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Energies, Volume 18, Issue 6 (March-2 2025) – 249 articles

Cover Story (view full-size image): Three-dimensional flexible solar fabrics based on hydrogenated amorphous silicon (a-Si:H) thin film solar cells were prepared and characterized. A glass fiber fabric with a polytetrafluoroethylene (PTFE) coating proved to be a suitable textile substrate. Interwoven metal wires enabled an integrated electrical interconnection. The best solar cells showed an efficiency of 3.9%, with an open-circuit voltage of 876 mV and a short-circuit current density of 11.4 mA/cm2. The high series resistance limited the fill factor to 39%. The potential of the textile solar cells was demonstrated by the pseudo fill factor of 79% achieved when neglecting the series resistance, resulting in a pseudo efficiency of 7.6%. When four textile solar cells were connected in a series, an open-circuit voltage of about 3 V was achieved. View this paper
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23 pages, 6185 KiB  
Article
A Method for the Modular Power Flow Analysis of Extensive Distribution Grids
by Daniel-Leon Schultis and Clemens Korner
Energies 2025, 18(6), 1559; https://doi.org/10.3390/en18061559 - 20 Mar 2025
Viewed by 281
Abstract
The widespread deployment of distributed energy resources including volatile renewable generation raises the need for detailed distribution network analysis. In many cases, the vast system sizes make the joint analysis of multiple voltage levels computationally impracticable. Consequently, most studies focus on single or [...] Read more.
The widespread deployment of distributed energy resources including volatile renewable generation raises the need for detailed distribution network analysis. In many cases, the vast system sizes make the joint analysis of multiple voltage levels computationally impracticable. Consequently, most studies focus on single or selected voltage levels and represent subordinate system portions by conventional static load models. Their parameters are usually identified by simplified aggregation methods that do not consider the effects of the network, i.e., network losses and spatial voltage variations. This approach involves inaccuracies and does not allow for validating compliance with the voltage and current limits inside subordinate system parts that are not explicitly represented in the model. In response to this challenge, this paper extends the static load model by including new parameters, i.e., the boundary voltage limits, and describes the associated component-based parameter identification method. Their combination paves the way for a modular power flow approach, which supports the separate investigation of different system portions without introducing considerable inaccuracies, enabling the systematic, precise, and computationally practicable power flow analysis and validation of voltage and current limit compliance in large distribution systems. The proposed concepts are applied to a synthetic distribution system to facilitate their use and showcase their usefulness. Full article
(This article belongs to the Section F1: Electrical Power System)
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21 pages, 3948 KiB  
Article
Numerical Simulation of the Input-Output Behavior of a Geothermal Energy Storage
by Paul Honore Takam and Ralf Wunderlich
Energies 2025, 18(6), 1558; https://doi.org/10.3390/en18061558 - 20 Mar 2025
Viewed by 281
Abstract
This paper studies numerical simulations of the input-output behavior of a geothermal energy storage used in residential heating systems. There, under or aside of a building a certain domain is filled with soil and insulated from the surrounding ground. Thermal energy is stored [...] Read more.
This paper studies numerical simulations of the input-output behavior of a geothermal energy storage used in residential heating systems. There, under or aside of a building a certain domain is filled with soil and insulated from the surrounding ground. Thermal energy is stored by raising the temperature of the soil inside the storage, and pipe heat exchangers filled with a moving fluid are used to charge and discharge the storage. Numerical simulations are required for the design, operation and optimal management of heating systems that are equipped with such a thermal storage system. They help to understand the storage response to charging and discharging processes, which depend crucially on the dynamics of the spatial temperature distribution in the storage medium. The latter is modeled mathematically by an initial boundary value problem for a linear heat equation with convection. The problem is solved numerically by finite difference discretization. Finally, the results of computer simulations are presented, which show the properties of the temperature distribution in the storage and its aggregated characteristics. Full article
(This article belongs to the Special Issue Renewable and Sustainable Energy in Light of Energy Transition Processes)
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21 pages, 5316 KiB  
Article
A Model Predictive Control Strategy with Minimum Model Error Kalman Filter Observer for HMEV-AS
by Ying Zhou, Chenlai Liu, Zhongxing Li and Yi Yu
Energies 2025, 18(6), 1557; https://doi.org/10.3390/en18061557 - 20 Mar 2025
Viewed by 148
Abstract
In hub-motor electric vehicles (HMEVs), performance is adversely affected by the mechanical-electromagnetic coupling effect arising from deformations of the air gap in the Permanent Magnet Brushless Direct Current Motor (PM BLDC), which are exacerbated by varying road conditions. In this paper, a Model [...] Read more.
In hub-motor electric vehicles (HMEVs), performance is adversely affected by the mechanical-electromagnetic coupling effect arising from deformations of the air gap in the Permanent Magnet Brushless Direct Current Motor (PM BLDC), which are exacerbated by varying road conditions. In this paper, a Model Predictive Control (MPC) strategy for HMEVs equipped with air suspension (AS) is introduced to enhance ride comfort. Firstly, an 18-degree of freedom (DOF) full-vehicle model incorporating unbalanced electromagnetic forces (UEMFs) induced by motor eccentricities is developed and experimentally validated. Additionally, a Minimum Model Error Extended Kalman Filter (MME-EKF) observer is designed to estimate unmeasurable state variables and account for errors resulting from sprung mass variations. To further improve vehicle performance, the MPC optimization objective is formulated by considering the suspension damping force and dynamic displacement constraints, solving for the optimal suspension force within a rolling time domain. Simulation results demonstrate that the proposed MPC approach significantly improves ride comfort, effectively mitigates coupling effects in hub driving motors, and ensures that suspension dynamic stroke adheres to safety criteria. Comparative analyses indicate that the MPC controller outperforms conventional PID control, achieving substantial reductions of approximately 41.59% in sprung mass vertical acceleration, 14.29% in motor eccentricity, 1.78% in tire dynamic load, 17.65% in roll angular acceleration, and 16.67% in pitch angular acceleration. Full article
(This article belongs to the Section F: Electrical Engineering)
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28 pages, 3486 KiB  
Article
Thermo-Economic Potential of Carnot Batteries for the Waste Heat Recovery of Liquid-Cooled Data Centers with Different Combinations of Heat Pumps and Organic Rankine Cycles
by Xiaoyu Zhou, Xinxing Lin, Wen Su, Ruochen Ding and Yaran Liang
Energies 2025, 18(6), 1556; https://doi.org/10.3390/en18061556 - 20 Mar 2025
Viewed by 222
Abstract
To fully recover abundant waste heat and reduce the operation cost in liquid-cooled data centers, a Carnot battery consisting of a heat pump (HP) and organic Rankine cycle (ORC) is proposed. Due to the existence of different cycle states for HPs and ORCs, [...] Read more.
To fully recover abundant waste heat and reduce the operation cost in liquid-cooled data centers, a Carnot battery consisting of a heat pump (HP) and organic Rankine cycle (ORC) is proposed. Due to the existence of different cycle states for HPs and ORCs, four different cycle combinations are considered. To evaluate and compare their performances, thermo-economic models are developed. Under the design conditions, the optimal working fluid combinations are first determined for each battery. On this basis, thermodynamic and economic performances of the four batteries are analyzed in detail. The results indicate that the system consisting of a subcritical HP/transcritical ORC achieves the highest round-trip efficiency at 76%. Notably, the round-trip efficiency of the system can exceed 100% at low ORC condensing temperatures. Additionally, the system cost is about 767–796 USD/kW∙h, depending on the cycle combinations. Furthermore, the effects of operating parameters on system performances are also investigated. Finally, with the objective of maximum round-trip efficiency, key parameters of four batteries are optimized. The results reveal that the system with a subcritical HP/subcritical ORC attains a maximum round-trip efficiency of 83% after optimization. These research results contribute to the development of green data centers and the reduction of power costs. Full article
(This article belongs to the Section J: Thermal Management)
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15 pages, 2152 KiB  
Article
A Novel Water-Flooding Characteristic Curve Based on Fractal Theory and Its Application
by Ke Li, Xulin Du, Jing Li, Junzhe Jiang and Shaobin Cai
Energies 2025, 18(6), 1555; https://doi.org/10.3390/en18061555 - 20 Mar 2025
Viewed by 142
Abstract
There are currently numerous types of water-flooding characteristic curves, most of which are derived from fundamental theories such as material balance, relative permeability, along with experimental results. A single exponential or power function expression cannot accurately characterize the complex flow characteristics of different [...] Read more.
There are currently numerous types of water-flooding characteristic curves, most of which are derived from fundamental theories such as material balance, relative permeability, along with experimental results. A single exponential or power function expression cannot accurately characterize the complex flow characteristics of different types of reservoirs, and the equivalent relationships corresponding to production wells and entire oilfields remain unclear. Consequently, practical applications often encounter issues such as curve tailing, difficulty in determining linear segments, inability to identify anomalous points, and inaccuracies in dynamic fitting and prediction. This paper derives a novel water-flooding characteristic curve expression based on fractal theory, incorporating the fractal characteristics of two-phase oil–water flow in reservoirs, as well as the micro-level pore–throat flow features and macro-level dynamic laws of water flooding. The approach is analyzed and validated with real oilfield cases. This study indicates that fitting with the novel water-flooding characteristic curve yields high correlation coefficients and excellent fitting results, demonstrating strong applicability across various types of oilfields and water cut stages. It can more accurately describe the water-flooding characteristics under different reservoir conditions and rapidly predict recoverable reserves, offering significant application value in the dynamic analysis of oilfields and the formulation of development strategies. Full article
(This article belongs to the Section H: Geo-Energy)
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25 pages, 6915 KiB  
Article
Design and Analysis of a Quasi-Biaxial Solar Tracker
by Yakang Liu, Zhiquan Xiao, Yu Huang, Yubo Ma and Zihan Yang
Energies 2025, 18(6), 1554; https://doi.org/10.3390/en18061554 - 20 Mar 2025
Viewed by 239
Abstract
Inspired by C. Alexandru, to achieve a balance between tracking accuracy and equipment cost and between single-axis tracking brackets and dual-axis tracking brackets, a kind of quasi-biaxial solar tracker, whose approximate two-axis motions are driven by a single motor, is studied in this [...] Read more.
Inspired by C. Alexandru, to achieve a balance between tracking accuracy and equipment cost and between single-axis tracking brackets and dual-axis tracking brackets, a kind of quasi-biaxial solar tracker, whose approximate two-axis motions are driven by a single motor, is studied in this paper. Firstly, considering the changes in the total number of sunny days and declination angle in a certain period of time, the characteristic day of the tracker in this period is set. Then, based on the variations in the Sun’s azimuth and elevation angle on the characteristic day, a quasi-biaxial solar tracker mechanism is designed. Its azimuth angle movement is directly driven by a single motor, while the elevation angle movement is driven by the same motor through a bevel gear and a cam mechanism. The solar irradiance of the photovoltaic module of the solar tracker is analyzed using PVsyst software. Through 3D modeling-aided design, a prototype of the solar tracker is built and then relative experiments are conducted to study the performance of the quasi-biaxial solar tracker. Simulation analysis and physical model experiments show that the quasi-biaxial solar tracker works and achieves a relative compromise between tracking accuracy and cost. Full article
(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
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31 pages, 7343 KiB  
Article
Exploration of Training Strategies for a Quantile Regression Deep Neural Network for the Prediction of the Rate of Penetration in a Multi-Lateral Well
by Adrian Ambrus, Felix James Pacis, Sergey Alyaev, Rasool Khosravanian and Tron Golder Kristiansen
Energies 2025, 18(6), 1553; https://doi.org/10.3390/en18061553 - 20 Mar 2025
Viewed by 272
Abstract
In recent years, rate of penetration (ROP) prediction using machine learning has attracted considerable interest. However, few studies have addressed ROP prediction uncertainty and its relation to training data and model inputs. This paper presents the application of a quantile regression deep neural [...] Read more.
In recent years, rate of penetration (ROP) prediction using machine learning has attracted considerable interest. However, few studies have addressed ROP prediction uncertainty and its relation to training data and model inputs. This paper presents the application of a quantile regression deep neural network (QRDNN) for ROP prediction on multi-lateral wells drilled in the Alvheim field of the North Sea. The quantile regression framework allows the characterization of the prediction uncertainty, which can inform the end-user on whether the model predictions are reliable. Three different training strategies for the QRDNN model are investigated. The first strategy uses individual hole sections of the multi-lateral well to train the model, which is then tested on sections of similar hole size. In the second strategy, the models are trained for specific formations encountered in the well, assuming the formation tops are known for both the training and test sections. The third strategy uses training data from offset wells from the same field as the multi-lateral well, exploring different offset–well combinations and input features. The resulting QRDNN models are tested on several complete well sections excluded from the training data, each several kilometers long. The second and third strategies give the lowest mean absolute percentage errors of their median predictions of 27.3% and 28.7% respectively—all without recalibration for the unknown test well sections. Furthermore, the third model based on offset training gives a robust prediction of uncertainty with over 99.6% of actual values within the predicted P10 and P90 percentiles. Full article
(This article belongs to the Special Issue Artificial Intelligence for a Sustainable Oil and Gas Industry and Energy Transition)
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23 pages, 2411 KiB  
Review
Review of Explosion Mechanism and Explosion-Proof Measures for High-Voltage Cable Intermediate Joints
by Wei Qiu, Chen Li, Nianqiao Chen, Yuhua Huang, Zhibin Jiang, Jiangjing Cui, Peifeng Wang and Gang Liu
Energies 2025, 18(6), 1552; https://doi.org/10.3390/en18061552 - 20 Mar 2025
Viewed by 312
Abstract
The intermediate joint of high-voltage cables, as a critical component in the power transmission system, plays a direct role in the stable operation of the entire electrical system. In recent years, frequent explosions of intermediate joints in high-voltage cables have led to significant [...] Read more.
The intermediate joint of high-voltage cables, as a critical component in the power transmission system, plays a direct role in the stable operation of the entire electrical system. In recent years, frequent explosions of intermediate joints in high-voltage cables have led to significant economic losses and safety risks. Therefore, studying the explosion mechanisms and explosion prevention measures of high-voltage cable intermediate joints is particularly important. This article provides a systematic review of the explosion mechanisms and explosion prevention measures for high-voltage cable intermediate joints. It begins by introducing the composition of cable systems and the structural features of the 220 kV prefabricated cable joint. Next, the article elaborates on the spatiotemporal evolution process of cable joint explosions. Typically, a cable joint explosion undergoes several stages: partial discharge, arc breakdown, and insulation material decomposition, which ultimately leads to explosion and ignition. Subsequently, the article reviews each of these dynamic stages in detail. Finally, the article discusses the existing explosion prevention measures and their shortcomings, and proposes future directions for the development of explosion prevention measures. This article can provide a theoretical foundation and technical reference for the research on the explosion mechanisms of high-voltage cable joints, as well as for the development of explosion prevention measures. Full article
(This article belongs to the Special Issue Dielectric Insulation in Medium- and High-Voltage Power Equipment—Degradation and Failure Mechanism, Diagnostics, and Electrical Parameters Improvement: 2nd Edition)
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19 pages, 5785 KiB  
Article
Thermoelectric Energy Harvesting with a Stacked Configuration Using Porous Medium for Marine Applications
by Taeho Choi, Junghwan Lee, Junsu Lee and Tae Young Kim
Energies 2025, 18(6), 1551; https://doi.org/10.3390/en18061551 - 20 Mar 2025
Viewed by 213
Abstract
This study proposes a vertically stacked thermoelectric generator (TEG) design to enhance output power per unit volume. While the proposed TEG achieved improved conversion efficiency, the high inertia of the exhaust gas leads to significant flow maldistribution across the channels, causing uneven thermal [...] Read more.
This study proposes a vertically stacked thermoelectric generator (TEG) design to enhance output power per unit volume. While the proposed TEG achieved improved conversion efficiency, the high inertia of the exhaust gas leads to significant flow maldistribution across the channels, causing uneven thermal conditions on the TEM surfaces and reducing overall efficiency. To enhance waste heat recovery by improving flow uniformity in the exhaust gas channels, a perforated plate with porosity ranging from 0.15 to 0.75 was inserted. A multi-physics numerical model was developed to simulate the thermoelectric energy conversion phenomena, enabling for the accurate evaluation of both module- and system-wise performance. The insertion of the perforated plate with 0.45 porosity provided the most uniform flow distribution with only a 5% flow rate difference between the exhaust gas channels. This resulted in a system-level output power of 167.1 W, which is ~7% higher than the case without the perforated plate, along with electrical efficiency of 91.1% and conversion efficiency of 3.41%. Moreover, enhanced flow uniformity led to an improved volumetric power density of 20.8 kW/m3. When accounting for pumping losses, the perforated plate with 0.6 porosity maximized net output power, demonstrating how optimized flow distribution significantly enhances energy harvesting performance. Full article
(This article belongs to the Section J: Thermal Management)
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16 pages, 4156 KiB  
Article
Flow Management in High-Viscosity Oil–Gas Mixing Systems: A Study of Flow Regimes
by Jiaming Tian, Mao Li and Yueshe Wang
Energies 2025, 18(6), 1550; https://doi.org/10.3390/en18061550 - 20 Mar 2025
Viewed by 230
Abstract
The flow management of the gas–liquid mixture module is crucial for the transmission efficiency of crude oil-and-natural gas-gathering and transportation systems. The concurrent flow of high-viscosity crude oil and natural gas in gas–liquid mixing is investigated numerically by adopting an improved volume of [...] Read more.
The flow management of the gas–liquid mixture module is crucial for the transmission efficiency of crude oil-and-natural gas-gathering and transportation systems. The concurrent flow of high-viscosity crude oil and natural gas in gas–liquid mixing is investigated numerically by adopting an improved volume of fluid (VOF) model programmed with the OpenFOAM v2012 software package. Over a wide range of superficial velocities for the oil, from 0.166 to 5.529 m/s, and natural gas, from 0.138 to 27.645 m/s, a variety of flow regimes of bubble flow, plug flow, slug flow, and annular flow are encountered successively, which are essentially consistent with the Brill and Mandhane flow regime identification criteria. The results show that the oil volume fraction, fluid velocity, and bubble slip velocity together affect the growth of bubbles in the pipeline at a low gas velocity. In the case of slug flow, the phenomenon of liquid film plugging is noticeable, and the flow is very unstable, which should be avoided as much as possible. Nonetheless, it is commended that stable plug flow and annular flow with a high oil transportation efficiency and minimal power consumption are friendly working conditions. Full article
(This article belongs to the Section H: Geo-Energy)
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28 pages, 7342 KiB  
Article
Development of WHED Method to Study Operational Stability of Typical Transitions in a Hydropower Plant and a Pumped Storage Plant
by Xiuli Mao, Guoqing Wen, Yuchuan Wang, Jiaren Hu, Xuetao Gan and Pengju Zhong
Energies 2025, 18(6), 1549; https://doi.org/10.3390/en18061549 - 20 Mar 2025
Viewed by 254
Abstract
This study proposes the water hammer energy difference (WHED) method based on unsteady flow energy and continuity equations, as well as the propagation laws of water hammer in closed pipes, and verifies its accuracy. Additionally, the parameter evolution patterns of typical transient conditions [...] Read more.
This study proposes the water hammer energy difference (WHED) method based on unsteady flow energy and continuity equations, as well as the propagation laws of water hammer in closed pipes, and verifies its accuracy. Additionally, the parameter evolution patterns of typical transient conditions in pumped storage power plants are investigated based on WHED. The application of WHED in the transient processes of hydropower plants (HPs) is validated by experiments, showing a maximum error of about 7% between numerical and experimental results under conditions of initial load increase followed by decrease (HR = 184 m). Additionally, WHED was validated under two critical conditions in pumped storage plants (PSPs): 90% load rejection in generating mode and emergency power-off in pumping mode. In PSPs, the results of WHED are consistent with those obtained using the method of characteristics (MOC), with a maximum fault tolerance rate Δ < 3%. Notably, WHED offers superior time efficiency when analyzing hydraulic transitions in complex pipe networks, as it directly considers boundary conditions at both ends of the pipeline and hydraulic machinery, whereas MOC requires dividing the pipeline into multiple segments with a series of boundary points. Lastly, WHED’s energy parameters are used to describe flow stability from a physics perspective, explaining the causes of pressure fluctuations during transient periods in HPs and PSPs. These findings offer valuable references and guidance for the safe operation of PSPs and HPs. Full article
(This article belongs to the Special Issue Optimization Design and Simulation Analysis of Hydraulic Turbine)
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22 pages, 1835 KiB  
Article
Estimating the CO2 Impacts of Wind Energy in the Transition Towards Carbon-Neutral Energy Systems
by Hannele Holttinen, Tomi J. Lindroos, Antti Lehtilä, Tiina Koljonen, Juha Kiviluoma and Magnus Korpås
Energies 2025, 18(6), 1548; https://doi.org/10.3390/en18061548 - 20 Mar 2025
Viewed by 343
Abstract
In this study, the CO2 reduction benefits of wind energy in the transition towards a carbon-neutral energy system are explored. The marginal benefits of wind energy in replacing CO2 emissions in electricity generation are gradually declining as carbon-emission-reduction targets are fulfilled. [...] Read more.
In this study, the CO2 reduction benefits of wind energy in the transition towards a carbon-neutral energy system are explored. The marginal benefits of wind energy in replacing CO2 emissions in electricity generation are gradually declining as carbon-emission-reduction targets are fulfilled. However, there is still the potential to reduce emissions by replacing fossil fuels in other energy sectors via electrification. Using the Finnish TIMES-VTT energy system model, this study simulates the impacts of different wind energy scenarios between 2030 and 2050, analyzing the effects of adding or removing 5 TWh of wind energy on power generation. Our findings indicate that the reduction benefits of wind energy vary over time, stemming initially from the generation of electricity but they are increasingly being driven by electrification through lowered electricity prices, and fuel switching, like the replacement of bioenergy in heating and fuel production. Between the years 2030 and 2050, an average marginal emission reduction of 180–270 gCO2eq/kWh was seen, rising to 250–320 gCO2eq/kWh if the impact on reduced carbon sinks through wood chip use was taken into account. Issues using marginal, substitution impacts from simulations are discussed; however, no straightforward methods for capturing the cumulative benefits of assets over their lifetime exist. In transitioning towards a net-zero-carbon energy system, other issues like costs, land use, and social aspects will become more relevant than emission substitution. Full article
(This article belongs to the Special Issue Energy and Environmental Economics for a Sustainable Future)
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33 pages, 2848 KiB  
Review
A Review on Phase-Change Materials (PCMs) in Solar-Powered Refrigeration Systems
by Yali Guo, Chufan Liang, Hui Liu, Luyuan Gong, Minle Bao and Shengqiang Shen
Energies 2025, 18(6), 1547; https://doi.org/10.3390/en18061547 - 20 Mar 2025
Cited by 1 | Viewed by 436
Abstract
Over the past few years, the combination of solar power with refrigeration technology has matured, providing a promising solution for sustainable cooling. However, a key challenge remains, namely the inherent intermittency of solar energy. Due to its uneven temporal distribution, it is difficult [...] Read more.
Over the past few years, the combination of solar power with refrigeration technology has matured, providing a promising solution for sustainable cooling. However, a key challenge remains, namely the inherent intermittency of solar energy. Due to its uneven temporal distribution, it is difficult to ensure continuous 24 h operation when relying solely on solar energy. To address this issue, thermal energy storage technology has emerged as a viable solution. This paper presents a comprehensive systematic review of phase-change material (PCM) applications in solar refrigeration systems. It systematically categorizes solar energy conversion methodologies and refrigeration system configurations while elucidating the fundamental operational principles of each solar refrigeration system. A detailed examination of system components is provided, encompassing photovoltaic panels, condensers, evaporators, solar collectors, absorbers, and generators. The analysis further investigates PCM integration strategies with these components, evaluating integration effectiveness and criteria for PCM selection. The critical physical parameters of PCMs are comparatively analyzed, including phase transition temperature, latent heat capacity, specific heat, density, and thermal conductivity. Through conducting a critical analysis of existing studies, this review comprehensively evaluates current research progress within PCM integration techniques, methodological classification frameworks, performance enhancement approaches, and system-level implementation within solar refrigeration systems. The investigation concludes by presenting strategic recommendations for future research priorities based on a comprehensive systematic evaluation of technological challenges and knowledge gaps within the domain. Full article
(This article belongs to the Special Issue Advanced Technology for Solar Thermal Cooling, Heating, and Energy Storage)
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22 pages, 13155 KiB  
Article
Research on Multi-Machine Pre-Synchronization Control and Optimization Based on Parallel Recovery Black Start
by Zhongping Ruan, Shuye Ding and Yizhi Chen
Energies 2025, 18(6), 1546; https://doi.org/10.3390/en18061546 - 20 Mar 2025
Viewed by 288
Abstract
With the increasing prevalence of renewable energy, microgrids play a crucial role in enhancing distributed energy efficiency and system flexibility. However, the intermittent and unpredictable nature of renewable energy generation presents significant challenges for microgrid restoration and stable operation. Black-start technology, a key [...] Read more.
With the increasing prevalence of renewable energy, microgrids play a crucial role in enhancing distributed energy efficiency and system flexibility. However, the intermittent and unpredictable nature of renewable energy generation presents significant challenges for microgrid restoration and stable operation. Black-start technology, a key method for autonomous power restoration, is essential for ensuring reliable microgrid operation. Grid-forming virtual synchronous generators (VSGs), with inherent inertia support and regulation capabilities, autonomously establish the voltage, meeting the power supply demands of black-start processes. However, during the pre-synchronization of multiple distributed energy resources in black-start scenarios, rapid phase-angle adjustments can cause frequency fluctuations due to the coupling between the frequency and phase angle. This coupling often leads to frequency overshoot and decreased system stability. To address this challenge, this paper proposes an enhanced parallel restoration strategy for a multi-source black start. Optimizing phase-angle control reduces the dependency on phase-locked loops (PLLs), mitigates phase-angle difference jumps, and accelerates the pre-synchronization process. Furthermore, a linear active disturbance rejection controller (LADRC) dynamically compensates for frequency fluctuations, effectively decoupling the frequency from the phase angle. This approach improves synchronization accuracy and enhances parallel reliability among multiple distributed energy resources (DERs). Simulation results show that the proposed method suppresses frequency overshoot and system disturbances during a multi-source black start, significantly enhancing microgrid restoration capability and operational stability. Full article
(This article belongs to the Special Issue Advances and Optimization of Electric Energy System—2nd Edition)
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18 pages, 3285 KiB  
Article
Assessing the Sustainability of Electric and Hybrid Buses: A Life Cycle Assessment Approach to Energy Consumption in Usage
by Xiao Li, Balázs Horváth and Ágoston Winkler
Energies 2025, 18(6), 1545; https://doi.org/10.3390/en18061545 - 20 Mar 2025
Viewed by 305
Abstract
The global adoption of battery electric vehicles (EVs) and hybrid electric vehicles (HEVs) as a substitute for internal combustion engine cars (ICEs) in various nations offers a substantial opportunity to reduce carbon dioxide (CO2) emissions from land transportation. EVs are fitted [...] Read more.
The global adoption of battery electric vehicles (EVs) and hybrid electric vehicles (HEVs) as a substitute for internal combustion engine cars (ICEs) in various nations offers a substantial opportunity to reduce carbon dioxide (CO2) emissions from land transportation. EVs are fitted with an energy conversion system that efficiently converts stored energy into propulsion, referred to as “tank-to-wheel (TTW) conversion”. Battery-electric vehicles have a significant advantage in that their exhaust system does not produce any pollutants. This hypothesis is equally relevant to public transport. Despite their higher upfront cost, electric buses contribute significantly to environmental sustainability during their operation. This study aimed to evaluate the environmental sustainability of electric buses during their operational phase by utilizing the life cycle assessment (LCA) technique. This paper used the MATLAB R2021b code to ascertain the mean load of the buses during their operation. The energy consumption of battery electric and hybrid electric buses was evaluated using the WLTP Class 2 standard, which refers to vehicles with a power-to-mass ratio between 22 and 34 W/kg, overing four speed phases (low, medium, high, extra high) with speeds up to 131.3 km/h. The code was used to calculate the energy consumption levels for the complete test cycle. The code adopts an idealized rectangular blind box model, disregarding the intricate design of contemporary buses to streamline the computational procedure. Simulating realistic test periods of 1800 s resulted in an average consumption of 1.451 kWh per km for electric buses and an average of 25.3 L per 100 km for hybrid buses. Finally, through an examination of the structure of the Hungarian power system utilization, it was demonstrated that electrification is a more appropriate method for achieving the emission reduction goals during the utilization phase. Full article
(This article belongs to the Section E: Electric Vehicles)
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21 pages, 4097 KiB  
Article
Regionalization of the Location-Dependent Charging Demand of Electric Passenger Cars at the Grid Square Level Using an Agent-Based Mobility Simulation
by Nelly-Lee Fischer, Luka Eschmann and Krzysztof Rudion
Energies 2025, 18(6), 1544; https://doi.org/10.3390/en18061544 - 20 Mar 2025
Viewed by 194
Abstract
The charging demand of electric passenger cars needs to be considered during the planning and operation of the electric power grid, especially at high penetration rates. It is not sufficient to simply quantify these additional loads, but rather time- and location-dependent modeling of [...] Read more.
The charging demand of electric passenger cars needs to be considered during the planning and operation of the electric power grid, especially at high penetration rates. It is not sufficient to simply quantify these additional loads, but rather time- and location-dependent modeling of these loads is required, so that grid operators can precisely predict the magnitude and location of the additional load. For this purpose, an agent-based modeling approach was developed that calculates, locates, and aggregates the charging demand of electric passenger cars per 100 m by 100 m grid squares in an observed area. The mobility of individual vehicles is simulated by efficiently finding destinations in the form of grid squares for generated trips using a k-d tree and parking space data. In a case study, the developed approach is applied to regionalize the charging demand of electric passenger cars at the transmission grid level within the federal state of Baden-Wuerttemberg, Germany. The resulting charging demand can be determined for each individual node of the transmission grid. The analysis shows that the developed approach can be used to quantify regional differences in charging demand and can therefore be used to improve grid planning and operation. Full article
(This article belongs to the Section E: Electric Vehicles)
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23 pages, 1091 KiB  
Review
Cryogenics in Renewable Energy Storage: A Review of Technologies
by Arian Semedo, João Garcia and Moisés Brito
Energies 2025, 18(6), 1543; https://doi.org/10.3390/en18061543 - 20 Mar 2025
Viewed by 429
Abstract
The increase in the exploration of renewable energy sources intensifies the need for efficient storage solutions to mitigate the inherent intermittence of these sources. Among the available technologies, cryogenic energy storage (CES) systems stand out as a major and promising technology due to [...] Read more.
The increase in the exploration of renewable energy sources intensifies the need for efficient storage solutions to mitigate the inherent intermittence of these sources. Among the available technologies, cryogenic energy storage (CES) systems stand out as a major and promising technology due to their high scalability, energy efficiency, and potential for integration with other systems. This paper deals with cryogenic approaches, focused on Liquid Air Energy Storage (LAES). Several topics are addressed, including the characterization of the CES systems, their working principle, with special relevance to efficiency and temperature/entropy diagram, the conception and the technical challenges, design, and construction of CES. LAES demonstrates energy efficiencies ranging from 45% to 70%, potentially reaching up to 75% with the integration of complementary technologies, with capital costs ranging from 900 EUR/kW to 1750/EUR/kW. Carbon dioxide (CO2)-based systems, while more energy-efficient (40% to 60%), face significant barriers due to high infrastructure costs. Additionally, hybrid configurations that combine advanced thermal cycles and waste heat management achieve efficiencies between 55% and 80%, showing adaptability in complex energy scenarios. In comparison with alternatives such as batteries and Compressed Air Energy Storage (CAES), despite economic and technological limitations, CES systems have a promising role in the global energy transition, particularly with anticipated advancements that will enhance their competitiveness and economic viability. Full article
(This article belongs to the Section D: Energy Storage and Application)
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22 pages, 11583 KiB  
Article
Optimizing Ventilation Strategies for Thermal Comfort in Mediterranean Schools: A Dynamic Modeling Approach
by Paolo Maria Congedo, Andrea Palmieri and Cristina Baglivo
Energies 2025, 18(6), 1542; https://doi.org/10.3390/en18061542 - 20 Mar 2025
Viewed by 220
Abstract
Schools, key symbols of progress and innovation, require particular attention regarding energy efficiency, which is considered a strategic priority in sustainable development policies. Improving energy efficiency in schools reduces costs and environmental impact while educating students and the community about sustainability. Ensuring good [...] Read more.
Schools, key symbols of progress and innovation, require particular attention regarding energy efficiency, which is considered a strategic priority in sustainable development policies. Improving energy efficiency in schools reduces costs and environmental impact while educating students and the community about sustainability. Ensuring good air quality and thermal comfort is also crucial for student well-being and performance, resulting in improved productivity, health, and concentration. This study shows that proper ventilation in schools can maintain thermal comfort by exploiting the heat loads generated by the environment and equipment. Yearly and hourly analyses were conducted in terms of internal operative temperature on a simplified school prototype located in a Mediterranean city following the UNI EN ISO 52016 standard. Thermal comfort was evaluated in accordance with the UNI EN 16798-1 standard and tested for different air exchange rates. The results showed that the heating system would typically operate for about 1000 h per year, excluding holiday periods when teaching activities are suspended. With the implementation of a suitable ventilation system, however, the need for a heating system could be removed. Full article
(This article belongs to the Section G: Energy and Buildings)
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20 pages, 3585 KiB  
Article
Optimization of Renewable-Based Multi-Energy Systems in Residential Building Design
by Vasileios Kilis, Georgios Anastasiadis, Nikolaos Ploskas and Giorgos Panaras
Energies 2025, 18(6), 1541; https://doi.org/10.3390/en18061541 - 20 Mar 2025
Viewed by 371
Abstract
Electrification is a key priority of the European Union, focusing on saving energy resources and mitigating carbon emissions through enhancing restrictions on relative policies and initiatives. For such goals to be achieved, investing in renewable energy technologies on large- and small-scale projects is [...] Read more.
Electrification is a key priority of the European Union, focusing on saving energy resources and mitigating carbon emissions through enhancing restrictions on relative policies and initiatives. For such goals to be achieved, investing in renewable energy technologies on large- and small-scale projects is promoted. These efforts were implemented in the building sector too, highlighting the importance of optimal decisions in improving the energy performance of buildings, from an economic, energy and environmental perspective. In this context, this paper aims to elaborate a decision-making methodology for building thermal design, considering the optimal selection and operation of multi-energy systems focused on renewable technologies. Solar thermal collectors, photovoltaic systems and heat pumps were included in an Energy Hub for meeting the heating, cooling and domestic hot water energy demand. Optimal decisions were achieved by formulating Mathematical Programming models in GAMS, for minimizing economic, energy and environmental parameters of the systems under a life cycle perspective. The proposed methodology was implemented in a residential building case study. Results show that combining heat pumps with photovoltaics is preferable for all of the examined criteria, while a sensitivity analysis of the economic, energy and environmental parameters, influencing the energy mixture, leads to optimal solutions with the participation of different energy systems. Full article
(This article belongs to the Special Issue Optimizing Energy Efficiency and Thermal Comfort in Building)
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21 pages, 6449 KiB  
Article
An Evaluation of the Power System Stability for a Hybrid Power Plant Using Wind Speed and Cloud Distribution Forecasts
by Théodore Desiré Tchokomani Moukam, Akira Sugawara, Yuancheng Li and Yakubu Bello
Energies 2025, 18(6), 1540; https://doi.org/10.3390/en18061540 - 20 Mar 2025
Viewed by 454
Abstract
Power system stability (PSS) refers to the capacity of an electrical system to maintain a consistent equilibrium between the generation and consumption of electric power. In this paper, the PSS is evaluated for a “hybrid power plant” (HPP) which combines thermal, wind, solar [...] Read more.
Power system stability (PSS) refers to the capacity of an electrical system to maintain a consistent equilibrium between the generation and consumption of electric power. In this paper, the PSS is evaluated for a “hybrid power plant” (HPP) which combines thermal, wind, solar photovoltaic (PV), and hydropower generation in Niigata City. A new method for estimating its PV power generation is also introduced based on NHK (the Japan Broadcasting Corporation)’s cloud distribution forecasts (CDFs) and land ratio settings. Our objective is to achieve frequency stability (FS) while reducing CO2 emissions in the power generation sector. So, the PSS is evaluated according to the results in terms of the FS variable. Six-minute autoregressive wind speed prediction (6ARW) support is used for wind power (WP). One-hour GPV wind farm (1HWF) power is computed from the Grid Point Value (GPV) wind speed prediction data. The PV power is predicted using autoregressive modelling and the CDFs. In accordance with the daily power curve and the prediction time, we can support thermal power generation planning. Actual data on wind and solar are measured every 10 min and 1 min, respectively, and the hydropower is controlled. The simulation results for the electricity frequency fluctuations are within ±0.2 Hz of the requirements of Tohoku Electric Power Network Co,. Inc. for testing and evaluation days. Therefore, the proposed system supplies electricity optimally and stably while contributing to reductions in CO2 emissions. Full article
(This article belongs to the Section F1: Electrical Power System)
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20 pages, 10647 KiB  
Article
Speed Estimation Method of Active Magnetic Bearings Magnetic Levitation Motor Based on Adaptive Sliding Mode Observer
by Lei Gong, Yu Li, Wenjuan Luo, Jingwen Chen, Zhiguang Hua and Dali Dai
Energies 2025, 18(6), 1539; https://doi.org/10.3390/en18061539 - 20 Mar 2025
Viewed by 234
Abstract
The installation distance between the speed sensor of the traditional rolling or sliding bearing permanent magnet synchronous motor and the rotor was very close, and the rotor of the magnetic levitation motor supported by Active Magnetic Bearings (AMBs) was in suspension. When the [...] Read more.
The installation distance between the speed sensor of the traditional rolling or sliding bearing permanent magnet synchronous motor and the rotor was very close, and the rotor of the magnetic levitation motor supported by Active Magnetic Bearings (AMBs) was in suspension. When the motor was running at high speed, the radial trajectory of the rotor changed all the time. The same frequency vibration caused by the unbalanced mass of the rotor made it easy to cause mechanical collision between the sensor and the rotor, resulting in direct damage of the sensor. Therefore, the sensorless speed estimation method was needed for the rotor control system of the magnetic levitation motor (MLM) to achieve high performance closed-loop control of speed and position. More importantly, in order to control or compensate the unbalanced force of the electromagnetic bearing rotor system, the rotor rotation speed signal should be obtained as accurately as possible. Therefore, the principle of adaptive sliding mode observer (SMO) was analyzed in detail by taking the rotor system of MLM as an example. Then, the sliding mode surface was designed, the speed estimation algorithm based on adaptive SMO was derived, and the stability analysis was completed. Finally, in order to verify the anti-disturbance performance of the system and the static and dynamic tracking performance of the motor, the dynamic performance was verified by increasing and decreasing the speed and load. The results showed that the speed estimation method based on adaptive SMO could achieve accurate speed estimation and had good static and dynamic performance. Full article
(This article belongs to the Section F3: Power Electronics)
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20 pages, 2038 KiB  
Article
Assessment of the Risks Associated with the Handling and Transportation of Air Shipments Containing Lithium-Ion Batteries
by Anna Kwasiborska and Sylwia Ścigaj
Energies 2025, 18(6), 1538; https://doi.org/10.3390/en18061538 - 20 Mar 2025
Viewed by 272
Abstract
Air transport, in addition to passenger transport, also transports air shipments containing hazardous materials. Hazardous materials include lithium-ion batteries, which can be carried both by passengers and by cargo aircraft. Due to the dynamic development of lithium-ion power supply technology, many devices are [...] Read more.
Air transport, in addition to passenger transport, also transports air shipments containing hazardous materials. Hazardous materials include lithium-ion batteries, which can be carried both by passengers and by cargo aircraft. Due to the dynamic development of lithium-ion power supply technology, many devices are equipped with batteries that threaten air traffic safety. The article presents the results of research based on FAA reports of incidents involving lithium-ion batteries. The article aims to present a risk assessment for transporting lithium-ion batteries. Due to the emergence of new devices containing batteries, it is essential to analyze their transport to minimize threats and eliminate aviation incidents. The observations and the analysis of FAA reports showed possible threats from the transport of lithium-ion batteries on board aircraft. The matrix method used indicated the level of risk of transporting lithium-ion batteries. The risk assessment showed the need to monitor or implement corrective actions while transporting flight-ion batteries. Possible solutions were also presented to increase the safety level of transporting lithium-ion batteries. Full article
(This article belongs to the Section D: Energy Storage and Application)
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17 pages, 15320 KiB  
Article
A New Customized Measurement System for a Non-Contact, Enhanced Thermometric Method
by Luca Evangelisti, Edoardo De Cristo, Salvatore Monteleone, Claudia Guattari, Paola Gori, Ivan Pini, Tullio de Rubeis and Dario Ambrosini
Energies 2025, 18(6), 1537; https://doi.org/10.3390/en18061537 - 20 Mar 2025
Viewed by 189
Abstract
This study introduces a novel, low-cost, non-contact measurement system for heat flux estimation based on an enhanced thermometric method. The customized system was designed and assembled to implement a non-contact, indirect approach for heat flux assessment. Developed as an affordable alternative to conventional [...] Read more.
This study introduces a novel, low-cost, non-contact measurement system for heat flux estimation based on an enhanced thermometric method. The customized system was designed and assembled to implement a non-contact, indirect approach for heat flux assessment. Developed as an affordable alternative to conventional contact-based techniques, it is suitable for historical buildings, where invasive sensors could compromise structural integrity. The system integrates real-time data acquisition, remote access via a web-based interface, and automated data processing, enhancing both usability and efficiency. Laboratory tests were conducted to evaluate its performance, with results compared against data from widely used heat flow plates and air/surface temperature sensors. The results showed good agreement between the proposed method and the reference data. Small differences were observed between the values measured by the air temperature sensors (0.10 °C on average), as well as by the contact and non-contact surface temperature sensors (0.12 °C on average). Finally, percentage variations between −6% and −5% in terms of heat fluxes confirmed the reliability of the non-contact approach. These findings provide a strong foundation for further testing, including applications in real buildings. Full article
(This article belongs to the Section G: Energy and Buildings)
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23 pages, 5349 KiB  
Article
Power Grid Primary Frequency Control Strategy Based on Fuzzy Adaptive and State-of-Charge Self-Recovery of Flywheel–Battery Hybrid Energy Storage System
by Shaobo Wen, Yipeng Gong, Zhendong Zhao, Xiufeng Mu and Sufang Zhao
Energies 2025, 18(6), 1536; https://doi.org/10.3390/en18061536 - 20 Mar 2025
Viewed by 304
Abstract
The integration of new renewable energy sources, such as wind and solar power, is characterized by strong randomness and volatility, which increases the risk of power grid system frequency fluctuations exceeding limits. Traditional thermal power units are unable to frequently respond to frequency [...] Read more.
The integration of new renewable energy sources, such as wind and solar power, is characterized by strong randomness and volatility, which increases the risk of power grid system frequency fluctuations exceeding limits. Traditional thermal power units are unable to frequently respond to frequency regulation signals, necessitating the incorporation of energy storage technologies for primary frequency control. This paper presents a primary frequency control strategy for a flywheel–battery hybrid energy storage system (HESS) based on fuzzy adaptation and state-of-charge (SOC) self-recovery. First, a frequency response system model for primary frequency regulation in flywheel–battery hybrid energy storage was formulated. The frequency regulation command is divided into high-frequency and low-frequency components, which are allocated to the flywheel and the battery, respectively. Fuzzy control and regression functions were employed to adjust and constrain the frequency deviation, frequency deviation rate, and SOC. Subsequently, considering the SOC and frequency deviation of each energy storage component, a SOC self-recovery strategy was proposed. Finally, a simulation analysis was performed using a system benchmark capacity of 600 MW. Under step load disturbance conditions, the proposed strategy reduces the maximum frequency deviation by 10.52% and the steady-state frequency deviation by 8.35% compared with traditional methods. Under random load disturbance conditions, the root mean square (RMS) value of frequency deviation is reduced by 7.34%, and the peak-to-valley difference of frequency decreases by 6.74%. Compared to energy storage without SOC self-recovery, the RMS values of SOC for flywheel storage and battery storage are reduced by 8.79% and 16.68%, respectively. The results demonstrate that the proposed control strategy effectively improves the system’s frequency regulation performance, reduces energy storage output fluctuations, and enhances the SOC self-recovery effect of the HESS. Full article
(This article belongs to the Collection Advanced Control and Applications of Power Electronics and Power Converters)
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21 pages, 8615 KiB  
Article
Advanced Deep Learning Based Predictive Maintenance of DC Microgrids: Correlative Analysis
by M. Y. Arafat, M. J. Hossain and Li Li
Energies 2025, 18(6), 1535; https://doi.org/10.3390/en18061535 - 20 Mar 2025
Viewed by 292
Abstract
This paper presents advanced frameworks for microgrid predictive maintenance by performing a comprehensive correlative analysis of advanced recurrent neural network (RNN) architectures, i.e., RNNs, Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRUs) for photovoltaic (PV) based DC microgrids (MGs). Key contributions of [...] Read more.
This paper presents advanced frameworks for microgrid predictive maintenance by performing a comprehensive correlative analysis of advanced recurrent neural network (RNN) architectures, i.e., RNNs, Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRUs) for photovoltaic (PV) based DC microgrids (MGs). Key contributions of this analysis are development of advanced architectures based on RNN, GRU and LSTM, their correlative performance analysis, and integrating adaptive threshold technique with the algorithms to detect faulty operations of inverters which is indispensable for ensuring the reliability and sustainability of distributed energy resources (DERs) in modern MG systems. The proposed models are trained and evaluated with a dataset of diverse real-world operational scenarios and environmental conditions. Moreover, the performances of those advanced models have been compared with the conventional RNN-based techniques. The achieved decremental MAE scores from 12.102 (advanced RNN) to 10.182 (advanced GRU) to 8.263 (advanced LSTM) and incremental R2 scores from 0.941 (advanced RNN) to 0.958 (advanced GRU), and finally to 0.971 (advanced LSTM) demonstrate strong predictive capabilities of all, while the proposed advanced LSTM method outperforming other counterparts. This study can contribute to the emerging technology for predictive maintenance of MGs and provide significant insights into the modeling and performance of RNN architectures for improving fault detection in MG systems. The findings can have noteworthy implications to enhance the efficiency and resilience in MG systems, thereby evolving the renewable energy technologies in power sector and contributing to the sustainable and greener energy landscape. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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14 pages, 5823 KiB  
Article
Research on Diagnostic Methods for Zero-Value Insulators in 110 kV Transmission Lines Based on Spatial Distribution Characteristics of Electric Fields
by Lei Zheng, Pengxiang Yin, Jian Li, Hui Liu, Tao Li and Hao Luo
Energies 2025, 18(6), 1534; https://doi.org/10.3390/en18061534 - 20 Mar 2025
Viewed by 194
Abstract
Porcelain insulators in power systems are subject to prolonged mechanical and electrical loads, as well as environmental factors such as climate variations. These conditions often lead to degradation of insulation performance and structural damage, resulting in a decrease in insulation resistance and the [...] Read more.
Porcelain insulators in power systems are subject to prolonged mechanical and electrical loads, as well as environmental factors such as climate variations. These conditions often lead to degradation of insulation performance and structural damage, resulting in a decrease in insulation resistance and the formation of cracks, which in turn produce “zero-value” insulators. The presence of zero-value insulators significantly increases the risk of pollution flashovers and electrical arcing, with flashover occurrences possible even under normal operating voltages. This poses a severe threat to the safe and stable operation of the power grid. This study develops a high-fidelity simulation model of insulator strings containing zero-value defects for a 110 kV transmission line. The impact of variations in the position and quantity of zero-value insulators on the spatial electric field distribution is analyzed in detail. Based on the electric field changes, a detection method for zero-value insulators is proposed. Additionally, a prediction model for the electric field strength of insulators with zero-value defects is developed using a Multilayer Perceptron (MLP) neural network. A spatial electric field distribution database for insulator strings containing zero-value defects is also established. The accuracy of the model is validated through laboratory testing. 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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12 pages, 3213 KiB  
Article
Three-Dimensionally Printed Metal-Coated Flow-Field Plate for Lightweight Polymer Electrolyte Membrane Fuel Cells
by Dasol Kim, Geonhwi Kim, Juho Na, Hyeok Kim, Jaeyeon Kim, Guyoung Cho and Taehyun Park
Energies 2025, 18(6), 1533; https://doi.org/10.3390/en18061533 - 20 Mar 2025
Viewed by 272
Abstract
This study investigates the potential for affordable and lightweight polymer electrolyte membrane fuel cells (PEMFCs) using lightweight flow-field plates, also referred to as bipolar plates. A comparative analysis was conducted on the performance of metal-coated and uncoated three-dimensional (3D)-printed flow-field plates, as well [...] Read more.
This study investigates the potential for affordable and lightweight polymer electrolyte membrane fuel cells (PEMFCs) using lightweight flow-field plates, also referred to as bipolar plates. A comparative analysis was conducted on the performance of metal-coated and uncoated three-dimensional (3D)-printed flow-field plates, as well as that of a conventional graphite flow-field plate. The fabrication of these lightweight flow-field plates involved the application of sputtering and 3D printing technologies. The polarization curves and corresponding electrochemical impedance spectra of PEMFCs with metal-coated 3D-printed, uncoated 3D-printed, and graphite flow-field plates were measured. The results demonstrate that the metal-coated 3D-printed flow-field plate exhibits a gravimetric power density of 5.21 mW/g, while the graphite flow-field plate registers a value of 2.78 mW/g, representing an 87.4% improvement in gravimetric power density for the metal-coated 3D-printed flow-field plate compared to the graphite flow-field plate. These findings suggest the feasibility of reducing the weight of PEMFCs using metal-coated 3D-printed flow-field plates. Full article
(This article belongs to the Special Issue Sustainable Development of Fuel Cells and Hydrogen Technologies)
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20 pages, 4542 KiB  
Article
Spatial Evolution and Scenario Simulation of Carbon Metabolism in Coal-Resource-Based Cities Towards Carbon Neutrality: A Case Study of Jincheng, China
by Li Zhu, Mengying Cao, Wenyuan Wang and Tianyue Zhang
Energies 2025, 18(6), 1532; https://doi.org/10.3390/en18061532 - 20 Mar 2025
Viewed by 237
Abstract
As important energy suppliers in China, coal-resource-based cities are pivotal to achieving the nation’s 2060 carbon-neutrality goal. This study focused on Jincheng City, utilizing the LOW EMISSIONS ANALYSIS PLATFORM (LEAP) model to predict carbon emissions from energy consumption under various scenarios from 2020 [...] Read more.
As important energy suppliers in China, coal-resource-based cities are pivotal to achieving the nation’s 2060 carbon-neutrality goal. This study focused on Jincheng City, utilizing the LOW EMISSIONS ANALYSIS PLATFORM (LEAP) model to predict carbon emissions from energy consumption under various scenarios from 2020 to 2060. Then, combined with the Markov-PLUS model to map carbon emissions to land-use types, it evaluated spatial changes in carbon metabolism and analyzed carbon-transfer patterns across different land-use types. The results showed the following: (1) Across all scenarios, Jincheng’s carbon emissions exhibited an initial increase followed by a decline, with the industrial sector accounting for over 70% of total emissions. While the baseline scenario deviated from China’s carbon peaking target, the high-limit scenario achieved an early carbon peak by 2027. (2) High-negative-carbon-metabolism areas were concentrated in central urban zones and industrial parks. Notably, arable land shifted from a carbon-sink area to a carbon source area by 2060 in both the low- and high-limit scenarios. (3) In the baseline scenario, industrial and transportation land uses were the primary barriers to carbon metabolism balance. In the low-carbon scenario, the focus shifted from industrial and transportation emissions to urban construction land emissions. In the high-limit scenario, changes in urban–rural land-use relationships significantly influenced carbon metabolism balance. This study emphasizes the importance of industrial green transformation and land-use planning control to achieve carbon neutrality, and it further explores the significant impact of territorial spatial planning on the low-carbon transition of coal-resource-based cities. Full article
(This article belongs to the Section C: Energy Economics and Policy)
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17 pages, 709 KiB  
Article
A Multi-Task Spatiotemporal Graph Neural Network for Transient Stability and State Prediction in Power Systems
by Shuaibo Wang, Xinyuan Xiang, Jie Zhang, Zhuohang Liang, Shufang Li, Peilin Zhong, Jie Zeng and Chenguang Wang
Energies 2025, 18(6), 1531; https://doi.org/10.3390/en18061531 - 20 Mar 2025
Viewed by 297
Abstract
Transient stability assessments and state prediction are critical tasks for power system security. The increasing integration of renewable energy sources has introduced significant uncertainties into these tasks. While AI has shown great potential, most existing AI-based approaches focus on single tasks, such as [...] Read more.
Transient stability assessments and state prediction are critical tasks for power system security. The increasing integration of renewable energy sources has introduced significant uncertainties into these tasks. While AI has shown great potential, most existing AI-based approaches focus on single tasks, such as either stability assessments or state prediction, limiting their practical applicability. In power system operations, these two tasks are inherently coupled, as system states directly influence stability conditions. To address these challenges, this paper presents a multi-task learning framework based on spatiotemporal graph convolutional networks that efficiently performs both tasks. The proposed framework employs a spatiotemporal graph convolutional encoder to capture system topology features and integrates a self-attention U-shaped residual decoder to enhance prediction accuracy. Additionally, a Multi-Exit Network branch with confidence-based exit points enables efficient and reliable transient stability assessments. Experimental results on IEEE standard test systems and real-world power grids demonstrate the framework’s superiority as compared to state-of-the-art AI models, achieving a 48.1% reduction in prediction error, a 6.3% improvement in the classification F1 score, and a 52.1% decrease in inference time, offering a robust solution for modern power system monitoring and safety assessments. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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15 pages, 2587 KiB  
Article
Optimal Configuration Strategy of PV and ESS for Enhancing the Regulation Capability of Electric Vehicles Under the Scenario of Orderly Power Utilization
by Shunjiang Wang, Peng Qiu, Yiwen Feng and Xu Jin
Energies 2025, 18(6), 1530; https://doi.org/10.3390/en18061530 - 20 Mar 2025
Viewed by 205
Abstract
Orderly power consumption is an important method for maintaining the supply–demand balance in the power system. However, the large-scale integration of renewable energy significantly raises demand-side load flexibility requirements, challenging the implementation of orderly power utilization. The optimal configuration and scheduling of distributed [...] Read more.
Orderly power consumption is an important method for maintaining the supply–demand balance in the power system. However, the large-scale integration of renewable energy significantly raises demand-side load flexibility requirements, challenging the implementation of orderly power utilization. The optimal configuration and scheduling of distributed energy resources (DER), including electric vehicles (EVs) and energy storage systems (ESS), represent promising approaches to addressing this issue. However, current research neglects the influence of DER configuration schemes on the participation rate of EV users in orderly power utilization. This work proposes an optimized configuration strategy for PV and ESS to enhance the participation rate of EV users in grid regulation. An economic configuration model of PV and ESS is constructed to obtain the optimal configuration plan. An incentive pricing strategy based on the configuration plan is proposed to improve the participation rate of EV users in orderly power scheduling. Simulation results demonstrate the effectiveness of the proposed configuration strategy. Full article
(This article belongs to the Section E: Electric Vehicles)
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