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Green Synthesis of Core/Shell Phase Change Materials: Applications in Industry and Energy Sectors
Modeling Retail Buildings Within Renewable Energy Communities: Generation and Implementation of Reference Energy Use Profiles
Introduction to ORC–VCC Systems: A Review
Offshore Wind Power—Seawater Electrolysis—Salt Cavern Hydrogen Storage Coupling System: Potential and Challenges
Unsteady Loading on a Tidal Turbine Due to the Turbulent Wake of an Upstream Turbine Interacting with a Seabed Ridge

Journal Description

Energies

Energies is a peer-reviewed, open access journal of related scientific research, technology development, engineering policy, and management studies related to the general field of energy, from technologies of energy supply, conversion, dispatch, and final use to the physical and chemical processes behind such technologies. Energies is published semimonthly online by MDPI. The European Biomass Industry Association (EUBIA), Association of European Renewable Energy Research Centres (EUREC), Institute of Energy and Fuel Processing Technology (ITPE), International Society for Porous Media (InterPore), CYTED and others are affiliated with Energies and their members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, RePEc, Inspec, CAPlus / SciFinder, and other databases.
Journal Rank: CiteScore - Q1 (Control and Optimization)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.8 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the second half of 2024).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Sections: published in 41 topical sections.
Testimonials: See what our editors and authors say about Energies.
Companion journals for Energies include: Gases, Nanoenergy Advances, Solar, Wind, Energy Storage and Applications and Bioresources and Bioproducts.

Impact Factor: 3.0 (2023); 5-Year Impact Factor: 3.0 (2023)

Imprint Information Journal Flyer Open Access ISSN: 1996-1073

Latest Articles

19 pages, 1365 KiB

Open AccessArticle

An Integrated Building Energy Model in MATLAB

by Marco Simonazzi, Nicola Delmonte, Paolo Cova and Roberto Menozzi

Energies 2025, 18(11), 2948; https://doi.org/10.3390/en18112948 (registering DOI) - 3 Jun 2025

This paper discusses the development of an Integrated Building Energy Model (IBEM) in MATLAB (R2024b) for a university campus building. In the general context of the development of integrated energy district models to guide the evolution and planning of smart energy grids for [...] Read more.

This paper discusses the development of an Integrated Building Energy Model (IBEM) in MATLAB (R2024b) for a university campus building. In the general context of the development of integrated energy district models to guide the evolution and planning of smart energy grids for increased efficiency, resilience, and sustainability, this work describes in detail the development and use of an IBEM for a university campus building featuring a heat pump-based heating/cooling system and PV generation. The IBEM seamlessly integrates thermal and electrical aspects into a complete physical description of the energy performance of a smart building, thus distinguishing itself from co-simulation approaches in which different specialized tools are applied to the two aspects and connected at the level of data exchange. Also, the model, thanks to its physical, white-box nature, can be instanced repeatedly within the comprehensive electrical micro-grid model in which it belongs, with a straightforward change of case-specific parameter settings. The model incorporates a heat pump-based heating/cooling system and photovoltaic generation. The model’s components, including load modeling, heating/cooling system simulation, and heat pump implementation are described in detail. Simulation results illustrate the building’s detailed power consumption and thermal behavior throughout a sample year. Since the building model (along with the whole campus micro-grid model) is implemented in the MATLAB Simulink environment, it is fully portable and exploitable within a large, world-wide user community, including researchers, utility companies, and educational institutions. This aspect is particularly relevant considering that most studies in the literature employ co-simulation environments involving multiple simulation software, which increases the framework’s complexity and presents challenges in models’ synchronization and validation. Full article

(This article belongs to the Special Issue Energy and Buildings: Thermal Storage, Emissions, Transports, Control and Their Effects)

15 pages, 2024 KiB

Open AccessArticle

Continuous-Control-Set Model Predictive Control Strategy for MMC-UPQC Under Non-Ideal Conditions

by Lianghua Chen, Jianping Zhou, Jiayu Zhai, Lisheng Yang, Xudong Qian and Zhiyong Tao

Energies 2025, 18(11), 2946; https://doi.org/10.3390/en18112946 (registering DOI) - 3 Jun 2025

In the MMC-based unified power quality conditioner (MMC-UPQC), the computational burden of finite-control-set model predictive control (FCS-MPC) increases rapidly with the number of MMC submodules. Meanwhile, conventional linear and nonlinear control methods suffer from limited compensation accuracy. To address this, a control strategy [...] Read more.

In the MMC-based unified power quality conditioner (MMC-UPQC), the computational burden of finite-control-set model predictive control (FCS-MPC) increases rapidly with the number of MMC submodules. Meanwhile, conventional linear and nonlinear control methods suffer from limited compensation accuracy. To address this, a control strategy combining continuous-control-set model predictive control (CCS-MPC) and phase-shifted carrier pulse-width modulation (PSC-PWM) is proposed. CCS-MPC performs repeated time-domain optimization based on the system model. It offers advantages such as fast dynamic response and ease of implementation, thereby enhancing both dynamic and steady-state performance, as well as compensation effectiveness. Unlike FCS-MPC, the computational complexity of CCS-MPC combined with PSC-PWM does not depend on the number of submodules, which significantly reduces the overall computational burden. Simulation results verify that the proposed method exhibits superior performance under three scenarios: grid-side voltage unbalance, high-order harmonic injection, and nonlinear load connection. Compared with the linear PI control strategy and the nonlinear passivity-based control strategy, the proposed method significantly enhances power quality and system robustness. Full article

19 pages, 3792 KiB

Open AccessArticle

Experiment and Simulation of the Non-Catalytic Reforming of Biomass Gasification Producer Gas for Syngas Production

by Yongbin Wang, Guoqiang Cao, Zhongren Ba, Hao Cheng, Donghai Hu, Jonas Baltrusaitis, Chunyu Li, Jiantao Zhao and Yitian Fang

Energies 2025, 18(11), 2945; https://doi.org/10.3390/en18112945 (registering DOI) - 3 Jun 2025

Among biomass gasification syngas cleaning methods, non-catalytic reforming emerges as a sustainable and high-efficiency alternative. This study employed integrated experimental analysis and kinetic modeling to examine non-catalytic reforming processes of biomass-derived producer gas utilizing a synthetic tar mixture containing representative model compounds: naphthalene [...] Read more.

Among biomass gasification syngas cleaning methods, non-catalytic reforming emerges as a sustainable and high-efficiency alternative. This study employed integrated experimental analysis and kinetic modeling to examine non-catalytic reforming processes of biomass-derived producer gas utilizing a synthetic tar mixture containing representative model compounds: naphthalene (C₁₀H₈), toluene (C₇H₈), benzene (C₆H₆), and phenol (C₆H₅OH). The experiments were conducted using a high-temperature fixed-bed reactor under varying temperatures (1100–1500 °C) and equivalence ratios (ERs, 0.10–0.30). The results obtained from the experiment, namely the measured mole concentration of H₂, CO, CH₄, CO₂, H₂O, soot, and tar suggested that both reactor temperature and O₂ content had an important effect. Increasing the temperature significantly promotes the formation of H₂ and CO. At 1500 °C and a residence time of 0.01 s, the product gas achieved CO and H₂ concentrations of 28.02% and 34.35%, respectively, while CH₄, tar, and soot were almost entirely converted. Conversely, the addition of O₂ reduces the concentrations of H₂ and CO. Increasing ER from 0.10 to 0.20 could reduce CO from 22.25% to 16.11%, and H₂ from 13.81% to 10.54%, respectively. Experimental results were used to derive a kinetic model to accurately describe the non-catalytic reforming of producer gas. Furthermore, the maximum of the Root Mean Square Error (RMSE) and the Relative Root Mean Square Error (RRMSE) between the model predictions and experimental data are 2.42% and 11.01%, respectively. In particular, according to the kinetic model, the temperature increases predominantly accelerated endothermic reactions, including the Boudouard reaction, water gas reaction, and CH₄ steam reforming, thereby significantly enhancing CO and H₂ production. Simultaneously, O₂ content primarily influenced carbon monoxide oxidation, hydrogen oxidation, and partial carbon oxidation. Full article

(This article belongs to the Special Issue Advanced Clean Coal Technology)

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26 pages, 642 KiB

Open AccessArticle

Unpacking Market Barriers to Energy Efficiency in Emerging Economies: Policy Insights and a Business Model Perspective from Jordan

by Rund Awwad, Scott Dwyer and Andrea Trianni

Energies 2025, 18(11), 2944; https://doi.org/10.3390/en18112944 (registering DOI) - 3 Jun 2025

Energy efficiency (EE) remains an underexploited opportunity in many developing economies, where a complex interplay of policy, institutional, and market-related challenges limit its implementation at scale. This study explores the structural, economic, and policy-related constraints affecting the EE market in Jordan, a country [...] Read more.

Energy efficiency (EE) remains an underexploited opportunity in many developing economies, where a complex interplay of policy, institutional, and market-related challenges limit its implementation at scale. This study explores the structural, economic, and policy-related constraints affecting the EE market in Jordan, a country with a high dependence on imported energy. Using a multi-framework approach, we apply the political, economic, social, technological, environmental, and legal (PESTEL) framework to categorize these barriers, complemented by Brown’s business model (BM) typology to enhance the analytical depth. Primary data were collected through semi-structured interviews with key market actors. The findings highlight issues such as economic volatility, regulatory fragmentation, and the structural biases associated with donor-driven interventions, which contribute to an uneven and loosely regulated market environment in which businesses face significant scaling challenges. This study reflects on international experience to explore how strategies from other contexts might inform markets’ adaptation in emerging economies. This study concludes with targeted policy recommendations aimed at clarifying regulatory pathways and supporting more effective market delivery. This research contributes to ongoing policy discourse by highlighting how context-specific BM innovations might help address systemic barriers, while potentially supporting national energy goals. Full article

(This article belongs to the Section C: Energy Economics and Policy)

15 pages, 1203 KiB

Open AccessArticle

Conversion of a Small-Size Passenger Car to Hydrogen Fueling: Evaluation of Boosting Potential and Peak Performance During Lean Operation

by Adrian Irimescu, Simona Silvia Merola and Bianca Maria Vaglieco

Energies 2025, 18(11), 2943; https://doi.org/10.3390/en18112943 (registering DOI) - 3 Jun 2025

Energy and mobility are currently powered by conventional fuels, and for the specific case of spark ignition (SI) engines, gasoline is dominant. Converting these power-units to hydrogen is an efficient and cost-effective choice for achieving zero-carbon emissions. The use of this alternative fuel [...] Read more.

Energy and mobility are currently powered by conventional fuels, and for the specific case of spark ignition (SI) engines, gasoline is dominant. Converting these power-units to hydrogen is an efficient and cost-effective choice for achieving zero-carbon emissions. The use of this alternative fuel can be combined with a circular-economy approach that gives new life to the existing fleet of engines and minimizes the need for added components. In this context, the current work scrutinizes specific aspects of converting a small-size passenger car to hydrogen fueling. The approach combined measurements performed with gasoline and predictive 0D/1D models for correctly including fuel chemistry effects; the experimental data were used for calibration purposes. One particular aspect of H₂ is that it results in lower volumetric efficiency compared to gasoline, and therefore boosting requirements can feature significant changes. The results of the 0D/1D simulations show that one of the main conclusions is that only stoichiometric operation would ensure the reference peak power level; lean fueling featured relative air–fuel ratios too low for ensuring the minimum value of 2 that would allow mitigating NO_x formation. Top speed could be instead feasible in lean conditions, with the same gearbox, but with an extension of the engine speed operating range to 7000 rpm compared to the 3700 rpm reference point with gasoline. Full article

(This article belongs to the Special Issue Advanced Methods for Hydrogen Production, Storage and Utilization, 2nd Edition)

40 pages, 3546 KiB

Open AccessArticle

Hybrid AI-Based Framework for Renewable Energy Forecasting: One-Stage Decomposition and Sample Entropy Reconstruction with Least-Squares Regression

by Nahed Zemouri, Hatem Mezaache, Zakaria Zemali, Fabio La Foresta, Mario Versaci and Giovanni Angiulli

Energies 2025, 18(11), 2942; https://doi.org/10.3390/en18112942 (registering DOI) - 3 Jun 2025

Accurate renewable energy forecasting is crucial for grid stability and efficient energy management. This study introduces a hybrid model that combines signal decomposition and artificial intelligence to enhance the prediction of solar radiation and wind speed. The framework uses a one-stage decomposition strategy, [...] Read more.

Accurate renewable energy forecasting is crucial for grid stability and efficient energy management. This study introduces a hybrid model that combines signal decomposition and artificial intelligence to enhance the prediction of solar radiation and wind speed. The framework uses a one-stage decomposition strategy, applying variational mode decomposition and an improved empirical mode decomposition method with adaptive noise. This process effectively extracts meaningful components while reducing background noise, improving data quality, and minimizing uncertainty. The complexity of these components is assessed using entropy-based selection to retain only the most relevant features. The refined data are then fed into advanced predictive models, including a bidirectional neural network for capturing long-term dependencies, an extreme learning machine, and a support vector regression model. These models address nonlinear patterns in the historical data. To optimize forecasting accuracy, outputs from all models are combined using a least-squares regression technique that assigns optimal weights to each prediction. The hybrid model was tested on datasets from three geographically diverse locations, encompassing varying weather conditions. Results show a notable improvement in accuracy, achieving a root mean square error as low as 2.18 and a coefficient of determination near 0.999. Compared to traditional methods, forecasting errors were reduced by up to 30%, demonstrating the model’s effectiveness in supporting sustainable and reliable energy systems. Full article

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25 pages, 4793 KiB

Open AccessArticle

Study on the Influence of Temperature Distribution in Thermite Plugging Abandoned Well Technology

by Hao Liu, Jie Zhang, Ruitao Sun, Xiang Li, Jiajun Yao and Jiazheng Zhou

Energies 2025, 18(11), 2941; https://doi.org/10.3390/en18112941 (registering DOI) - 3 Jun 2025

With the intensive development of oil and gas resources leading to a rapid increase in abandoned wells, sealing failures may cause oil and gas leakage and environmental pollution. Systematically investigating the temperature distribution patterns of thermite melting in open-hole abandoned wells under various [...] Read more.

With the intensive development of oil and gas resources leading to a rapid increase in abandoned wells, sealing failures may cause oil and gas leakage and environmental pollution. Systematically investigating the temperature distribution patterns of thermite melting in open-hole abandoned wells under various factors is critical for effective plugging. This study overcomes the limitations of traditional single heat conduction models by integrating thermite reaction kinetics, phase change latent heat, and thermal–fluid–solid multi-field coupling effects, establishing a thermal–fluid–solid coupling model for thermite melting in open-hole abandoned wells. This model provides theoretical guidance for the effectiveness of plugging operations and temperature control during operations. The model was validated through thermite melting experiments: the simulated expansion of the sandstone borehole diameter was 9.8 mm, with a 5.5% error compared to the experimental value of 9.29 mm; and the simulated axial extension at the well bottom was 18.9 mm, with a 4.7% error compared to the experimental value of 17.19 mm, confirming the model’s accuracy. The influence of different lithologies and initial downhole temperatures on the temperature distribution in the open-hole section of abandoned wells under identical conditions was analyzed. The results show that the ultimate melting thicknesses of dolomite, limestone, and granite are 0.0354 m, 0.0350 m, and 0.0234 m, respectively, indicating superior plugging effects in dolomite and limestone. In the initial reaction stage (stage a), the phase change thickness of limestone exceeded that of dolomite by 59.78%, demonstrating better thermite melting and sealing efficacy in limestone. Additionally, model analysis reveals that the initial downhole temperature has a minimal impact on the temperature distribution of thermite melting in open-hole abandoned wells. Full article

(This article belongs to the Section H1: Petroleum Engineering)

30 pages, 3781 KiB

Open AccessArticle

Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers

by Ahmed Chiheb Ammari, Wael Labidi and Rami Al-Hmouz

Energies 2025, 18(11), 2940; https://doi.org/10.3390/en18112940 (registering DOI) - 3 Jun 2025

Green data centers (GDCs) are increasingly deployed worldwide to power digital infrastructure sustainably. These centers integrate renewable energy sources, such as solar and wind, to reduce dependence on grid electricity and lower operational costs. When distributed geographically, GDCs face considerable challenges due to [...] Read more.

Green data centers (GDCs) are increasingly deployed worldwide to power digital infrastructure sustainably. These centers integrate renewable energy sources, such as solar and wind, to reduce dependence on grid electricity and lower operational costs. When distributed geographically, GDCs face considerable challenges due to spatial variations in renewable energy availability, electricity pricing, and bandwidth costs. This paper addresses the joint optimization of operational cost and service quality for delay-sensitive applications scheduled across distributed green data centers (GDDCs). We formulate a multi-objective optimization problem that minimizes total operational costs while reducing the Average Task Loss Probability (ATLP), a key Quality of Service (QoS) metric. To solve this, we propose an Adaptive Firefly-Based Bi-Objective Optimization (AFBO) algorithm that introduces multiple adaptive mechanisms to improve convergence and diversity. The minimum Manhattan distance method is adopted to select a representative knee solution from each algorithm’s Pareto front, determining optimal task service rates and ISP task splits into each time slot. AFBO is evaluated using real-world trace-driven simulations and compared against benchmark multi-objective algorithms, including multi-objective particle swarm optimization (MOPSO), simulated annealing-based bi-objective differential evolution (SBDE), and the baseline Multi-Objective Firefly Algorithm (MOFA). The results show that AFBO achieves up to 64-fold reductions in operational cost and produces an extremely low ATLP value (

1.875 \times 10^{- 7}

) that is nearly two orders of magnitude lower than SBDE and MOFA and several orders better than MOPSO. These findings confirm AFBO’s superior capability to balance energy cost savings and Quality of Service (QoS), outperforming existing methods in both solution quality and convergence speed. Full article

(This article belongs to the Special Issue Studies in Renewable Energy Production and Distribution)

21 pages, 3751 KiB

Open AccessArticle

Performance Characteristics of a Pilot-Scale Electromethanogenic Reactor Treating Brewery Wastewater

by Kyle Bowman, Marcelo Elaiuy, George Fudge, Harvey Rutland, William Gambier, Theo Hembury, Ben Jobling-Purser, Thomas Fudge, Izzet Kale and Godfrey Kyazze

Energies 2025, 18(11), 2939; https://doi.org/10.3390/en18112939 (registering DOI) - 3 Jun 2025

A pilot-scale (4000 L) continuous flow electromethanogenic reactor (EMR), also known as a microbial electrochemical cell coupled with an anaerobic digester (MEC-AD), treating brewery wastewater was designed and installed at Hepworth’s Brewery, UK. This investigation presents a 4-fold increase in size compared to [...] Read more.

A pilot-scale (4000 L) continuous flow electromethanogenic reactor (EMR), also known as a microbial electrochemical cell coupled with an anaerobic digester (MEC-AD), treating brewery wastewater was designed and installed at Hepworth’s Brewery, UK. This investigation presents a 4-fold increase in size compared to the next largest pilot-scale MEC-AD system presented in the literature, providing findings to inform the operation of a 52,000 L MEC-AD system (currently under construction). Housed in a 20 ft shipping container, the pilot system features four 1000 L reaction vessels arranged in series, each with a working volume of 900 L. Each reaction vessel contained 8 electrode modules. The system was tested over varying organic loading rates (OLRs), achieved through systematic reductions in hydraulic retention time (HRT). HRTs between 24 and 1.8 days were investigated to align with commercial viability targets. OLRs were observed from 0.4 to 7.5 kgCOD/m³/d. A maximum stable OLR of 6.75 kgCOD/m³/d at a HRT of 2.3 days was observed while maintaining COD removal of 65 and 88% over the first two vessels. This pilot demonstrated commercially viable performance of an EMR at a brewery, resulting in the purchase of the technology at commercial scale (52,000 L) to form part of a wastewater treatment system. Full article

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

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23 pages, 12649 KiB

Open AccessArticle

Robust Wide-Speed-Range Control of IPMSM with Multi-Axis Coordinated Extended State Observer for Dynamic Performance Enhancement

by Wentao Zhang, Yanchen Zhai, Pengcheng Zhu and Yiwei Liu

Energies 2025, 18(11), 2938; https://doi.org/10.3390/en18112938 (registering DOI) - 3 Jun 2025

Wide-speed regulation control strategies for Interior Permanent Magnet Synchronous Motors (IPMSMs) are widely applied in industrial fields. However, traditional algorithms are prone to being affected by motor parameter mismatches, sensor sampling errors, and other disturbances under complex operating conditions, leading to insufficient robustness. [...] Read more.

Wide-speed regulation control strategies for Interior Permanent Magnet Synchronous Motors (IPMSMs) are widely applied in industrial fields. However, traditional algorithms are prone to being affected by motor parameter mismatches, sensor sampling errors, and other disturbances under complex operating conditions, leading to insufficient robustness. In order to enhance dynamic performance while simultaneously ensuring robustness, we analyzed the limitations of traditional control strategies and, based on this, proposed an improved control framework. A Multi-Axis Coordinated Extended State Observer(MCESO)-based robust control framework was developed for full-speed domain operation, which enhances disturbance rejection capability against parameter uncertainties and abrupt load changes through hierarchical disturbance estimation. Subsequently, the effectiveness and stability of the proposed method were verified through theoretical analysis and simulation studies. Compared with traditional control strategies, this method can effectively observe and compensate for a series of complex issues such as nonlinear disturbances during operation without requiring additional hardware support. Finally, extensive experimental tests were carried out on a 500 W IPMSM dual-motor drive platform. The experimental results demonstrated that, even under harsh operating conditions, the proposed scheme can effectively suppress torque ripple and significantly reduce current harmonics. Full article

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

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26 pages, 9196 KiB

Open AccessArticle

Critical Node Identification for Cyber–Physical Power Distribution Systems Based on Complex Network Theory: A Real Case Study

by Mehdi Doostinia, Davide Falabretti, Giacomo Verticale and Sadegh Bolouki

Energies 2025, 18(11), 2937; https://doi.org/10.3390/en18112937 (registering DOI) - 3 Jun 2025

In today’s world, power distribution systems and information and communication technology (ICT) systems are increasingly interconnected, forming cyber–physical power systems (CPPSs) at the core of smart grids. Ensuring the resilience of these systems is essential for maintaining reliable performance under disasters, failures, or [...] Read more.

In today’s world, power distribution systems and information and communication technology (ICT) systems are increasingly interconnected, forming cyber–physical power systems (CPPSs) at the core of smart grids. Ensuring the resilience of these systems is essential for maintaining reliable performance under disasters, failures, or cyber-attacks. Identifying critical nodes within these interdependent networks is key to preserving system robustness. This paper applies complex network (CN) theory—specifically degree centrality (DC), closeness centrality (CC), and betweenness centrality (BC)—to a real-world distribution grid integrated with an ICT layer in northeastern Italy. Simulations are conducted across three scenarios: a directed power network, an undirected power network, and an undirected ICT network. Each centrality metric generates a ranking of nodes which is validated using node removal performance (NRP) analysis. In the directed power network, in-closeness centrality and out-degree centrality are the most effective in identifying critical nodes, with correlations of 84% and 74% with NRP, respectively. DC and BC perform best in the undirected power network, with correlation values of 67% and 53%, respectively. In the ICT network, BC achieves the highest correlation (64%), followed by CC at 55%. These findings demonstrate the potential of centrality-based methods for identifying critical nodes and support strategies for enhancing CPPS resilience and fault recovery by distribution system operators. Full article

(This article belongs to the Special Issue Optimal Planning, Integration and Control of Smart Microgrid Systems with Renewable Energy: 2nd Edition)

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20 pages, 4061 KiB

Open AccessArticle

A Spatial Analysis of the Wind and Hydrogen Production in the Black Sea Basin

by Alexandra Ionelia Manolache and Florin Onea

Energies 2025, 18(11), 2936; https://doi.org/10.3390/en18112936 (registering DOI) - 3 Jun 2025

The aim of the present work is to assess the wind and hydrogen production capacity of the Black Sea basin from a spatial point of view, by using reanalysis data that covers a 10-year interval (2015–2024). Based on the ERA5 data it was [...] Read more.

The aim of the present work is to assess the wind and hydrogen production capacity of the Black Sea basin from a spatial point of view, by using reanalysis data that covers a 10-year interval (2015–2024). Based on the ERA5 data it was possible to highlight the general distribution of the wind resources at 100 m height, with more consistent resources being noticed in the region of the Azov Sea or in the north-western sector of the Black Sea, where average values of 8.3 m/s are expected. Taking into account that at this moment in the Black Sea area there are no operational offshore wind farms, several generators ranging from 3 to 15 MW were considered for assessment. In this case, from a single turbine, we can expect values in the range of 11.04 GWh (3 MW system) and 89 GWh (15 MW system), respectively. As a next step, the electricity generated from each wind turbine was used to highlight the hydrogen production of several electrolysers systems (or PEMs). The equivalent number of PEMs was identified, and in some cases it was noticed that some devices will not reach their full capacity, while for smaller PEMs a single 10 MW wind turbine could support the operation of almost four modules. Regarding hydrogen output, a maximum of 1560 tons/year can be expected from the PEMs connected to a 15 MW wind turbine. Full article

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

15 pages, 5155 KiB

Open AccessArticle

Surface Charge Accumulation on Basin-Shape Insulator in Various Eco-Friendly Gases with Metal Particle Under AC Voltage

by Xiaohui Duan, Chuanyun Zhu, Qifeng Shang, Zhen Zhang, Kaiyuan Wang and Yu Gao

Energies 2025, 18(11), 2935; https://doi.org/10.3390/en18112935 (registering DOI) - 3 Jun 2025

Surface charge accumulation is considered one of the key factors that lead to unexpected insulator flashover failures in gas-insulated switchgear (GIS). With the existence of metal particles, charge accumulation characteristics on insulator surfaces become intricate in eco-friendly gases under AC voltage. In this [...] Read more.

Surface charge accumulation is considered one of the key factors that lead to unexpected insulator flashover failures in gas-insulated switchgear (GIS). With the existence of metal particles, charge accumulation characteristics on insulator surfaces become intricate in eco-friendly gases under AC voltage. In this study, the surface charge behavior on a down-scaled 252 kV AC GIS basin insulator model with a linear metal particle adhered to the HV electrode on the convex surface in compressed air (80%N₂/20%O₂) and C₄F₇N/CO₂ mixtures was investigated. After applying an AC voltage of 40 kV for 5 min, the charge densities on both surfaces were measured, and the effect of the metal particle and gas parameters was discussed. The results showed that charge spots were induced by metal particles on the insulator surfaces, and the polarities of which varied with the gas atmosphere. A decrease in maximum charge density was detected with an increase in C₄F₇N proportion at 0.1 MPa, and soar of which was observed at 0.5 MPa. With an increase in gas pressure, the maximum charge density increased in both atmospheres. The total quantity of charges showed similar behavior to the charge densities. It is indicated that the high electronegativity of C₄F₇N molecules presents a competing relationship in charge accumulation as the pressure increases. Full article

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21 pages, 2870 KiB

Open AccessArticle

Diagnosis of Power Transformer On-Load Tap Changer Mechanical Faults Based on SABO-Optimized TVFEMD and TCN-GRU Hybrid Network

by Shan Wang, Zhihu Hong, Qingyun Min, Dexu Zou, Yanlin Zhao, Runze Qi and Tong Zhao

Energies 2025, 18(11), 2934; https://doi.org/10.3390/en18112934 (registering DOI) - 3 Jun 2025

Accurate mechanical fault diagnosis of On-Load Tap Changers (OLTCs) remains crucial for power system reliability yet faces challenges from vibration signals’ non-stationary characteristics and limitations of conventional methods. This paper develops a hybrid framework combining metaheuristic-optimized decomposition with hierarchical temporal learning. The methodology [...] Read more.

Accurate mechanical fault diagnosis of On-Load Tap Changers (OLTCs) remains crucial for power system reliability yet faces challenges from vibration signals’ non-stationary characteristics and limitations of conventional methods. This paper develops a hybrid framework combining metaheuristic-optimized decomposition with hierarchical temporal learning. The methodology employs a Subtraction-Average-Based Optimizer (SABO) to adaptively configure Time-Varying Filtered Empirical Mode Decomposition (TVFEMD), effectively resolving mode mixing through optimized parameter selection. The decomposed components undergo dual-stage temporal processing: A Temporal Convolutional Network (TCN) extracts multi-scale dependencies via dilated convolution architecture, followed by Gated Recurrent Unit (GRU) layers capturing dynamic temporal patterns. An experimental platform was established using a KM-type OLTC to acquire vibration signals under typical mechanical faults, subsequently constructing the dataset. Experimental validation demonstrates superior classification accuracy compared to conventional decomposition–classification approaches in distinguishing complex mechanical anomalies, achieving a classification accuracy of 96.38%. The framework achieves significant accuracy improvement over baseline methods while maintaining computational efficiency, validated through comprehensive mechanical fault simulations. This parameter-adaptive methodology demonstrates enhanced stability in signal decomposition and improved temporal feature discernment, proving particularly effective in handling non-stationary vibration signals under real operational conditions. The results establish practical viability for industrial condition monitoring applications through robust feature extraction and reliable fault pattern recognition. Full article

(This article belongs to the Special Issue Fault Diagnosis and Simulations for Power Transformers, Converter Transformers, and High-Frequency Transformers)

24 pages, 5402 KiB

Open AccessReview

Grid-Forming Converter Fault Control Strategy and Its Impact on Relay Protection: Challenges and Adaptability Analysis

by Xiaopeng Li, Jiaqi Yao, Wei Chen, Wenyue Zhou, Zhaowei Zhou, Hao Wang, Zhenchao Jiang, Wei Dai and Zhongqing Wang

Energies 2025, 18(11), 2933; https://doi.org/10.3390/en18112933 (registering DOI) - 3 Jun 2025

As the proportion of new energy generation continues to rise, power systems are confronted with novel challenges. Grid-forming converters, which possess voltage source characteristics and can support the grid, typically employ a VSG control strategy during normal operation to emulate the behavior of [...] Read more.

As the proportion of new energy generation continues to rise, power systems are confronted with novel challenges. Grid-forming converters, which possess voltage source characteristics and can support the grid, typically employ a VSG control strategy during normal operation to emulate the behavior of synchronous generators. This approach enhances frequency response and system stability in modern power systems. This review article systematically examines two typical fault control strategies for grid-forming converters: the switching strategy and the virtual impedance strategy. These different control strategies result in distinct fault response characteristics of the converter. Based on the analysis of fault control strategies for grid-forming converters, this study investigates the impact of the converter’s fault response characteristics on overcurrent protection, pilot protection, distance protection, and differential protection and investigates and prospects corresponding countermeasures. Finally, through simulation modeling, the fault response characteristics under different control strategies and their effects on protection are verified and analyzed. Focusing on grid-forming converters, this paper dissects the influence of their fault control strategies on relay protection, providing strong support for the wide application and promotion of grid-forming converters in new types of power systems. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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17 pages, 5125 KiB

Open AccessArticle

Impacts of Bipolar Impulse Parameters on the PDIV of Random-Wound Inverted-Fed Motor Insulation

by Junsheng Chen and Peng Wang

Energies 2025, 18(11), 2932; https://doi.org/10.3390/en18112932 - 3 Jun 2025

The detection of Partial Discharge Inception Voltage (PDIV) is vital for evaluating the insulation performance of random-wound inverter-fed motor stators. However, existing research on the impact of impulse parameters on PDIV patterns and their underlying mechanisms is limited, leading to inadequate guidelines for [...] Read more.

The detection of Partial Discharge Inception Voltage (PDIV) is vital for evaluating the insulation performance of random-wound inverter-fed motor stators. However, existing research on the impact of impulse parameters on PDIV patterns and their underlying mechanisms is limited, leading to inadequate guidelines for choosing suitable impulse parameters during PDIV tests of stator insulation under impulsive conditions. This lack of understanding significantly affects the precision of the accuracy of insulation test results for inverter-fed motors. To bridge this gap, this study systematically investigated the influence of key impulse parameters, such as pulse width, dead time, and impulse frequency, on the PDIV test outcomes in enameled wire samples (enameled twisted pairs and pig-tail wires) and random-wound inverter-fed motor stators. A differential bipolar repetitive impulse voltage and a sinusoidal voltage were applied to simulate the pulse-width modulation electrical stress typically experienced by these motors. Results reveal a negative correlation between PDIV test results and pulse width, a positive correlation with dead time, and a weak correlation with impulse frequency. Furthermore, the potential fundamental mechanisms are proposed for the influence of impulse voltage parameters on PDIV characteristics by analyzing the electric field distribution and discharge processes within insulating materials when subjected to impulsive voltages. Based on the experimental conclusion, this study proposes targeted recommendations for revising the current IEC testing standards. These improvements are anticipated to refine stator insulation testing methodologies for inverter-fed motors, ultimately contributing to enhanced insulation reliability in such electric motors. Full article

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16 pages, 5358 KiB

Open AccessArticle

Empirical Motion Compensation for Turbulence Intensity Measurement by Floating LiDARs

by Shogo Uchiyama, Teruo Ohsawa, Hiroshi Asou, Mizuki Konagaya, Takeshi Misaki, Ryuzo Araki and Kohei Hamada

Energies 2025, 18(11), 2931; https://doi.org/10.3390/en18112931 - 3 Jun 2025

We propose an empirical motion compensation algorithm for a better turbulence intensity (TI) measurement by Floating LiDAR systems (FLSs) with a newly introduced motion parameter, the significant tilt angle

θ_{α, 1 / 3}

, using four datasets from three different FLSs [...] Read more.

We propose an empirical motion compensation algorithm for a better turbulence intensity (TI) measurement by Floating LiDAR systems (FLSs) with a newly introduced motion parameter, the significant tilt angle

θ_{α, 1 / 3}

, using four datasets from three different FLSs in Japan. The parameter was compared to other environmental parameters; it was confirmed to well represent various types of buoy motion. A sensitivity assessment was conducted for the error of the FLS’s standard deviation of wind speed to the buoy motion. The strong correlation obtained by the assessment suggests that the error of the FLS TI is dominated by the motion and that it is possible to offset the error by applying the relationship back to the measurement. The corrected TI shows good agreement with that of a reference fixed vertical LiDAR (VL). Moreover, the similarity of the relationships for the same type of VL mounted on different buoys implies that the correction may be VL-specific rather than FLS-specific, and, therefore, universal regardless of the FLS type. The successful validation suggests that the correction based on

θ_{α, 1 / 3}

can be applied not only to the future campaign but also to those performed in the past to revitalize numerous existing FLS datasets. Full article

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22 pages, 3017 KiB

Open AccessReview

Review of Hydrogen Storage in Solid-State Materials

by Gelin Chen, Deqing Liang, Zhanxiao Kang, Jintu Fan, Shuanshi Fan and Xuebing Zhou

Energies 2025, 18(11), 2930; https://doi.org/10.3390/en18112930 - 3 Jun 2025

As a kind of clean energy, hydrogen energy has great potential to reduce environmental pollution and provide efficient energy conversion, and the key to its efficient utilization is to develop safe, economical and portable hydrogen storage technology. At present, hydrogen storage technology lags [...] Read more.

As a kind of clean energy, hydrogen energy has great potential to reduce environmental pollution and provide efficient energy conversion, and the key to its efficient utilization is to develop safe, economical and portable hydrogen storage technology. At present, hydrogen storage technology lags behind hydrogen production and use, which is the bottleneck restricting the development of hydrogen energy. In this paper, several current solid-state hydrogen storage methods are reviewed, including hydrate hydrogen storage, alloy hydrogen storage and MOF hydrogen storage. At the hydrogen storage density level, the hydrogen storage capacity of 1K-MOF-5 can reach 4.23 wt% at 77 K and 10 MPa, and remains basically unchanged in 20 isothermal adsorption and desorption experiments. At the level of temperature and pressure of hydrogen storage, the alloy can realize hydrogen storage under ambient conditions. At the economic level, the cost of hydrogen storage in hydrates is only USD 5–8 per kilogram, with almost zero carbon emissions. Through the analysis, it can be seen that the above solid-state hydrogen storage technologies have their own advantages. Although hydrate hydrogen storage is lower than alloy materials and MOF materials in hydrogen storage density, it still has huge potential for utilization space because of its low cost and simple preparation methods. This paper further provides a comprehensive review of the existing challenges in hydrate research and outlines prospective directions for the advancement of hydrogen storage technologies. Full article

(This article belongs to the Special Issue Advances in Hydrogen Energy IV)

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26 pages, 1615 KiB

Open AccessReview

Economic Analysis of Nuclear Energy Cogeneration: A Comprehensive Review on Integrated Utilization

by Guobin Jia, Guifeng Zhu, Yang Zou, Yuwen Ma, Ye Dai, Jianhui Wu and Jian Tian

Energies 2025, 18(11), 2929; https://doi.org/10.3390/en18112929 - 3 Jun 2025

Nuclear energy cogeneration, which integrates electricity generation with thermal energy utilization, presents a transformative pathway for enhancing energy efficiency and decarbonizing industrial and urban sectors. This comprehensive review synthesizes advancements in technological stratification, economic modeling, and sectoral practices to evaluate the viability of [...] Read more.

Nuclear energy cogeneration, which integrates electricity generation with thermal energy utilization, presents a transformative pathway for enhancing energy efficiency and decarbonizing industrial and urban sectors. This comprehensive review synthesizes advancements in technological stratification, economic modeling, and sectoral practices to evaluate the viability of nuclear cogeneration as a cornerstone of low-carbon energy transitions. By categorizing applications based on temperature requirements (low: <250 °C, medium: 250–550 °C, high: >550 °C), the study highlights the adaptability of reactor technologies, including light water reactors (LWRs), high-temperature gas-cooled reactors (HTGRs), and molten salt reactors (MSRs), to sector-specific demands. Key findings reveal that nuclear cogeneration systems achieve thermal efficiencies exceeding 80% in low-temperature applications and reduce CO₂ emissions by 1.5–2.5 million tons annually per reactor by displacing fossil fuel-based heat sources. Economic analyses emphasize the critical role of cost allocation methodologies, with exergy-based approaches reducing levelized costs by 18% in high-temperature applications. Policy instruments, such as carbon pricing, value-added tax (VAT) exemptions, and subsidized loans, enhance project viability, elevating net present values by 25–40% for district heating systems. Case studies from Finland, China, and Canada demonstrate operational successes, including 30% emission reductions in oil sands processing and hydrogen production costs as low as USD 3–5/kg via thermochemical cycles. Hybrid nuclear–renewable systems further stabilize energy supply, reducing the levelized cost of heat by 18%. The review underscores the necessity of integrating Generation IV reactors, thermal storage, and policy alignment to unlock nuclear cogeneration’s full potential in achieving global decarbonization and energy security goals. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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23 pages, 4508 KiB

Open AccessArticle

Investigation of Frequency Response Sharing-Induced Power Oscillations in VSC-HVDC Systems for Asynchronous Interconnection

by Ke Wang, Chunguang Zhou, Yiping Chen, Yan Guo, Zhantao Fan and Zhixuan Li

Energies 2025, 18(11), 2928; https://doi.org/10.3390/en18112928 - 3 Jun 2025

Low-frequency power oscillations (LFPOs) may occur in voltage source converter-based high-voltage direct current (VSC-HVDC) systems when providing frequency support to asynchronously interconnected power grids. This phenomenon has been observed in the LUXI back-to-back (BTB) VSC-HVDC project in China and results from insufficient damping, [...] Read more.

Low-frequency power oscillations (LFPOs) may occur in voltage source converter-based high-voltage direct current (VSC-HVDC) systems when providing frequency support to asynchronously interconnected power grids. This phenomenon has been observed in the LUXI back-to-back (BTB) VSC-HVDC project in China and results from insufficient damping, which may threaten the stability of the overall power system. To better understand and address this problem, this study investigates the root causes of LFPOs and evaluates how different parts of the system affect damping. A combined approach using small-signal modeling and the damping torque method is developed to analyze the damping behavior of DC power in VSC-HVDC systems. Results show that LFPOs are caused by the interaction between VSC-based frequency control and the dynamic response of synchronous generators (SGs). The turbine and governor systems in SGs help stabilize the system by providing positive damping, whereas the DC voltage-controlled VSC station introduces negative damping. The findings are supported by detailed simulations using a modified IEEE 39-bus test system, demonstrating the effectiveness of the proposed analysis method. Full article

(This article belongs to the Special Issue Advanced Electric Power Systems, 2nd Edition)

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