Energies

33 pages, 3891 KiB

Open AccessReview

Utility Transformer DC Bias Caused by Metro Stray Current—A Review

by Adisu Makeyaw, Xiaofeng Yang, Xiangxuan Sun, Ke Liu, Tianyi Wu and Lu Chen

Energies 2025, 18(14), 3678; https://doi.org/10.3390/en18143678 - 11 Jul 2025

The rapid expansion of the urban rail network has increased concerns regarding stray current generated by the DC traction power supply system. This stray current, which arises from inadequate insulation between the rail and the ground, can cause electrochemical corrosion and operational challenges [...] Read more.

The rapid expansion of the urban rail network has increased concerns regarding stray current generated by the DC traction power supply system. This stray current, which arises from inadequate insulation between the rail and the ground, can cause electrochemical corrosion and operational challenges to nearby buried metallic infrastructures. A portion of stray current entering utility transformers may induce DC bias risk, thereby affecting the stability and reliability of distribution networks. This review studies the trends in utility transformer-related DC bias caused by metro stray current. Various modeling approaches and suppression measures are discussed, with an emphasis on comprehensively understanding stray current distribution behavior, the DC bias coupling loop, and its impacts. This review underscores the need for a thorough evaluation of existing DC bias suppression measures, and more effective and efficient measures must be developed to enhance the resilience of distribution networks. The gaps in current research are highlighted, and further studies are advocated, particularly those focusing on dynamic metro conditions, supported by advanced modeling, field applications, and interdisciplinary collaboration, to address the challenges of DC bias in urban rail environments. Full article

(This article belongs to the Topic Power System Protection)

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20 pages, 1299 KiB

Open AccessArticle

Selective Microwave Pretreatment of Biomass Mixtures for Sustainable Energy Production

by Raimonds Valdmanis and Maija Zake

Energies 2025, 18(14), 3677; https://doi.org/10.3390/en18143677 - 11 Jul 2025

Abstract

Methods for the improvement of regional lignocellulosic resources (wood and agriculture waste) were studied and analyzed using blends with optimized compositions and a selective pretreatment of the blends using microwaves to enhance their thermochemical conversion and energy production efficiency. A batch-size pilot device [...] Read more.

Methods for the improvement of regional lignocellulosic resources (wood and agriculture waste) were studied and analyzed using blends with optimized compositions and a selective pretreatment of the blends using microwaves to enhance their thermochemical conversion and energy production efficiency. A batch-size pilot device was used to provide the thermochemical conversion of biomass blends of different compositions, analyzing the synergy of the effects of thermal and chemical interaction between the components on the yield and thermochemical conversion of volatiles, responsible for producing heat energy at various stages of flame formation. To control the thermal decomposition of the biomass, improving the flame characteristics and the produced heat, a selective pretreatment of blends using microwaves (2.45 GHz) was achieved by varying the temperature of microwave pretreatment. Assessing correlations between changes in the main characteristics of pretreated blends (elemental composition and heating value) on the produced heat and composition of products suggests that selective MW pretreatment of biomass blends activates synergistic effects of thermal and chemical interaction, enhancing the yield and combustion of volatiles with a correlating increase in produced heat energy, thus promoting the wider use of renewable biomass resources for sustainable energy production by limiting the use of fossil fuels for heat-energy production and the formation of GHG emissions. Full article

(This article belongs to the Special Issue Wood-Based Bioenergy: 2nd Edition)

22 pages, 2892 KiB

Open AccessArticle

Optimization of Photovoltaic and Battery Storage Sizing in a DC Microgrid Using LSTM Networks Based on Load Forecasting

by Süleyman Emre Eyimaya, Necmi Altin and Adel Nasiri

Energies 2025, 18(14), 3676; https://doi.org/10.3390/en18143676 - 11 Jul 2025

Abstract

This study presents an optimization approach for sizing photovoltaic (PV) and battery energy storage systems (BESSs) within a DC microgrid, aiming to enhance cost-effectiveness, energy reliability, and environmental sustainability. PV generation is modeled based on environmental parameters such as solar irradiance and ambient [...] Read more.

This study presents an optimization approach for sizing photovoltaic (PV) and battery energy storage systems (BESSs) within a DC microgrid, aiming to enhance cost-effectiveness, energy reliability, and environmental sustainability. PV generation is modeled based on environmental parameters such as solar irradiance and ambient temperature, while battery charging and discharging operations are managed according to real-time demand. A simulation framework is developed in MATLAB 2021b to analyze PV output, battery state of charge (SOC), and grid energy exchange. For demand-side management, the Long Short-Term Memory (LSTM) deep learning model is employed to forecast future load profiles using historical consumption data. Moreover, a Multi-Layer Perceptron (MLP) neural network is designed for comparison purposes. The dynamic load prediction, provided by LSTM in particular, improves system responsiveness and efficiency compared to MLP. Simulation results indicate that optimal sizing of PV and storage units significantly reduces energy costs and dependency on the main grid for both forecasting methods; however, the LSTM-based approach consistently achieves higher annual savings, self-sufficiency, and Net Present Value (NPV) than the MLP-based approach. The proposed method supports the design of more resilient and sustainable DC microgrids through data-driven forecasting and system-level optimization, with LSTM-based forecasting offering the greatest benefits. Full article

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19 pages, 1252 KiB

Open AccessArticle

Analogy Analysis of Height Exergy and Temperature Exergy in Energy Storage System

by Yan Cui, Tong Jiang and Mulin Liu

Energies 2025, 18(14), 3675; https://doi.org/10.3390/en18143675 - 11 Jul 2025

Abstract

As a pivotal technology and infrastructure component for modern power systems, energy storage has experienced significant advancement in recent years. A fundamental prerequisite for designing future energy storage facilities lies in the systematic evaluation of energy conversion capabilities across diverse storage technologies. This [...] Read more.

As a pivotal technology and infrastructure component for modern power systems, energy storage has experienced significant advancement in recent years. A fundamental prerequisite for designing future energy storage facilities lies in the systematic evaluation of energy conversion capabilities across diverse storage technologies. This study conducted a comparative analysis between pumped hydroelectric storage (PHS) and compressed air energy storage (CAES), defining the concepts of height exergy and temperature exergy. Height exergy is the maximum work capacity of a liquid due to height differences, while temperature exergy is the maximum work capacity of a gas due to temperature differences. The temperature exergy represents innovation in thermodynamic analysis; it is derived from internal exergy and proven through the Maxwell relation and the decoupling method of internal exergy, offering a more efficient method for calculating energy storage capacity in CAES systems. Mathematical models of height exergy and temperature exergy were established based on their respective forms. A unified calculation formula was derived, and their respective characteristics were analyzed. In order to show the meaning of temperature exergy more clearly and intuitively, a height exergy model of temperature exergy was established through analogy analysis, and it was concluded that the shape of the reservoir was a cone when comparing water volume to heat quantity, intuitively showing that the cold source had a higher energy storage density than the heat source. Finally, a typical hybrid PHS–CAES system was proposed, and a mathematical model was established and verified in specific cases based on height exergy and temperature exergy. It was demonstrated that when the polytropic exponent n = 1.2, the theoretical loss accounted for the largest proportion, which was 2.06%. Full article

(This article belongs to the Section D: Energy Storage and Application)

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18 pages, 3631 KiB

Open AccessArticle

Analysis of Implementing Hydrogen Storage for Surplus Energy from PV Systems in Polish Households

by Piotr Olczak and Dominika Matuszewska

Energies 2025, 18(14), 3674; https://doi.org/10.3390/en18143674 - 11 Jul 2025

Abstract

One of the methods for mitigating the duck curve phenomenon in photovoltaic (PV) energy systems is storing surplus energy in the form of hydrogen. However, there is a lack of studies focused on residential PV systems that assess the impact of hydrogen storage [...] Read more.

One of the methods for mitigating the duck curve phenomenon in photovoltaic (PV) energy systems is storing surplus energy in the form of hydrogen. However, there is a lack of studies focused on residential PV systems that assess the impact of hydrogen storage on the reduction of energy flow imbalance to and from the national grid. This study presents an analysis of hydrogen energy storage based on real-world data from a household PV installation. Using simulation methods grounded in actual electricity consumption and hourly PV production data, the research identified the storage requirements, including the required operating hours and the capacity of the hydrogen tank. The analysis was based on a 1 kW electrolyzer and a fuel cell, representing the smallest and most basic commercially available units, and included a sensitivity analysis. At the household level—represented by a single-family home with an annual energy consumption and PV production of approximately 4–5 MWh over a two-year period—hydrogen storage enabled the production of 49.8 kg and 44.6 kg of hydrogen in the first and second years, respectively. This corresponded to the use of 3303 kWh of PV-generated electricity and an increase in self-consumption from 30% to 64%. Hydrogen storage helped to smooth out peak energy flows from the PV system, decreasing the imbalance from 5.73 kWh to 4.42 kWh. However, while it greatly improves self-consumption, its capacity to mitigate power flow imbalance further is constrained; substantial improvements would necessitate a much larger electrolyzer proportional in size to the PV system’s output. Full article

(This article belongs to the Special Issue Challenges and Opportunities in the Global Clean Energy Transition)

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18 pages, 5325 KiB

Open AccessArticle

Design of High-Speed, High-Efficiency Electrically Excited Synchronous Motor

by Shumei Cui, Yuqi Zhang, Beibei Song, Shuo Zhang and Hongwen Zhu

Energies 2025, 18(14), 3673; https://doi.org/10.3390/en18143673 - 11 Jul 2025

Abstract

In air-conditioning compressors operating under ultra-low temperature conditions, both the rotational speed and load torque are at high levels, demanding pump motors that offer high efficiency and high power at high speeds. Electrically excited synchronous motors (EESMs) satisfy these operational requirements by leveraging [...] Read more.

In air-conditioning compressors operating under ultra-low temperature conditions, both the rotational speed and load torque are at high levels, demanding pump motors that offer high efficiency and high power at high speeds. Electrically excited synchronous motors (EESMs) satisfy these operational requirements by leveraging their inherent wide-speed field-weakening capability and superior high-speed performance characteristics. Current research on EESM primarily targets electric vehicle applications, with a high-efficiency design focused on medium and low speeds. Excitation design under constant-power–speed extension remains insufficiently explored. To address it, this paper proposes an EESM design methodology optimized for high-speed efficiency and constant-power excitation control. Key EESM parameters are determined through a dynamic phasor diagram, and design methods for turn number, split ratio, and other parameters are proposed to extend the high-efficiency region into the high-speed range. Additionally, a power output modulation strategy in the field-weakening region is introduced, enabling dynamic high-power regulation at high speed through excitation adjustment. Compared to similarly sized PMSMs, the proposed EESM exhibits consistently superior efficiency beyond 10,000 rpm, delivering 19% and 49% higher power output at 12,000 rpm and 14,000 rpm, respectively, relative to conventional pump-drive PMSMs. Experimental validation via a prototype confirms excellent high-speed efficiency and sustained constant-power performance, in alignment with the design targets. Full article

(This article belongs to the Section F: Electrical Engineering)

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26 pages, 11610 KiB

Open AccessArticle

Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models

by Mohamed Salah Benkhalfallah, Sofia Kouah and Saad Harous

Energies 2025, 18(14), 3672; https://doi.org/10.3390/en18143672 - 11 Jul 2025

Abstract

Optimization of energy consumption in urban infrastructures is essential to achieve sustainability and reduce environmental impacts. In particular, accurate regression-based energy forecasting of the energy consumption in various sectors plays a key role in informed decision-making, efficiency improvements, and resource allocation. This paper [...] Read more.

Optimization of energy consumption in urban infrastructures is essential to achieve sustainability and reduce environmental impacts. In particular, accurate regression-based energy forecasting of the energy consumption in various sectors plays a key role in informed decision-making, efficiency improvements, and resource allocation. This paper examines the application of artificial intelligence and supervised machine learning techniques to modeling and predicting the energy consumption patterns in the smart grid sector of a commercial building located in Singapore. By evaluating performance of several regression algorithms using various metrics, this study identifies the most effective method for analyzing sectoral energy consumption. The results show that the Regression Tree Ensemble algorithm outperforms other techniques, achieving an accuracy of 97.00%, followed by Random Forest Regression (96.20%) and Gradient Boosted Regression Trees (95.50%). These results underline the potential of machine learning models to foster intelligent energy management and promote sustainable energy practices in smart cities. Full article

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21 pages, 3527 KiB

Open AccessArticle

Research on Lithium Iron Phosphate Battery Balancing Strategy for High-Power Energy Storage System

by Ren Zhou, Junyong Lu, Yiting Wu, Hehui Zhang and Kangwei Yan

Energies 2025, 18(14), 3671; https://doi.org/10.3390/en18143671 - 11 Jul 2025

Abstract

For the problem of consistency decline during the long-term use of battery packs for high-voltage and high-power energy storage systems, a dynamic timing adjustment balancing strategy is proposed based on the charge–discharge topology. Compared with the traditional balancing strategy, the dynamic timing adjustment [...] Read more.

For the problem of consistency decline during the long-term use of battery packs for high-voltage and high-power energy storage systems, a dynamic timing adjustment balancing strategy is proposed based on the charge–discharge topology. Compared with the traditional balancing strategy, the dynamic timing adjustment balance strategy is more suitable for the transient high-frequency pulse and high-rate output of a high-power energy storage system. It gives full play to the pulse output adjustment function of the integrated charge–discharge topology. The advantages of this strategy include improving the balance between battery groups, the operating capacity of the system, and improving the continuous working ability of the system. Combined with the work condition of the high-power energy storage system, a balance control model is established, and a cycle charge–discharge test platform of battery packs is built. The effectiveness and advantages of the balance strategy of dynamic timing adjustment are verified by the experiment and simulations. The balancing time is less than 2 min, and the voltage difference is less than 6 mv. Full article

(This article belongs to the Section D: Energy Storage and Application)

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20 pages, 3691 KiB

Open AccessArticle

Distributed Voltage Optimal Control Method for Energy Storage Systems in Active Distribution Network

by Yang Liu, Wenbin Liu, Ying Wu and Haidong Yu

Energies 2025, 18(14), 3670; https://doi.org/10.3390/en18143670 - 11 Jul 2025

Abstract

High permeability distributed photovoltaic (PV) access to the distribution network makes it easy to cause frequent overvoltage of the system. However, the traditional centralized optimization scheduling method is difficult to meet the real-time voltage regulation requirements due to high communication costs. In this [...] Read more.

High permeability distributed photovoltaic (PV) access to the distribution network makes it easy to cause frequent overvoltage of the system. However, the traditional centralized optimization scheduling method is difficult to meet the real-time voltage regulation requirements due to high communication costs. In this regard, this paper proposes a distributed fast voltage regulation method for energy storage systems (ESSs) in distribution networks. Firstly, to reduce the communication burden, the distribution network cluster is divided according to the electrical distance modularity index. Secondly, the distributed control model of active distribution network with the goal of voltage recovery and ESS power balance is established, and a distributed controller is designed. The feedback-control gains are optimized to improve the convergence rate. Finally, the IEEE33 bus system and IEEE69 bus system are applied for simulation. The results show that the proposed distributed optimal control method can effectively improve the voltage level of the distribution network under the condition of ensuring the ESS power balance. Full article

(This article belongs to the Special Issue Development of Distributed Energy Systems Based on Renewable Energy Sources—Current Status and Development Prospects)

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16 pages, 2849 KiB

Open AccessArticle

A Simulation Model for the Transient Characteristics of No-Insulation Superconducting Coils Based on T–A Formulation

by Zhihao He, Yingzhen Liu, Chenyi Yang, Jiannan Yang, Jing Ou, Chengming Zhang, Ming Yan and Liyi Li

Energies 2025, 18(14), 3669; https://doi.org/10.3390/en18143669 - 11 Jul 2025

Abstract

The no-insulation (NI) technique improves the stability and defect-tolerance of high-temperature superconducting (HTS) coils by enabling current redistribution, thereby reducing the risk of quenching. NI–HTS coils are widely applied in DC systems such as high-field magnets and superconducting field coils for electric machines. [...] Read more.

The no-insulation (NI) technique improves the stability and defect-tolerance of high-temperature superconducting (HTS) coils by enabling current redistribution, thereby reducing the risk of quenching. NI–HTS coils are widely applied in DC systems such as high-field magnets and superconducting field coils for electric machines. However, the presence of turn-to-turn contact resistance makes current distribution uneven, rendering traditional simulation methods unsuitable. To address this, a finite element method (FEM) based on the T–A formulation is proposed. This model solves coupled equations for the magnetic vector potential (A) and current vector potential (T), incorporating turn-to-turn contact resistance and anisotropic conductivity. The thin-strip approximation simplifies second-generation HTS materials as one-dimensional conductors, and a homogenization technique further reduces computational time by averaging the properties between turns, although it may limit the resolution of localized inter-turn effects. To verify the model’s accuracy, simulation results are compared against the H formulation, distributed circuit network (DCN) model, and experimental data. The proposed T–A model accurately reproduces key transient characteristics, including magnetic field evolution and radial current distribution, in both circular and racetrack NI coils. These results confirm the model’s potential as an efficient and reliable tool for transient electromagnetic analysis of NI–HTS coils. Full article

(This article belongs to the Section F: Electrical Engineering)

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22 pages, 1314 KiB

Open AccessArticle

From Fossil Dependence on Sustainability: The Effects of Energy Transition, Green Growth, and Financial Inclusion on Environmental Degradation in the MENA Region

by Sami Mustafa Omar, Wagdi M. S. Khalifa and Tolga Oz

Energies 2025, 18(14), 3668; https://doi.org/10.3390/en18143668 - 11 Jul 2025

Abstract

Amid growing environmental concerns and an increasing push for sustainable development, countries in the Middle East and North Africa (MENA) region have taken proactive steps toward green growth, energy transition, and technological innovation. As a result, this study examines the effects of green [...] Read more.

Amid growing environmental concerns and an increasing push for sustainable development, countries in the Middle East and North Africa (MENA) region have taken proactive steps toward green growth, energy transition, and technological innovation. As a result, this study examines the effects of green growth, energy transition, technological innovation, financial inclusion, and urbanization on environmental sustainability in the Middle East and North Africa (MENA) region. Moreover, this study breaks new ground by exposing the hidden environmental costs of financial inclusion, urbanization, and technological innovation in the MENA region’s development trajectory, thereby providing compelling evidence for rethinking sustainability through an integrated approach that aligns economic ambition with ecological responsibility. Data for the studied variables were sourced from the World Bank database covering the period 1990 to 2021. The results show that green growth and energy transition significantly reduce CO₂ emissions, supporting the idea that economic expansion aligned with environmental priorities can contribute to ecological improvement. However, the impact of technological innovation is statistically insignificant, indicating that innovation in the region has not yet translated into meaningful environmental gains, possibly due to the dominance of non-green or industrial-focused innovation. Financial inclusion is found to increase CO₂ emissions, likely by facilitating greater access to credit and financial services that fuel energy-intensive consumption and production activities. Similarly, urbanization also contributes to rising emissions, reflecting the unsustainable nature of urban growth in many MENA region. Based on this study, we advocate for a coordinated regional approach to climate and energy policy, underpinned by shared governance and collective action. Full article

(This article belongs to the Special Issue Carbon Neutrality Through Green Innovations—the Role of the Renewable Energy: 3rd Edition)

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22 pages, 1415 KiB

Open AccessArticle

GCT–CET Integrated Flexible Load Control Method for IES

by Yaoxian Liu, Yuanyuan Wang, Yiqi Yang, Kaixin Zhang, Yue Sun, Cong Hou, Zhonghao Dongye and Jingwen Chen

Energies 2025, 18(14), 3667; https://doi.org/10.3390/en18143667 - 11 Jul 2025

Abstract

Under the “dual carbon” goals, the low-carbon economic dispatch of integrated energy systems (IES) faces multiple challenges, including suboptimal economic efficiency, excessive carbon emissions, and limited renewable energy integration. While traditional green certificate trading (GCT) enhances renewable energy adoption, its emission reduction effect [...] Read more.

Under the “dual carbon” goals, the low-carbon economic dispatch of integrated energy systems (IES) faces multiple challenges, including suboptimal economic efficiency, excessive carbon emissions, and limited renewable energy integration. While traditional green certificate trading (GCT) enhances renewable energy adoption, its emission reduction effect remains inadequate. Conversely, standalone carbon emission trading (CET) effectively curbs emissions but often at the expense of increased operational costs, making it difficult to achieve both economic and environmental objectives simultaneously. To address these limitations, this study proposes an innovative green certificate trading–tiered carbon emission trading (GCT–CET) synergistic mechanism integrated with demand-side flexible load optimization, developing a low-carbon dispatch model designed to minimize total system costs. Simulation experiments conducted with the CPLEX solver demonstrate that, compared to individual GCT or CET implementations, the proposed coordinated mechanism effectively combines renewable energy incentives (through GCT) with stringent emission control (via stepped CET), resulting in a 47.8% reduction in carbon emissions and a 5.4% decrease in total costs. Furthermore, the participation of flexible loads enhances supply–demand balancing, presenting a transformative solution for achieving high-efficiency and low-carbon operation in IES. Full article

(This article belongs to the Special Issue Low-Carbon Energy System Management in Sustainable Cities)

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18 pages, 6838 KiB

Open AccessArticle

Performance Evaluation of Static and Dynamic Compressed Air Reservoirs for Energy Storage

by Alfred Rufer

Energies 2025, 18(14), 3666; https://doi.org/10.3390/en18143666 - 10 Jul 2025

Abstract

The concept of static and dynamic reservoirs is presented, and their performances are evaluated. The static reservoir is a simple reservoir with constant volume, and the dynamic one has a volume which varies as a function of the position of an internal piston [...] Read more.

The concept of static and dynamic reservoirs is presented, and their performances are evaluated. The static reservoir is a simple reservoir with constant volume, and the dynamic one has a volume which varies as a function of the position of an internal piston coupled to a spring. The spring is compressed when the pressure in the chamber rises and exerts a proportional force on it. The two reservoirs are components to be used in compressed air energy storage systems. The study comprises a model of the compression machine as well as models of the two reservoirs. The filling processes are simulated, and the different variables are represented as a function of time. A reduced scale experimentation set-up is presented, and its behavior is first simulated. Then. the results are compared to the experimental records. Full article

(This article belongs to the Special Issue Intelligent Concepts for the Modelling, Optimization and Control of Smart Energy Systems)

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16 pages, 1610 KiB

Open AccessArticle

Energy-Efficient Vacuum Sublimation Drying of Camel Milk: Numerical Simulation and Parametric Analysis

by Arshyn Altybay, Ayaulym Rakhmatulina, Dauren Darkenbayev and Symbat Satybaldy

Energies 2025, 18(14), 3665; https://doi.org/10.3390/en18143665 - 10 Jul 2025

Abstract

This study describes both experimental and numerical investigations into the heat and mass transfer processes governing the vacuum freeze drying of camel milk, with a specific focus on improving the energy efficiency. A three-dimensional model was developed and solved using the finite element [...] Read more.

This study describes both experimental and numerical investigations into the heat and mass transfer processes governing the vacuum freeze drying of camel milk, with a specific focus on improving the energy efficiency. A three-dimensional model was developed and solved using the finite element method to simulate temperature evolution and sublimation interface progression during drying. The numerical model was validated against experimental data, achieving strong agreement, with an

R^{2}

value of 0.94. A detailed parametric analysis examined the effects of the shelf temperature, sample thickness, and chamber pressure on the drying kinetics and energy input. The results indicate that optimising these parameters can significantly reduce the energy consumption and processing time while maintaining product quality. Notably, reducing the sample thickness to 4 mm shortened the drying time by up to 40% and reduced the specific energy consumption (SEC) from 358 to 149 kWh/kg. These findings offer valuable insights for the design of more energy-efficient freeze drying systems, with implications for sustainable milk powder production and industrial-scale process optimisation. Full article

(This article belongs to the Section J1: Heat and Mass Transfer)

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15 pages, 4616 KiB

Open AccessArticle

A Novel Wide-Gain-Range Variable-Structure DC/DC Converter Based on an LLC Resonant Converter

by Qingqing He, Shun Tang, Dan Ren, Zhaoyang Tang, Qisheng Zhu, Chao Tang and Keliang Zhou

Energies 2025, 18(14), 3664; https://doi.org/10.3390/en18143664 - 10 Jul 2025

Abstract

The LLC resonant converter, as an isolated DC-DC conversion topology, has been widely adopted in industrial applications. However, when operating under wide input/output voltage ranges, a broad switching frequency range is required to achieve the desired voltage gain. This wide frequency variation complicates [...] Read more.

The LLC resonant converter, as an isolated DC-DC conversion topology, has been widely adopted in industrial applications. However, when operating under wide input/output voltage ranges, a broad switching frequency range is required to achieve the desired voltage gain. This wide frequency variation complicates the design of magnetic components, causes loss of soft-switching characteristics, and deteriorates electromagnetic interference (EMI) performance. To address these challenges, this paper presents a detailed analysis of the L-LCLC resonant converter. By controlling the connection/disconnection of additional inductors and capacitors through switching devices, the topology achieves structural reconfiguration to enhance the voltage gain range. Optimal mode transition points are selected to ensure stable operation during mode transitions, thereby reducing design complexity, minimizing transition losses, and suppressing voltage/current stress. The parameter design methodology for the additional reactive components is systematically developed. The converter’s performance is validated with Simulink, and the experimental prototype is established with 100 W. Both simulation and experimental results confirm that the L-LCLC resonant converter achieves a wide voltage gain range within a narrow frequency band while maintaining stable mode transitions. Full article

(This article belongs to the Special Issue Reliability of Power Electronics Devices and Converter Systems)

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21 pages, 3429 KiB

Open AccessArticle

Transient Voltage Stability Analysis of the Dual-Source DC Power System

by Yi Lei, Yang Li, Feng Zhao, Yelun Peng, Zhen Mei and Zhikang Shuai

Energies 2025, 18(14), 3663; https://doi.org/10.3390/en18143663 - 10 Jul 2025

Abstract

This paper analyzes the transient voltage stability of the dual-source DC power system. The system’s equivalent model is first established. Subsequently, the effect mechanisms of line parameters and voltage-source rectifiers’ current control inner loops on the system’s transient voltage instability are investigated. It [...] Read more.

This paper analyzes the transient voltage stability of the dual-source DC power system. The system’s equivalent model is first established. Subsequently, the effect mechanisms of line parameters and voltage-source rectifiers’ current control inner loops on the system’s transient voltage instability are investigated. It indicates that these factors reduce the power supply capacity of the source, increasing the risk of transient instability in the system. Then, considering the influence of fault depths, the influence of different large disturbances on the transient voltage stability is investigated. Furthermore, the critical cutting voltage and critical cutting time for DC power systems are determined and then validated on the MATLAB R2023b/Simulink platform. Finally, based on the mixed potential function theory, the impact of system parameter variations on stability boundaries is analyzed quantitatively. Simulation verification is conducted on the MATLAB R2023b/Simulink platform, and experimental verification is conducted on the RT-LAB Hardware-in-the-Loop platform. The results of the quantitative analysis and experiments corroborate the conclusions drawn from the mechanistic analysis, underscoring the critical role of line parameters and converter control parameters in the system’s transient voltage stability. Full article

(This article belongs to the Special Issue Modeling, Stability Analysis and Control of Microgrids)

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36 pages, 2980 KiB

Open AccessReview

Artificial Intelligence in Cable Fault Detection and Localization: Recent Advances and Research Challenges

by Qianqiu Shao, Songhai Fan, Zongxi Zhang, Fenglian Liu, Zhengzheng Fu, Pinlei Lv and Zhou Mu

Energies 2025, 18(14), 3662; https://doi.org/10.3390/en18143662 - 10 Jul 2025

Abstract

With the large-scale integration of new power systems and distributed generators (DGs), cable fault detection and localization face numerous challenges, where artificial intelligence (AI) techniques demonstrate significant advantages. This review first outlines the causes of cable faults and traditional methods for fault detection [...] Read more.

With the large-scale integration of new power systems and distributed generators (DGs), cable fault detection and localization face numerous challenges, where artificial intelligence (AI) techniques demonstrate significant advantages. This review first outlines the causes of cable faults and traditional methods for fault detection and localization. Subsequently, it comprehensively analyzes the applications of both conventional machine learning and deep learning approaches in this field, elaborating on their application scenarios, strengths, defects, and successful case studies, providing valuable references for researchers and professionals. Additionally, the paper discusses the strengths and limitations of current AI techniques, along with the impacts introduced by DG integration. Finally, it highlights future development trends and potential research directions for advancing AI-based solutions in cable fault detection and localization. Full article

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14 pages, 2432 KiB

Open AccessArticle

Charge Reduction and Performance Analysis of a Heat Pump Water Heater Using R290 as a Refrigerant—A Field Study

by Ahmed Elatar, Joseph Rendall, Jian Sun, Jamieson Brechtl and Kashif Nawaz

Energies 2025, 18(14), 3661; https://doi.org/10.3390/en18143661 - 10 Jul 2025

Abstract

Heat pump water heaters (HPWHs) are a proven technology for water heating that has been commercialized. The adoption of HPWHs for domestic and commercial water heating is growing rapidly because of their superior performance compared with alternative water heating methods. Whereas most existing [...] Read more.

Heat pump water heaters (HPWHs) are a proven technology for water heating that has been commercialized. The adoption of HPWHs for domestic and commercial water heating is growing rapidly because of their superior performance compared with alternative water heating methods. Whereas most existing systems use R-134a as a working refrigerant, R290 has gained major attention owing to its superior thermodynamic properties. The goal of the current study is to assess the performance of residential HPWH with R290 as a direct refrigerant replacement for R134a. Two units of a 50 gal HPWH were used in this experimental study. A baseline unit contained R134a refrigerant, and a prototype unit contained R290 refrigerant. The prototype unit was developed through the modification of a commercially available HPWH unit to achieve a low charge of R290 refrigerant. Another major modification was the replacement of the baseline compressor with a compressor designed for R290. Tests were conducted in a field environment (a research and demonstration house) using programmed drawn profiles daily. The prototype that reduced the charge by 43–47% provided displayed performance comparable to the baseline unit regarding first-hour rating (FHR) and the uniform energy factor (UEF). Full article

(This article belongs to the Special Issue Heat Transfer and Fluid Flows for Industry Applications)

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18 pages, 588 KiB

Open AccessReview

Digital Twin for Energy-Intelligent Bakery Operations: Concepts and Applications

by Tsega Y. Melesse, Mohamed Shameer Peer, Suganthi Ramasamy, Vigneselvan Sivasubramaniyam, Mattia Braggio and Pier Francesco Orrù

Energies 2025, 18(14), 3660; https://doi.org/10.3390/en18143660 - 10 Jul 2025

Abstract

The bakery industry is undergoing a profound digital transformation driven by the increasing need for enhanced energy efficiency, operational resilience, and a commitment to environmental sustainability. Digital Twin (DT) technology, recognized as a fundamental component of Industry 4.0, provides advanced capabilities for intelligent [...] Read more.

The bakery industry is undergoing a profound digital transformation driven by the increasing need for enhanced energy efficiency, operational resilience, and a commitment to environmental sustainability. Digital Twin (DT) technology, recognized as a fundamental component of Industry 4.0, provides advanced capabilities for intelligent energy management across bakery operations. This paper utilizes a narrative and integrative review approach, conceptually integrating emerging developments in using DT with respect toenergy management in the baking industry, including real-time energy monitoring, predictive maintenance, dynamic optimization of production processes, and the seamless integration of renewable energy sources. The study underscores the transformative benefits of adopting DT technologies, such as improvements in energy utilization, greater equipment reliability, increased operational transparency, and stronger alignment with global sustainability objectives. It also critically examines the technical, organizational, and financial barriers limiting broader adoption, particularly among small and medium-sized enterprises (SMEs). Future research directions are identified, emphasizing the potential of artificial intelligence-driven DTs, the adoption of edge computing, the development of scalable and modular platforms, and the necessity of supportive policy frameworks. By integrating DT technologies, bakeries can shift from traditional reactive energy practices to proactive, data-driven strategies, paving the way for greater competitiveness, operational excellence, and a sustainable future. Full article

(This article belongs to the Special Issue Industry 4.0-Driven Smart Energy Solutions: Advancements in Renewable Energy Systems)

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