
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49 pages, 7310 KiB  
Review
Progress of MXene-Based Materials in the Field of Rechargeable Batteries
by Jianfei Gao, Jing Li, Qian Wang and Cheng Zou
Materials 2025, 18(10), 2386; https://doi.org/10.3390/ma18102386 - 20 May 2025
Abstract
With the rapid development of electrical energy storage technologies, traditional battery systems are limited in practical applications by insufficient energy density and short cycle life. This review provides a comprehensive and critical summary of MXene or MXene-based composites as electrode materials for high-performance [...] Read more.
With the rapid development of electrical energy storage technologies, traditional battery systems are limited in practical applications by insufficient energy density and short cycle life. This review provides a comprehensive and critical summary of MXene or MXene-based composites as electrode materials for high-performance energy storage devices. By integrating the synthesis techniques of MXenes that have been studied, this paper systematically illustrates the physicochemical properties, synthesis strategies, and mechanisms of MXenes, and analyzes the bottlenecks in their large-scale preparation. Meanwhile, it collates the latest research achievements of MXenes in the field of metal–ion batteries in recent years, focusing on integrating their latest progress in lithium–ion, sodium–ion, lithium–sulfur, and multivalent ion (Zn2+, Mg2+, Al3+) batteries, and reveals their action mechanisms in different electrode material cases. Combining DFT analysis of the effects of surface functional groups on adsorption energy with experimental studies clarifies the structure–activity relationships of MXene-based composites. However, the development of energy storage electrode materials using MXenes and their hybrid compounds remains in its infancy. Future development directions for MXene-based batteries should focus on understanding and regulating surface chemistry, investigating specific energy storage mechanisms in electrodes, and exploring and developing electrode materials related to bimetallic MXenes. Full article
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23 pages, 8487 KiB  
Article
An Artificial Intelligence Frequency Regulation Strategy for Renewable Energy Grids Based on Hybrid Energy Storage
by Qiang Zhang, Qi Jia, Tingqi Zhang, Hui Zeng, Chao Wang, Wansong Liu, Hanlin Li and Yihui Song
Energies 2025, 18(10), 2629; https://doi.org/10.3390/en18102629 - 20 May 2025
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Abstract
To address the frequency regulation requirements of hybrid energy storage (HES) in renewable-dominated power grids, this paper proposes an asymmetric droop control strategy based on an improved backpropagation (BP) neural network. First, a simulation model of HES (comprising supercapacitors for the power support [...] Read more.
To address the frequency regulation requirements of hybrid energy storage (HES) in renewable-dominated power grids, this paper proposes an asymmetric droop control strategy based on an improved backpropagation (BP) neural network. First, a simulation model of HES (comprising supercapacitors for the power support and batteries for the energy balance) participating in primary frequency regulation is established, with a stepwise frequency regulation dead zone designed to optimize multi-device coordination. Second, an enhanced Sigmoid activation function (with controllable parameters a, b, m, and n) is introduced to dynamically adjust the power regulation coefficients of energy storage units, achieving co-optimization of frequency stability and State of Charge (SOC). Simulation results demonstrate that under a step load disturbance (0.05 p.u.), the proposed strategy reduces the maximum frequency deviation by 79.47% compared to scenarios without energy storage (from 1.7587 × 10−3 to 0.0555 × 10−3) and outperforms fixed-droop strategies by 44.33%. During 6-min continuous random disturbances, the root mean square (RMS) of system frequency deviations decreases by 4.91% compared to conventional methods, while SOC fluctuations of supercapacitors and batteries are reduced by 49.28% and 45.49%, respectively. The parameterized asymmetric regulation mechanism significantly extends the lifespan of energy storage devices, offering a novel solution for real-time frequency control in high-renewable penetration grids. Full article
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26 pages, 2634 KiB  
Article
Optimized Dual-Battery System with Intelligent Auto-Switching for Reliable Soil Nutrient Monitoring in Remote IoT Applications
by Doan Perdana, Pascal Lorenz and Bagus Aditya
J. Sens. Actuator Netw. 2025, 14(3), 53; https://doi.org/10.3390/jsan14030053 - 19 May 2025
Viewed by 145
Abstract
This study introduces a novel dual-battery architecture with intelligent auto-switching control, designed to ensure uninterrupted operation of agricultural sensing systems in environments with unpredictable energy availability. The proposed system integrates Lithium-Sulphur (Li-S) and Lithium-Ion (Li-Ion) batteries with advanced switching algorithms—specifically, the Dynamic Load [...] Read more.
This study introduces a novel dual-battery architecture with intelligent auto-switching control, designed to ensure uninterrupted operation of agricultural sensing systems in environments with unpredictable energy availability. The proposed system integrates Lithium-Sulphur (Li-S) and Lithium-Ion (Li-Ion) batteries with advanced switching algorithms—specifically, the Dynamic Load Balancing–Power Allocation Optimisation (DLB–PAO) and Dynamic Load Balancing–Genetic Algorithm (DLB–GA)—tailored to maximise sensor operational longevity. By optimizing the dual-battery configuration for real-world deployment and conducting comparative evaluations across multiple system designs, this work advances an innovative engineering solution with significant practical implications for sustainable agriculture and remote sensing applications. Unlike conventional single-battery systems or passive redundancy approaches, the architecture introduces active redundancy, adaptive energy management, and fault tolerance, substantially improving operational continuity. A functional prototype was experimentally validated using realistic load profiles, demonstrating seamless battery switching, extended uptime, and enhanced energy reliability. To further assess long-term performance under continuous Internet of Things (IoT) operation, a simulation framework was developed in MATLAB/Simulink, incorporating battery degradation models and empirical sensor load profiles. The experimental results reveal distinct performance improvements. A baseline single-battery system sustains 28 h of operation with 31.2% average reliability, while a conventional dual-battery configuration extends operation to 45 h with 42.6% reliability. Implementing the DLB–PAO algorithm elevates the average reliability to 91.7% over 120 h, whereas the DLB–GA algorithm achieves near-perfect reliability (99.9%) for over 170 h, exhibiting minimal variability (standard deviation: 0.9%). The integration of intelligent auto-switching mechanisms and metaheuristic optimisation algorithms demonstrates a marked enhancement in both reliability and energy efficiency for soil nutrient monitoring systems. This method extends the lifespan of electronic devices while ensuring reliable energy storage over time. It creates a practical foundation for sustainable IoT agricultural systems in areas with limited resources. Full article
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19 pages, 6402 KiB  
Article
Modular Multilevel Converter-Based Hybrid Energy Storage System Integrating Supercapacitors and Batteries with Hybrid Synchronous Control Strategy
by Chuan Yuan, Jing Gou, Jiao You, Bo Li, Xinwei Du, Yifeng Fu, Weixuan Zhang, Xi Wang and Peng Shi
Processes 2025, 13(5), 1580; https://doi.org/10.3390/pr13051580 - 19 May 2025
Viewed by 146
Abstract
This paper proposes a hybrid synchronization control modular multilevel converter-based hybrid energy storage system (HSC-MMC-HESS) that innovatively integrates battery units within MMC submodules (SMs) while connecting a supercapacitor (SC) to the DC bus. The configuration synergistically combines the high energy density of batteries [...] Read more.
This paper proposes a hybrid synchronization control modular multilevel converter-based hybrid energy storage system (HSC-MMC-HESS) that innovatively integrates battery units within MMC submodules (SMs) while connecting a supercapacitor (SC) to the DC bus. The configuration synergistically combines the high energy density of batteries with the high power density of SCs through distinct energy/power pathways. The operational principles and control architecture are systematically analyzed, incorporating a hybrid synchronization control (HSC) strategy to deliver system inertia, primary frequency regulation, fault-tolerant mode transition capabilities, and isolation control. A hierarchical control framework implements power distribution through filtering mechanisms and state-of-charge (SOC) balancing control for battery management. Hardware-in-the-loop experimental validation confirms the topology’s effectiveness in providing inertial support, enabling flexible operational mode switching and optimizing hybrid energy storage utilization. The demonstrated capabilities indicate strong application potential for medium-voltage distribution networks requiring dynamic grid support. Full article
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