Energies

19 pages, 5877 KB

Open AccessArticle

Numerical Investigation of Combustion Characteristics in a 330 MW Coal-Fired Boiler with Preheating Combustion Devices at Half Load Operation

by Siyuan Wang, Hong Tang, Zuodong Liu, Lingfang Sun and Zhiming Xu

Energies 2025, 18(18), 5042; https://doi.org/10.3390/en18185042 - 22 Sep 2025

Viewed by 494

Abstract

To reduce the impact of renewable energy generation on power grid stability, preheating combustion technology is introduced to maintain coal-fired boiler efficiency at low loads. A 330 MW coal-fired boiler is retrofitted with preheating combustion devices to improve combustion performance and lower NO [...] Read more.

To reduce the impact of renewable energy generation on power grid stability, preheating combustion technology is introduced to maintain coal-fired boiler efficiency at low loads. A 330 MW coal-fired boiler is retrofitted with preheating combustion devices to improve combustion performance and lower NO_x emissions. The device is installed in the reduction zone between the furnace burnout zone and the burner zone. The combustion characteristics of the boiler with and without these devices are examined at 50% rated load. Numerical simulations are conducted to analyze the effects of preheating coal input and burner arrangement on temperature and species distribution within the boiler. Results show that increasing preheating coal input from 0 to 30 t/h enhances NO_x reduction due to a higher flow rate of preheated products. At a preheating coal input of 20 t/h, the combustion efficiency reaches 96.9%. The NO_x concentration at the furnace exit rises from 122.4 to 171.3 mg/Nm³ as the height of the burner arrangement increases. The middle three-layer burner arrangement achieves a uniform temperature distribution and a peak combustion efficiency of 97.6%. The bottom and middle three-layer burner arrangements are recommended for efficient and clean combustion. Compared to the original boiler, the retrofitted boiler’s combustion efficiency increases from 96.3% to a maximum of 97.6%, while the NO_x concentration at the furnace outlet drops from 168.1 to 93.2 mg/Nm³, showing that installing preheating combustion devices promotes efficient and clean combustion. Full article

(This article belongs to the Special Issue Advanced Energy Technologies and Energy Savings: Low Emissions and High Efficiency)

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22 pages, 8883 KB

Open AccessFeature PaperArticle

Autonomous Decentralized Cooperative Control DC Microgrid Deployed in Residential Areas

by Hirohito Yamada

Energies 2025, 18(18), 5041; https://doi.org/10.3390/en18185041 - 22 Sep 2025

Viewed by 342

Abstract

This paper presents a DC microgrid architecture with autonomous decentralized control that exhibits high resilience against increasingly common threats, such as natural disasters and cyber-physical attacks, as well as its operational characteristics under normal circumstances. The proposed system achieves autonomous decentralized cooperative control [...] Read more.

This paper presents a DC microgrid architecture with autonomous decentralized control that exhibits high resilience against increasingly common threats, such as natural disasters and cyber-physical attacks, as well as its operational characteristics under normal circumstances. The proposed system achieves autonomous decentralized cooperative control by combining a battery-integrated DC baseline, in which multiple distributed small-scale batteries are directly connected to the grid baseline, with a weakly coupled grid architecture in which each power device is loosely coupled via the grid baseline. Unlike conventional approaches that assign grid formation, inertial support, and power balancing functions to DC/DC converters, the proposed approach delegates these fundamental grid roles to the distributed batteries. This configuration simplifies the control logic of the DC/DC converters, limiting their role to power exchange only. To evaluate system performance, a four-family DC microgrid model incorporating a typical Japanese home environment, including an EV charger, was constructed in MATLAB/Simulink R2025a and subjected to one-year simulations. The results showed that with approximately 5 kW of PV panels and a 20 kWh battery capacity per household, a stable power supply could be maintained throughout the year, with more than 50% of the total power consumption covered by solar energy. Furthermore, the predicted battery life was over 20 years, confirming the practicality and economic viability of the proposed residential microgrid design. Full article

(This article belongs to the Special Issue Intelligent Operation and Control of Resilient Microgrids)

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20 pages, 4073 KB

Open AccessArticle

Energy-Constrained Optimization of Data Center Layouts: An Integer Linear Programming Approach

by Jing Liang, Donglin Chen and Shangying Xu

Energies 2025, 18(18), 5040; https://doi.org/10.3390/en18185040 - 22 Sep 2025

Viewed by 373

Abstract

Optimizing the layout of data centers is important for the rapid development of digital infrastructure, while also addressing the issues of energy consumption, environmental sustainability, and geographic resource distribution. Traditional strategies usually focus only on the distance to demand centers and ignore the [...] Read more.

Optimizing the layout of data centers is important for the rapid development of digital infrastructure, while also addressing the issues of energy consumption, environmental sustainability, and geographic resource distribution. Traditional strategies usually focus only on the distance to demand centers and ignore the energy and environmental costs of data centers in densely populated areas. In this paper, we propose a layout optimization model based on energy consumption constraints that combines integer linear programming with binary decision variables. The model combines energy efficiency, renewable resource availability, and regional characteristics to balance economic benefits and environmental impacts, consistent with the “East data, West computing” project. The experimental results showed that the energy efficient scenario consistently reduced costs, from ¥3.68 × 10⁸ to ¥3.08 × 10⁸ without energy constraints, and from ¥4.08 × 10⁸ to ¥3.47 × 10⁸ under energy consumption constraints. Additionally, energy constraints increased the number of required data centers from two to three. The results of the study emphasized the importance of strategic siting, especially in low electricity price areas, in order to optimize the layout and improve sustainability. Full article

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22 pages, 3564 KB

Open AccessArticle

Design and Techno-Economic Evaluation for Large-Scale Offshore Wind Power Transmission Scheme

by Chunhua Li, Han Diao, Yijing Chen and Shaowei Huang

Energies 2025, 18(18), 5039; https://doi.org/10.3390/en18185039 - 22 Sep 2025

Viewed by 411

Abstract

As offshore wind farms continue to scale up in both distance and capacity, the design of transmission systems has become a critical factor in the effective development and utilization of offshore wind energy. In response to the growing trend of larger wind turbine [...] Read more.

As offshore wind farms continue to scale up in both distance and capacity, the design of transmission systems has become a critical factor in the effective development and utilization of offshore wind energy. In response to the growing trend of larger wind turbine volume and the densification of offshore platforms, this paper presents a design methodology for compact transmission system tailored to large-scale offshore wind farms, with a focus on the collection system and reactive power control. Firstly, the feasibility of 66 kV single-stage collection system and a unified reactive power compensation scheme using wind turbines and Modular Multilevel Converter (MMC) is analyzed. On this basis, a compact transmission scheme based on MMC-HVDC is proposed for large-scale wind farms. Secondly, a cooperative reactive power control strategy is introduced, leveraging the reactive power regulation capabilities of both wind turbines and MMC. This approach enhances the system’s reactive power and voltage regulation capabilities, as well as its low-voltage ride-through (LVRT) performance. Finally, the effectiveness of the proposed transmission scheme and reactive power control strategy is validated through simulations, and a techno-economic comparison is made with conventional transmission systems. Full article

(This article belongs to the Special Issue Integration of Renewable Energy Systems in Power Grid)

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21 pages, 2168 KB

Open AccessEditor’s ChoiceArticle

Comparative Study on the Effects of Diesel Fuel, Hydrotreated Vegetable Oil, and Its Blends with Pyrolytic Oils on Pollutant Emissions and Fuel Consumption of a Diesel Engine Under WLTC Dynamic Test Conditions

by Artur Jaworski, Hubert Kuszewski, Dariusz Szpica, Paweł Woś, Krzysztof Balawender, Adam Ustrzycki, Artur Krzemiński, Mirosław Jakubowski, Grzegorz Mieczkowski, Andrzej Borawski, Michał S. Gęca and Arkadiusz Rybak

Energies 2025, 18(18), 5038; https://doi.org/10.3390/en18185038 - 22 Sep 2025

Viewed by 616

Abstract

The search for alternative liquid fuels for compression-ignition (CI) internal combustion engines includes waste-derived fuels such as hydrotreated vegetable oil (HVO) and pyrolytic oils from end-of-life tires (tire pyrolytic oil, TPO) and plastics—polystyrene pyrolytic oil (PSO). The application of these fuels requires meeting [...] Read more.

The search for alternative liquid fuels for compression-ignition (CI) internal combustion engines includes waste-derived fuels such as hydrotreated vegetable oil (HVO) and pyrolytic oils from end-of-life tires (tire pyrolytic oil, TPO) and plastics—polystyrene pyrolytic oil (PSO). The application of these fuels requires meeting a number of criteria, including exhaust pollutant emissions. The scientific objective of this study was to compare pollutant emissions—carbon dioxide (CO₂), carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NO_x), particulate matter (PM)—and fuel consumption of a passenger car CI engine fueled with diesel B7, HVO, and a blend consisting of 90% HVO, 5% TPO, and 5% PSO (vol.), hereinafter referred to as HVO–TPO–PSO. The tests were carried out using a chassis dynamometer equipped for conducting standardized WLTC Class 3b driving cycles, with exhaust gases measured by laboratory-grade analyzers to ensure accuracy and repeatability. Fueling the engine with HVO resulted in the lowest CO₂, CO, THC, NO_x, and PM emissions across all phases of the driving cycle. The addition of pyrolytic oils to HVO increased NO_x and CO₂ levels while maintaining benefits in PM, THC, and CO reduction compared to the B7 reference fuel. The results demonstrated the applicability of HVO–TPO–PSO blends in engine applications while indicating the need for further durability studies. The adopted research approach addresses a significant knowledge gap by providing a unique analysis of the impact of HVO blends with tire and plastic pyrolysis oils on pollutant emissions and internal combustion engine fuel consumption under WLTC 3b operating conditions. Full article

(This article belongs to the Section I2: Energy and Combustion Science)

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33 pages, 1023 KB

Open AccessArticle

Forecasting Renewable Power Generation by Employing a Probabilistic Accumulation Non-Homogeneous Grey Model

by Peng Zhang, Jinsong Hu, Kelong Zheng, Wenqing Wu and Xin Ma

Energies 2025, 18(18), 5037; https://doi.org/10.3390/en18185037 - 22 Sep 2025

Viewed by 341

Abstract

Accurately predicting annual renewable power generation is critical for advancing energy structure transformation, ensuring energy security, and fostering sustainable development. In this study, a probabilistic non-homogeneous grey model (PNGM) is proposed to address this forecasting challenge. Firstly, the proposed model is constructed by [...] Read more.

Accurately predicting annual renewable power generation is critical for advancing energy structure transformation, ensuring energy security, and fostering sustainable development. In this study, a probabilistic non-homogeneous grey model (PNGM) is proposed to address this forecasting challenge. Firstly, the proposed model is constructed by integrating a Probabilistic Accumulation Generation Operator with the classical non-homogeneous grey model. Secondly, the Whale Optimization Algorithm is utilized to tune the parameters of the operator, thereby enhancing the extraction of valid information required for modeling. Furthermore, the superiority of the new model in information extraction and predictive performance is validated using synthetic datasets. Finally, it is applied to forecast renewable power generation in the United States, Russia, and India. The result exhibits significantly superior performance compared to the comparative models. Additionally, this study provides projections of renewable power generation for the United States, Russia, and India from 2025 to 2030, and the uncertainty intervals of the predicted values are estimated using the Bootstrap method. These results can provide reliable decision support for energy sectors and policymakers. Full article

(This article belongs to the Special Issue The Future of Renewable Energy: 2nd Edition)

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20 pages, 4502 KB

Open AccessArticle

Virtual Energy Replication Framework for Predicting Residential PV Power, Heat Pump Load, and Thermal Comfort Using Weather Forecast Data

by Daud Mustafa Minhas, Muhammad Usman, Irtaza Bashir Raja, Aneela Wakeel, Muzaffar Ali and Georg Frey

Energies 2025, 18(18), 5036; https://doi.org/10.3390/en18185036 - 22 Sep 2025

Viewed by 332

Abstract

It is essential to balance energy supply and demand in residential buildings through accurate forecasting of energy use due to varying daily and seasonal residential building loads. This study demonstrates a data-driven Virtual Energy Replication Framework (VERF) to predict the behavior of residential [...] Read more.

It is essential to balance energy supply and demand in residential buildings through accurate forecasting of energy use due to varying daily and seasonal residential building loads. This study demonstrates a data-driven Virtual Energy Replication Framework (VERF) to predict the behavior of residential buildings using weather forecast data. The framework integrates supervised machine learning models and time-ahead weather parameters to estimate photovoltaic (PV) power production, heat pump energy consumption, and indoor thermal comfort. The accuracy of prediction models is validated using TRNSYS simulations of a typical household in Saarbrucken, Germany, a temperate oceanic climate region. The XGBoost model exhibits the highest reliability, achieving a root mean square error (RMSE) of 0.003 kW for PV power generation and 0.025 kW for heat pump energy use, with R² scores of 0.94 and 0.87, respectively. XGBoost and random forest regression models perform well in predicting PV generation and HP electricity load, with mean prediction errors of 5.27–6% and 0–7.7%, respectively. In addition, the thermal comfort index (PPD) is predicted with an RMSE of 1.84 kW and an R² score of 0.80 using the XGBoost model. The mean prediction error remains between 2.4% (XGBoost regression) and −11.5% (lasso regression) throughout the forecasted data. Because the framework requires no real-time instrumentation or detailed energy modelling, it is scalable and adaptable for smart building energy systems, and has particular value for Building-Integrated Photovoltaics (BIPV) demonstration projects on account of its predictive load-matching capabilities. The research findings justify the applicability of VERF for efficient and sustainable energy management using weather-informed prediction models in residential buildings. Full article

(This article belongs to the Special Issue Application of Machine Learning Tools for Energy System)

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21 pages, 1833 KB

Open AccessReview

A Review of Green Hydrogen Technologies and Their Role in Enabling Sustainable Energy Access in Remote and Off-Grid Areas Within Sub-Saharan Africa

by Nkanyiso Msweli, Gideon Ude Nnachi and Coneth Graham Richards

Energies 2025, 18(18), 5035; https://doi.org/10.3390/en18185035 - 22 Sep 2025

Viewed by 822

Abstract

Electricity access deficits remain acute in Sub-Saharan Africa (SSA), where more than 600 million people lack reliable supply. Green hydrogen, produced through renewable-powered electrolysis, is increasingly recognized as a transformative energy carrier for decentralized systems due to its capacity for long-duration storage, sector [...] Read more.

Electricity access deficits remain acute in Sub-Saharan Africa (SSA), where more than 600 million people lack reliable supply. Green hydrogen, produced through renewable-powered electrolysis, is increasingly recognized as a transformative energy carrier for decentralized systems due to its capacity for long-duration storage, sector coupling, and near-zero carbon emissions. This review adheres strictly to the PRISMA 2020 methodology, examining 190 records and synthesizing 80 peer-reviewed articles and industry reports released from 2010 to 2025. The review covers hydrogen production processes, hybrid renewable integration, techno-economic analysis, environmental compromises, global feasibility, and enabling policy incentives. The findings show that Alkaline (AEL) and PEM electrolyzers are immediately suitable for off-grid scenarios, whereas Solid Oxide (SOEC) and Anion Exchange Membrane (AEM) electrolyzers present high potential for future deployment. For Sub-Saharan Africa (SSA), the levelized costs of hydrogen (LCOH) are in the range of EUR5.0–7.7/kg. Nonetheless, estimates from the learning curve indicate that these costs could fall to between EUR1.0 and EUR1.5 per kg by 2050, assuming there is (i) continued public support for the technology innovation, (ii) appropriate, flexible, and predictable regulation, (iii) increased demand for hydrogen, and (iv) a stable and long-term policy framework. Environmental life-cycle assessments indicate that emissions are nearly zero, but they also highlight serious concerns regarding freshwater usage, land occupation, and dependence on platinum group metals. Namibia, South Africa, and Kenya exhibit considerable promise in the early stages of development, while Niger demonstrates the feasibility of deploying modular, community-scale systems in challenging conditions. The study concludes that green hydrogen cannot be treated as an integrated solution but needs to be regarded as part of blended off-grid systems. To improve its role, targeted material innovation, blended finance, and policies bridging export-oriented applications to community-scale access must be established. It will then be feasible to ensure that hydrogen contributes meaningfully to the attainment of Sustainable Development Goal 7 in SSA. Full article

(This article belongs to the Section A: Sustainable Energy)

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20 pages, 2119 KB

Open AccessArticle

Power Outage Prediction on Overhead Power Lines on the Basis of Their Technical Parameters: Machine Learning Approach

by Vadim Bol’shev, Dmitry Budnikov, Andrei Dzeikalo and Roman Korolev

Energies 2025, 18(18), 5034; https://doi.org/10.3390/en18185034 - 22 Sep 2025

Viewed by 463

Abstract

In this study, data on the characteristics of overhead power lines of high voltage was used in a classification task to predict power supply outages by means of a supervised machine learning technique. In order to choose the most optimal features for power [...] Read more.

In this study, data on the characteristics of overhead power lines of high voltage was used in a classification task to predict power supply outages by means of a supervised machine learning technique. In order to choose the most optimal features for power outage prediction, an Exploratory Data Analysis on power line parameters was carried out, including statistical and correlational methods. For the given task, five classifiers were considered as machine learning algorithms: Support Vector Machine, Logistic Regression, Random Forest, and two gradient-boosting algorithms over decisive trees LightGBM Classifier and CatBoost Classifier. To automate the process of data conversion and eliminate the possibility of data leakage, Pipeline and Column Transformers (builder of heterogeneous features) were applied; data for the models was prepared using One-Hot Encoding and standardization techniques. The data were divided into training and validation samples through cross-validation with stratified separation. The hyperparameters of the classifiers were adjusted using optimization methods: randomized and exhaustive search over specified parameter values. The results of the study demonstrated the potential for predicting power failures on 110 kV overhead power lines based on data on their parameters, as can be seen from the derived quality metrics of tuned classifiers. The best quality of outage prediction was achieved by the Logistic Regression model with quality metrics ROC AUC equal to 0.78 and AUC-PR equal to 0.68. In the final phase of the research, an analysis of the influence of power line parameters on the failure probability was made using the embedded method for determining the feature importance of various models, including estimating the vector of regression coefficients. It allowed for the evaluation of the numerical impact of power line parameters on power supply outages. Full article

(This article belongs to the Special Issue Future Multi-Energy Smart-Grids: Advances in Operation, Control, and Monitoring)

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18 pages, 3228 KB

Open AccessArticle

Driver-Oriented Adaptive Equivalent Consumption Minimization Strategy for Plug-in Hybrid Electric Buses

by Xiang Tian, Ma Wan, Xinqiang Chen, Yingfeng Cai, Xiaodong Sun and Zhen Zhu

Energies 2025, 18(18), 5033; https://doi.org/10.3390/en18185033 - 22 Sep 2025

Viewed by 356

Abstract

The adaptability of the supervisory control strategy of plug-in hybrid electric buses (PHEBs) to different driving styles determines the energy-saving performance. This paper proposes a driver-oriented adaptive equivalent consumption minimization strategy (ECMS) for PHEBs. The strategy aims to improve the fuel economy of [...] Read more.

The adaptability of the supervisory control strategy of plug-in hybrid electric buses (PHEBs) to different driving styles determines the energy-saving performance. This paper proposes a driver-oriented adaptive equivalent consumption minimization strategy (ECMS) for PHEBs. The strategy aims to improve the fuel economy of PHEBs as much as possible by adapting to different driving styles while satisfying the physical constraints of the hybrid power system. Firstly, an online driving style recognition algorithm based on the Fuzzy K-means (FKM) algorithm and the random forest (RF) method is devised, in which the FKM algorithm is used to preprocess the feature parameters related to driving styles and the RF method is utilized to identify the driver’s driving style. Secondly, the driving style recognition results are introduced into the ECMS framework to form a driver-oriented energy management strategy. Finally, the proposed control strategy is verified using both Matlab/Simulink and Hardware-in-the-Loop. The verification results demonstrate that the proposed control strategy improves the fuel economy of PHEBs. Full article

(This article belongs to the Special Issue Renewable Energy Management System and Power Electronic Converters)

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15 pages, 3968 KB

Open AccessArticle

Numerical Simulation and Theoretical Analysis of Wave Loads on Truss Legs for Offshore Energy Platforms

by Haoxun Yuan, Yingchun Xie, Di-Lin Chen, Jintong Huang, Cheng-Long Zhou, Xiangkun Li, Guijie Liu and Jinchi Zhu

Energies 2025, 18(18), 5032; https://doi.org/10.3390/en18185032 - 22 Sep 2025

Viewed by 359

Abstract

Jack-up offshore platforms, supported by truss legs, are integral to the development of marine energy resources, including oil, gas, and offshore wind. Due to the structural complexity of truss legs, accurately quantifying wave loads is crucial for ensuring the safety and efficiency of [...] Read more.

Jack-up offshore platforms, supported by truss legs, are integral to the development of marine energy resources, including oil, gas, and offshore wind. Due to the structural complexity of truss legs, accurately quantifying wave loads is crucial for ensuring the safety and efficiency of energy extraction operations. In this work, a numerical wave tank approach combined with theoretical analysis is employed comprehensively to investigate wave loads on truss legs, with a particular emphasis on the effects of component forces and inflow angle. The results demonstrate that wave loads are not solely dependent on member dimensions. The influencing factors affecting component forces include water depth and phase differences between structural units, which amplify the contribution of the component forces of members near the free surface and without phase difference to the total force. Furthermore, the total force varies periodically with the inflow angle in cycles of 60°. Notably, the influence of inflow angle on the total force becomes negligible when the wavelength substantially exceeds the pile spacing. This framework fundamentally provides a theoretical basis for the structural optimization of Jack-up offshore platform support systems, thereby enhancing the safety and reliability of energy infrastructure. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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25 pages, 8073 KB

Open AccessArticle

Maximum Efficiency Power Point Tracking in Reconfigurable S-LCC Compensated Wireless EV Charging Systems with Inherent CC and CV Modes Across Wide Operating Conditions

by Pabba Ramesh, Pongiannan Rakkiya Goundar Komarasamy, Ali ELrashidi, Mohammed Alruwaili and Narayanamoorthi Rajamanickam

Energies 2025, 18(18), 5031; https://doi.org/10.3390/en18185031 - 22 Sep 2025

Viewed by 411

Abstract

The wireless charging of electric vehicles (EVs) has drawn much attention as it can ease the charging process under different charging situations and environmental conditions. However, power transfer rate and efficiency are the critical parameters for the wide adaptation of wireless charging systems. [...] Read more.

The wireless charging of electric vehicles (EVs) has drawn much attention as it can ease the charging process under different charging situations and environmental conditions. However, power transfer rate and efficiency are the critical parameters for the wide adaptation of wireless charging systems. Different investigations are presented in the literature that have aimed to improve power transfer efficiency and to maintain constant power at the load side. This paper introduces a Maximum Efficiency Point Tracking (MEPT) system designed specifically for a reconfigurable S-LCC compensated wireless charging system. The reconfigurable nature of the S-LCC system supports the constant current (CC) and constant voltage (CV) mode of operation by operating S-LCC and S-SP mode. The proposed system enhances power transfer efficiency under load fluctuations, coil misalignments, and a wide range of operating conditions. The developed S-LCC compensated system inherently maintains the power transfer rate constantly under a majority of load variations. Meanwhile, the inclusion of the MEPT method with the S-LCC system provides stable and maximum output under different coupling and load variations. The proposed MEPT approach uses a feedback mechanism to track and maintain the maximum efficiency point by iteratively adjusting the DC-DC converter duty ratio and by monitoring load power. The proposed approach was designed and tested in a 3.3 kW laboratory scale prototype module at an operating frequency of 85 kHz. The simulation and hardware results show that the developed system provides stable maximum power under a wider range of load and coupling variations. Full article

(This article belongs to the Topic Electric Vehicles Smart Charging: Strategies, Technologies, and Challenges)

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24 pages, 1390 KB

Open AccessReview

Modern Systems for Nuclear Fuel Storage and Monitoring: An Analysis of Technological Trends, Challenges, and Future Perspectives

by Bogdan-Teodor Godea, Ana Gogorici, Daniela-Monica Iordache, Adriana-Gabriela Șchiopu, Daniel-Constantin Anghel and Mariea Deaconu

Energies 2025, 18(18), 5030; https://doi.org/10.3390/en18185030 - 22 Sep 2025

Viewed by 902

Abstract

The storage and monitoring of nuclear fuel, whether spent or fresh, are key components of the nuclear energy life cycle, with significant implications for safety and sustainability. With the global focus on carbon neutrality, interest in advanced management solutions is rising. This paper [...] Read more.

The storage and monitoring of nuclear fuel, whether spent or fresh, are key components of the nuclear energy life cycle, with significant implications for safety and sustainability. With the global focus on carbon neutrality, interest in advanced management solutions is rising. This paper provides a comprehensive analysis of modern technologies for the design, storage, and monitoring of nuclear fuel, highlighting current trends and future challenges. The study encompasses both spent and fresh nuclear fuel, with a focus on radiological safety, structural integrity, and digital monitoring. Data were organized into the following categories: storage types (wet/dry), monitored parameters, surveillance technologies (sensors, AI, IoT, and Digital Twin), simulation models, and emerging directions. A comparison between fresh and spent fuel shows a clear shift toward intelligent systems using non-invasive sensors, deep-learning algorithms, and decentralized architectures (e.g., blockchain-IoT). Despite progress, challenges remain, such as limited interoperability across system generations and insufficient experimental validation. This paper provides a solid foundation for researchers, suggesting future directions that include the full integration of AI in monitoring, broader numerical simulations for reliability, and the standardization of digital interfaces. These measures could significantly enhance the safety and efficiency of nuclear fuel storage systems. Full article

(This article belongs to the Section B4: Nuclear Energy)

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19 pages, 1661 KB

Open AccessArticle

A Reinforcement Learning-Based Approach for Distributed Photovoltaic Carrying Capacity Analysis in Distribution Grids

by Shumin Sun, Song Yang, Peng Yu, Yan Cheng, Jiawei Xing, Yuejiao Wang, Yu Yi, Zhanyang Hu, Liangzhong Yao and Xuanpei Pang

Energies 2025, 18(18), 5029; https://doi.org/10.3390/en18185029 - 22 Sep 2025

Viewed by 342

Abstract

Driven by the “double carbon” goals, the penetration rate of distributed photovoltaics (PV) in distribution networks has increased rapidly. However, the continuous growth of distributed PV installed capacity poses significant challenges to the carrying capacity of distribution networks. Reinforcement learning (RL), with its [...] Read more.

Driven by the “double carbon” goals, the penetration rate of distributed photovoltaics (PV) in distribution networks has increased rapidly. However, the continuous growth of distributed PV installed capacity poses significant challenges to the carrying capacity of distribution networks. Reinforcement learning (RL), with its capability to handle high-dimensional nonlinear problems, plays a critical role in analyzing the carrying capacity of distribution networks. This study constructs an evaluation model for distributed PV carrying capacity and proposes a corresponding quantitative evaluation index system by analyzing the core factors influencing it. An optimization scheme based on deep reinforcement learning is adopted, introducing the Deep Deterministic Policy Gradient (DDPG) algorithm to solve the evaluation model. Finally, simulations on the IEEE-33 bus system validate the good feasibility of the reinforcement learning approach for this problem. Full article

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17 pages, 650 KB

Open AccessEditor’s ChoiceArticle

Optimization of Biomass Delivery Through Artificial Intelligence Techniques

by Marta Wesolowska, Dorota Żelazna-Jochim, Krystian Wisniewski, Jaroslaw Krzywanski, Marcin Sosnowski and Wojciech Nowak

Energies 2025, 18(18), 5028; https://doi.org/10.3390/en18185028 - 22 Sep 2025

Viewed by 400

Abstract

Efficient and cost-effective biomass logistics remain a significant challenge due to the dynamic and nonlinear nature of supply chains, as well as the scarcity of comprehensive data on this topic. As biomass plays an increasingly important role in sustainable energy systems, managing its [...] Read more.

Efficient and cost-effective biomass logistics remain a significant challenge due to the dynamic and nonlinear nature of supply chains, as well as the scarcity of comprehensive data on this topic. As biomass plays an increasingly important role in sustainable energy systems, managing its complex supply chains efficiently is crucial. Traditional logistics methods often struggle with the dynamic, nonlinear, and data-scarce nature of biomass supply, especially when integrating local and international sources. To address these challenges, this study aims to develop an innovative modular artificial neural network (ANN)-based Biomass Delivery Management (BDM) model to optimize biomass procurement and supply for a fluidized bed combined heat and power (CHP) plant. The comprehensive model integrates technical, economic, and geographic parameters to enable supplier selection, optimize transport routes, and inform fuel blending strategies, representing a novel approach in biomass logistics. A case study based on operational data confirmed the model’s ability to identify cost-effective and quality-compliant biomass sources. Evaluated using empirical operational data from a Polish CHP plant, the ANN-based model demonstrated high predictive accuracy (MAE = 0.16, MSE = 0.02, R² = 0.99) within the studied scope. The model effectively handled incomplete datasets typical of biomass markets, aiding in supplier selection decisions and representing a proof-of-concept for optimizing Central European biomass logistics. The model was capable of generalizing supplier recommendations based on input variables, including biomass type, unit price, and annual demand. The proposed framework supports both strategic and real-time logistics decisions, providing a robust tool for enhancing supply chain transparency, cost efficiency, and resilience in the renewable energy sector. Future research will focus on extending the dataset and developing hybrid models to strengthen supply chain stability and adaptability under varying market and regulatory conditions. Full article

(This article belongs to the Topic AI and Computational Methods for Modelling, Simulations and Optimizing of Advanced Systems: Innovations in Complexity, Second Edition)

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24 pages, 16914 KB

Open AccessArticle

Unsteady Aerodynamic Errors in BEM Predictions Under Yawed Flow: CFD-Based Insights into Flow Structures for the NREL Phase VI Rotor

by Jiahong Hu, Hui Yang and Jiaxin Yuan

Energies 2025, 18(18), 5027; https://doi.org/10.3390/en18185027 - 22 Sep 2025

Viewed by 469

Abstract

Efficient prediction of aerodynamic loads on wind turbine blades under yawed inflow remains challenging due to the complexity of three-dimensional unsteady flow phenomena. In this work, a modified blade element momentum (BEM) method, incorporating multiple correction models, is systematically compared with high-fidelity computational [...] Read more.

Efficient prediction of aerodynamic loads on wind turbine blades under yawed inflow remains challenging due to the complexity of three-dimensional unsteady flow phenomena. In this work, a modified blade element momentum (BEM) method, incorporating multiple correction models, is systematically compared with high-fidelity computational fluid dynamics (CFD) simulations for the NREL Phase VI wind turbine across a range of inflow velocities (7–15 m/s) and yaw angles (

0^{°}

–

60^{°}

). A normalized absolute error metric, referenced to experimental measurements, is employed to quantify prediction discrepancies at different yaw conditions, wind speeds, and spanwise blade locations. Results indicate that the corrected BEM method maintains good agreement with measurements under non-yawed attached flow, with errors within 2%, but its accuracy declines substantially in separated and yawed flow regimes, where errors can exceed 20% at high yaw angles (e.g.,

60^{°}

) and low tip-speed ratios. CFD flow-field visualizations, including vorticity and Q-criterion iso-surfaces, reveal that yawed inflow strengthens vortex interactions on the leeward side and generates Coriolis-driven spanwise vortex structures, promoting stall progression from tip to root. These unsteady phenomena induce load fluctuations that are not captured by steady-state BEM formulations. Based on these insights, future studies could incorporate vortex structure and spanwise flow features extracted from CFD into unsteady correction models for BEM, enhancing prediction robustness under complex operating conditions. Full article

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21 pages, 2145 KB

Open AccessArticle

Optimized Chemical Absorption Process for CO₂ Removal in a Steel Plant

by Valentina Schiattarella and Stefania Moioli

Energies 2025, 18(18), 5026; https://doi.org/10.3390/en18185026 - 22 Sep 2025

Viewed by 410

Abstract

The steel industry is a significant contributor to global CO₂ emissions due to the highly energy-intensive nature of its production processes. Specifically, steel production involves the conversion of iron ore into steel through processes such as the blast furnace method, which result [...] Read more.

The steel industry is a significant contributor to global CO₂ emissions due to the highly energy-intensive nature of its production processes. Specifically, steel production involves the conversion of iron ore into steel through processes such as the blast furnace method, which result in significant greenhouse gas emissions due to the combustion of fossil fuels and the chemical reactions involved. To address this challenge, Carbon Capture Utilization and Storage (CCUS) technologies are essential for reducing emissions by capturing CO₂ at its source, preventing its release into the atmosphere. This study focuses on a French steel plant with an annual production capacity of 6.6 million tons of steel and seeks to optimize the chemical absorption process by using a 30 wt.% MonoEthanolAmine (MEA) aqueous solution. To the authors’ knowledge, studies on this solvent, widely used for treating other types of flue gases, are still not present in the literature for the application to this gaseous stream. The goal is to minimize the thermal energy required for solvent regeneration by optimizing some key parameters. Additionally, an economic analysis is carried out, with a particular focus on different achievable CO₂ recovery ratios, with costs quantified as 102.48, 104.47, and 224.36 [$/t CO₂ removed] for 90%, 95%, and 99% CO₂ recovery, respectively. Full article

(This article belongs to the Section B3: Carbon Emission and Utilization)

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17 pages, 5007 KB

Open AccessArticle

Experimental Comparative Analysis of Energy Production in HAWT with Bio-Inspired Active Oscillating Vortex Generators

by Hector G. Parra, Gabriel H. Castiblanco and Elvis E. Gaona

Energies 2025, 18(18), 5025; https://doi.org/10.3390/en18185025 - 22 Sep 2025

Viewed by 404

Abstract

This study presents a comparative analysis of horizontal-axis wind turbines (HAWTs) equipped with and without bio-inspired active oscillating vortex generators (VGs). The experimental investigation examines key aspects of mechanical integration and the resulting variations in aerodynamic behavior, demonstrating measurable improvements in electrical power [...] Read more.

This study presents a comparative analysis of horizontal-axis wind turbines (HAWTs) equipped with and without bio-inspired active oscillating vortex generators (VGs). The experimental investigation examines key aspects of mechanical integration and the resulting variations in aerodynamic behavior, demonstrating measurable improvements in electrical power output. The VGs were designed and implemented using servomechanisms and embedded control systems to enable oscillatory motion during operation. Experimental findings were validated against CFD simulations, indicating that the use of VGs increases annual energy production efficiency by 16.7%, primarily due to the stabilization of wake turbulence. While a reduction in output voltage was observed at wind speeds below 5 m/s, the VGs exhibited enhanced performance under variable wind conditions. These results highlight the potential of combining biomimetic design principles with electronically actuated flow-control devices to advance HAWT technology, improving energy efficiency and contributing to operational sustainability. Full article

(This article belongs to the Special Issue Advanced Control Systems in Wind Energy: Optimizing Performance from Component to Grid Integration)

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27 pages, 2192 KB

Open AccessArticle

Multi-Timescale Coordinated Planning of Wind, Solar, and Energy Storage Considering Generalized Adequacy

by Jian Yin, Lixiang Fu, Liming Xiao, Zijian Meng, Yuejun Luo, Zili Chen and Zhaoyuan Wu

Energies 2025, 18(18), 5024; https://doi.org/10.3390/en18185024 - 22 Sep 2025

Viewed by 379

Abstract

The core of power system planning lies in optimizing resource portfolios to ensure reliable electricity supply, with generalized adequacy serving as a key indicator of supply security. As the share of renewable energy increases, the mechanisms underlying system security undergo profound changes, extending [...] Read more.

The core of power system planning lies in optimizing resource portfolios to ensure reliable electricity supply, with generalized adequacy serving as a key indicator of supply security. As the share of renewable energy increases, the mechanisms underlying system security undergo profound changes, extending the concept of adequacy from mere power balance to encompass flexibility and inertia support while exhibiting spatial and temporal heterogeneity and wide-area characteristics. Traditional planning approaches can no longer meet these evolving requirements. To address this, a power grid coordinated planning framework is proposed based on generalized adequacy, which integrates power and energy adequacy, flexibility adequacy, and inertia adequacy. Within this framework, generalized adequacy metrics and their quantification methods are developed, and a coordinated planning strategy for wind power, photovoltaic power, multi-timescale energy storage, and transmission expansion is introduced to enhance renewable energy utilization and meet flexibility needs across multiple timescales. Furthermore, a scheme evaluation and selection method based on generalized adequacy is proposed. Finally, the effectiveness of the proposed approach is validated through case studies on the IEEE 24-bus system. Full article

(This article belongs to the Section A: Sustainable Energy)

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19 pages, 1596 KB

Open AccessArticle

Multistage Reaction Characteristics and Ash Mineral Evolution in Coal–Biomass Co-Combustion Process

by Yun Hu, Bo Peng, Songshan Cao, Zenghui Hou, Sheng Wang and Zefeng Ge

Energies 2025, 18(18), 5023; https://doi.org/10.3390/en18185023 - 22 Sep 2025

Viewed by 479

Abstract

This study investigates the combustion characteristics and ash behavior of coal–biomass co-combustion using Zhujixi coal and corn straw in a fixed-bed system. The research analyzes combustion stage division, gas release patterns, and mineral evolution of ash under varying blending ratios. Results indicate that [...] Read more.

This study investigates the combustion characteristics and ash behavior of coal–biomass co-combustion using Zhujixi coal and corn straw in a fixed-bed system. The research analyzes combustion stage division, gas release patterns, and mineral evolution of ash under varying blending ratios. Results indicate that biomass addition modifies the dynamic features of the combustion process by advancing the CO₂ release peak; extending the release of CO, CH₄, and H₂; and enhancing the completeness of char oxidation. At moderate blending levels (20–60%), oxygen utilization is significantly improved and combustion stability is strengthened. Ash fusion temperatures exhibit a consistent decline with increasing biomass proportion due to the formation of low-melting eutectic phases such as KAlSiO₄ and K, Ca-based phosphates. Mineralogical analysis further reveals that coal ash components promote the immobilization of alkali metals, thereby suppressing potassium volatilization. A blending ratio of 40% demonstrates the most favorable balance between burnout performance, oxygen efficiency, and alkali fixation, surpassing both pure coal and high-ratio biomass conditions. This optimized ratio not only improves energy conversion efficiency but also reduces slagging and corrosion risks, offering practical guidance for cleaner coal power transformation, stable boiler operation, and long-term reduction of carbon and pollutant emissions. Full article

(This article belongs to the Section I2: Energy and Combustion Science)

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12 pages, 2702 KB

Open AccessArticle

Mitigation of Magnetic Field Levels in Bipolar Transmission Lines of 500 and 600 kV in HVDC

by Jorge Luis Aguilar Marin, Luis Cisneros Villalobos, José Gerardo Vera-Dimas, Jorge Sánchez Jaime, Hugo Albeiro Saldarriaga-Noreña and Hugo Herrera Gutiérrez

Energies 2025, 18(18), 5022; https://doi.org/10.3390/en18185022 - 22 Sep 2025

Viewed by 434

Abstract

High-Voltage Direct Current (HVDC) systems are transforming the global energy landscape, distinguished by their efficiency, stability, and low impact on the electrical grid. One of the challenges of HVDC transmission line design is assessing the generated stray magnetic field, as it can have [...] Read more.

High-Voltage Direct Current (HVDC) systems are transforming the global energy landscape, distinguished by their efficiency, stability, and low impact on the electrical grid. One of the challenges of HVDC transmission line design is assessing the generated stray magnetic field, as it can have negative effects on human health and the environment. This study presents an analytical methodology for calculating the magnetic field density at any point along an HVDC line corridor. It considers the spatial configuration, the current per pole, and the location of the conductors. The equations allow for the calculation of the horizontal and vertical components of the field, as well as its total magnitude. A practical case study of a ±500 and ±600 kV HVDC two-pole transmission line is presented. The methodology was programmed in MATLAB^® version R2024a to calculate the magnetic field density, and the results are consistent with those obtained with the established methodology. The presented methodology can be applied to monopolar and two-pole HVDC overhead transmission lines, offering speed and accuracy. Full article

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23 pages, 3493 KB

Open AccessArticle

Comparative Study on Carbon Emissions and Economics of Three Types of Slab Systems in the Materialization Stages

by Yu Wang, Ling Dong and Hong Xian Li

Energies 2025, 18(18), 5021; https://doi.org/10.3390/en18185021 - 21 Sep 2025

Viewed by 331

Abstract

As one of the most important sources of carbon emissions, the construction industry consumes approximately 30% to 40% of global energy and emits about 30% of global greenhouse gases. Therefore, low-carbon emission reduction in the construction industry is an important means for China [...] Read more.

As one of the most important sources of carbon emissions, the construction industry consumes approximately 30% to 40% of global energy and emits about 30% of global greenhouse gases. Therefore, low-carbon emission reduction in the construction industry is an important means for China to achieve its “3060” strategic goals. In this context, prefabricated buildings have become a development direction for the transformation and upgrading of the construction industry due to their green, low-carbon, and efficient characteristics. Jiangsu Province in China has taken the lead in promoting the application of “three slabs”. Currently, the precast concrete floor slabs in the province mainly use two types: laminated slabs and prestressed hollow slabs. This article takes three types of slab systems (laminated slabs, prestressed hollow slabs, cast in-site slabs) as the research objects, compares and analyzes the construction process of the three in the materialization stage, establishes a calculation model for carbon emissions and comprehensive costs in the materialization stages, and conducts a comparative analysis of carbon emissions and economics from both environmental and economic perspectives. Research has shown that during the materialization stage, cast in-site slabs have the highest carbon emissions per unit area, with an increase of approximately 71.3% and 74.3% compared to laminated slabs and prestressed hollow slabs, respectively. The highest construction and installation cost per unit area is also for cast in-site slabs, which are increased by about 113.8% and 64.9%, respectively, compared to laminated slabs and prestressed hollow slabs. Among them, material costs are the most significant factor affecting construction and installation costs. The comprehensive cost per unit area of cast in-site slabs is much higher than that of laminated slabs and prestressed hollow slabs, with the construction and installation costs being the most important factors affecting the comprehensive cost. Therefore, compared with cast in-site slabs, laminated slabs and prestressed hollow slabs have significant advantages in carbon emissions and economics and thus have practical significance for carbon reduction in the construction industry and are worth promoting and further developing. Full article

(This article belongs to the Section B3: Carbon Emission and Utilization)

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30 pages, 7291 KB

Open AccessEditor’s ChoiceArticle

Energy Criteria in Adaptive Reuse Decision-Making: A Hybrid DEMATEL-ANP Model for Selecting New Uses of a Historic Building in Poland

by Elżbieta Radziszewska-Zielina, Grzegorz Śladowski, Bartłomiej Szewczyk, Małgorzata Fedorczak-Cisak, Alicja Kowalska-Koczwara, Tadeusz Tatara and Krzysztof Barnaś

Energies 2025, 18(18), 5020; https://doi.org/10.3390/en18185020 - 21 Sep 2025

Viewed by 410

Abstract

Historic buildings make up a significant proportion of the existing building stock. Most are characterised by poor technical condition and high energy demand. In Poland, many historic buildings are still in use today, but it is also common to find these buildings subjected [...] Read more.

Historic buildings make up a significant proportion of the existing building stock. Most are characterised by poor technical condition and high energy demand. In Poland, many historic buildings are still in use today, but it is also common to find these buildings subjected to adaptive reuse. Adaptive reuse, often combined with modernisation, is problematic, especially in terms of finding a use that is optimal in the light of use-specific decision criteria. In previous studies, the authors used and developed the potential for the modelling and structural analysis of decision-making problems for the selection of new uses for historic buildings. In this paper, we present a test of this methodology on a Polish historic building. To further the application of our approach in sustainability-focused contexts, we performed the analysis using criteria focused on environmental and energy performance, in addition to other established criteria. In our study, the highest ranking use was a kindergarten, which scored 18% higher than the second-ranked alternative and over 90% higher than the lowest-ranked alternative. Full article

(This article belongs to the Special Issue Green Innovation and Sustainable Energy Transition: Opportunities and Challenges)

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18 pages, 3792 KB

Open AccessArticle

Achieving Power-Noise Balance in Wind Farms by Fine-Tuning the Layout with Reinforcement Learning

by Guangxing Guo, Weijun Zhu, Ziliang Zhang, Wenzhong Shen and Zhe Chen

Energies 2025, 18(18), 5019; https://doi.org/10.3390/en18185019 - 21 Sep 2025

Viewed by 406

Abstract

Wind farms situated in proximity to residential areas present environmental challenges, primarily due to noise emissions. Rectangular and parallelogram layouts are commonly employed in current wind farm designs owing to their simplicity and visual appeal. However, such configurations often experience significant power loss [...] Read more.

Wind farms situated in proximity to residential areas present environmental challenges, primarily due to noise emissions. Rectangular and parallelogram layouts are commonly employed in current wind farm designs owing to their simplicity and visual appeal. However, such configurations often experience significant power loss under certain wind directions because of intense wake interactions. This paper proposes a layout fine-tuning strategy for low-noise wind farm design. Within a reinforcement learning framework integrated with an engineering wake model and a noise propagation model, the positions of two turbines (controlled by two variables) are optimized. The noise propagation model was validated for idealized long-range sound propagation over flat terrain with acoustically soft surfaces. A case study was conducted on a 12-turbine wind farm located on a flat plain in China, with a noise threshold of 45 dB(A) used to assess the noise impact area. Optimization results demonstrate that the proposed method achieves a balance between power output and noise reduction compared to the original regular layout: Annual Energy Production (AEP) increased slightly by 0.16%, while the noise impact area was reduced by 6.0%. Although these improvements appear modest, the potential of the proposed methodology warrants further investigation. Full article

(This article belongs to the Special Issue Advancements in Wind Farm Design and Optimization)

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38 pages, 6824 KB

Open AccessArticle

Strategic Planning for Power System Decarbonization Using Mixed-Integer Linear Programming and the William Newman Model

by Jairo Mateo Valdez Castro and Alexander Aguila Téllez

Energies 2025, 18(18), 5018; https://doi.org/10.3390/en18185018 - 21 Sep 2025

Viewed by 492

Abstract

This paper proposes a comprehensive framework for strategic power system decarbonization planning that integrates the William Newman method (diagnosis–options–forecast–decision) with a multi-objective Mixed-Integer Linear Programming (MILP) model. The approach simultaneously minimizes (i) generation cost, (ii) expected cost of energy not supplied (Value of [...] Read more.

This paper proposes a comprehensive framework for strategic power system decarbonization planning that integrates the William Newman method (diagnosis–options–forecast–decision) with a multi-objective Mixed-Integer Linear Programming (MILP) model. The approach simultaneously minimizes (i) generation cost, (ii) expected cost of energy not supplied (Value of Lost Load, VoLL), (iii) demand response cost, and (iv) CO₂ emissions, subject to power balance, technical limits, and binary unit commitment decisions. The methodology is validated on the IEEE RTS 24-bus system with increasing demand profiles and representative cost and emission parameters by technology. Three transition pathways are analyzed: baseline scenario (no environmental restrictions), gradual transition (−50% target in 20 years), and accelerated transition (−75% target in 10 years). In the baseline case, the oil- and coal-dominated mix concentrates emissions (≈14 ktCO₂ and ≈12 ktCO₂, respectively). Under gradual transition, progressive substitution with wind and hydro reduces emissions by 15.38%, falling short of the target, showing that renewable expansion alone is insufficient without storage and demand-side management. In the accelerated transition, the model achieves −75% by year 10 while maintaining supply, with a cost–emissions trade-off highly sensitive to the carbon price. Results demonstrate that decarbonization is technically feasible and economically manageable when three enablers are combined: higher renewable penetration, storage capacity, and policy instruments that both accelerate fossil phase-out and valorize demand-side flexibility. The proposed framework is replicable and valuable for outlining realistic, verifiable transition pathways in power system planning. Full article

(This article belongs to the Special Issue Advances and Optimization of Electric Energy System—2nd Edition)

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23 pages, 1062 KB

Open AccessFeature PaperReview

Cybersecurity of Smart Grids: Requirements, Threats, and Countermeasures

by Edyta Karolina Szczepaniuk and Hubert Szczepaniuk

Energies 2025, 18(18), 5017; https://doi.org/10.3390/en18185017 - 21 Sep 2025

Viewed by 783

Abstract

Cybersecurity is a key factor influencing the development of the smart grid paradigm. The integration of information and communication technologies into energy networks introduces new cybersecurity requirements, vulnerabilities, and threats. Typical countermeasures and security measures require optimization and customization for implementation in a [...] Read more.

Cybersecurity is a key factor influencing the development of the smart grid paradigm. The integration of information and communication technologies into energy networks introduces new cybersecurity requirements, vulnerabilities, and threats. Typical countermeasures and security measures require optimization and customization for implementation in a distributed and heterogeneous smart grid environment. In this paper, we propose a holistic approach to smart grid cybersecurity by considering information security attributes at the level of requirements, threats, and countermeasures analysis. The results of the conducted review enabled us to develop a holistic cybersecurity framework for smart grids, while also analyzing the challenges and barriers related to security measures, as well as the possibilities for their mitigation. Full article

(This article belongs to the Section A1: Smart Grids and Microgrids)

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28 pages, 1799 KB

Open AccessReview

A Rapid Review of Hygrothermal Performance Metrics for Innovative Materials in Building Envelope Retrofits

by Robin Hilbrecht, Cynthia A. Cruickshank, Christopher Baldwin and Nicholas Scharf

Energies 2025, 18(18), 5016; https://doi.org/10.3390/en18185016 - 21 Sep 2025

Viewed by 448

Abstract

With government, industry, and public pressure to decarbonize the building sector through reducing embodied and operational emissions, there have been a wide range of innovative materials used in building envelope retrofits. Although these innovative materials, such as super insulating materials, bio-based insulation, and [...] Read more.

With government, industry, and public pressure to decarbonize the building sector through reducing embodied and operational emissions, there have been a wide range of innovative materials used in building envelope retrofits. Although these innovative materials, such as super insulating materials, bio-based insulation, and many others, are assessed on thermal performance and code requirements before use in retrofits, there is no unified standard assessment metric for hygrothermal performance of innovative materials in building envelope retrofits. This paper performs a rapid review of the available literature from January 2013 to March 2025 on hygrothermal performance assessment metrics used in retrofits. Using rapid review methods to search for records in Scopus, Web of Science, and Google Scholar, fifty-nine publications were selected for bibliometric and qualitative analysis. Most selected publications include discussions and analysis of relative humidity in the wall assembly post retrofit, moisture content, and mould index within the envelope. There is a research gap in publications considering hygrothermal damage functions such as freeze–thaw index, relative humidity and temperature (RHT) index, or condensation prediction. There is also a research gap in country and climate studies and analyses of in situ retrofits with innovative materials, and occupant comfort post retrofit. Full article

(This article belongs to the Special Issue Sustainable Built Environment: Energy Efficiency Technologies, Performance Evaluation and Indoor Environment Quality)

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18 pages, 6081 KB

Open AccessArticle

Novel Design of Conical-Shaped Wireless Charger for Unmanned Aerial Vehicles

by Ashraf Ali, Omar Saraereh and Andrew Ware

Energies 2025, 18(18), 5015; https://doi.org/10.3390/en18185015 - 21 Sep 2025

Viewed by 460

Abstract

This work presents a novel wireless charging system for unmanned aerial vehicles (UAVs), which employs conical-shaped coils that also function as landing gear. By integrating electromagnetic simulation, circuit modeling, and system-level evaluation, we introduce an innovative coil design that enhances wireless power transfer [...] Read more.

This work presents a novel wireless charging system for unmanned aerial vehicles (UAVs), which employs conical-shaped coils that also function as landing gear. By integrating electromagnetic simulation, circuit modeling, and system-level evaluation, we introduce an innovative coil design that enhances wireless power transfer (WPT) efficiency while reducing misalignment sensitivity. The conical geometry naturally facilitates mechanical alignment upon drone landing, thereby improving inductive coupling. High-frequency simulations were carried out to optimize the coil parameters and evaluate the link efficiency at 6.78 MHz, an ISM-designated frequency. Our experimental testing confirmed that the proposed conical coil achieves high power transfer efficiency (up to 94%) under practical conditions, validating the effectiveness of the geometry. The characteristics of the designed coil make it highly suitable for use with Class EF amplifiers operating in the same frequency range; however, detailed amplifier hardware implementation and efficiency characterization were beyond the scope of this study and are reserved for future work. The results demonstrate the potential of the proposed system for deployment in UAV field applications such as surveillance, delivery, and remote sensing. Full article

(This article belongs to the Special Issue Advances in Design, Operation and Maintenance Technology for Electric Power Equipment)

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14 pages, 4622 KB

Open AccessArticle

Pressure-Dependent Breakdown Voltage in SF₆/Epoxy Resin Insulation Systems: Electric Field Enhancement Mechanisms and Interfacial Synergy

by Lin Liu, Qiaogen Zhang, Xiangyang Peng, Xiaoang Li, Zheng Wang and Shihu Yu

Energies 2025, 18(18), 5014; https://doi.org/10.3390/en18185014 - 21 Sep 2025

Viewed by 360

Abstract

In SF₆ gas-insulated equipment, solid dielectrics critically degrade insulation performance by reducing the electric field’s ability to withstand gas gaps. To investigate the critical role played by solid dielectric surfaces during the initial phase of gas–solid interface discharge phenomena, this paper experimentally [...] Read more.

In SF₆ gas-insulated equipment, solid dielectrics critically degrade insulation performance by reducing the electric field’s ability to withstand gas gaps. To investigate the critical role played by solid dielectric surfaces during the initial phase of gas–solid interface discharge phenomena, this paper experimentally measures the AC breakdown voltage (U_bd) of both dielectric surface-initiated breakdown (DIBD) and electrode surface-initiated breakdown (EIBD) across eight types of post insulator samples. Tests are conducted in 36 mm SF₆ gas gaps under pressures ranging from 0.1 to 0.4 MPa. Combined with electrostatic field simulations, the results reveal that DIBD requires substantially lower U_bd than EIBD under comparable maximum electric field (E_max) conditions. As gas pressure increases, this difference becomes more pronounced. This phenomenon can be explained by three key mechanisms: First, due to the regulatory effect of dielectric materials and shielding electrodes on the electric field distribution, the high-electric-field zone along the gas–solid interface exhibits a longer effective discharge path compared to that in a pure gas gap. This configuration creates more favorable conditions for discharge initiation and subsequent propagation toward the opposite electrode. Second, microscopic irregularities on the dielectric surface induce stronger local electric field enhancement than comparable features on metallic electrodes. Third, in high-electric-field regions adjacent to the dielectric surface, desorption processes significantly enhance electron multiplication during gas discharge, and this enhancement effect becomes more pronounced as gas pressure increases, further lowering the discharge inception threshold. As a result, discharge initiation at dielectric interfaces requires less stringent electric field conditions compared to breakdown in a gas gap, especially at high gas pressure. This conclusion not only accounts for the saturation behavior in the U_bd-p characteristic of SF₆ gas–solid interface discharges but also explains why surface contaminants/defects disproportionately degrade interfacial insulation performance relative to their impact on gas gaps. Full article

(This article belongs to the Special Issue Recent Progress, Challenges and Outlooks of Insulation System in HVDC: 2nd Edition)

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21 pages, 3104 KB

Open AccessArticle

Advanced Structural Assessment of a Bucked-and-Wedged Configuration for the EU DEMO Tokamak Under a 16.5 T Magnetic Field

by Andrea Chiappa and Corrado Groth

Energies 2025, 18(18), 5013; https://doi.org/10.3390/en18185013 - 21 Sep 2025

Viewed by 336

Abstract

The pursuit of compact and efficient fusion energy systems necessitates innovative structural concepts capable of withstanding extreme operational conditions. This study presents a preliminary structural evaluation and stress assessment of a bucked-and-wedged configuration for the EU DEMO tokamak, targeting a peak magnetic field [...] Read more.

The pursuit of compact and efficient fusion energy systems necessitates innovative structural concepts capable of withstanding extreme operational conditions. This study presents a preliminary structural evaluation and stress assessment of a bucked-and-wedged configuration for the EU DEMO tokamak, targeting a peak magnetic field of 16.5 T. The proposed concept leverages mutual wedging of the Toroidal Field (TF) coils and their interaction with the Central Solenoid (CS) to optimize stress distribution in the inner legs, a critical region in high-field fusion reactors. To address the significant tangential forces arising during plasma operation, the design integrates outer inter-coil structures and shear pins to enhance mechanical stability. A hybrid simulation approach—coupling 3D electromagnetic and structural finite element analyses—is employed to assess stress behavior and structural integrity under both in-plane and out-of-plane loading conditions. The results contribute to the optimization study of high-field fusion reactor components and offer insights into viable mechanical design strategies for next-generation nuclear energy systems. Full article

(This article belongs to the Special Issue Advanced Simulations for Nuclear Fusion Energy Systems)

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