Energies

17 pages, 4494 KB

Open AccessArticle

A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm

by Chuang Wang, Peijie Cong, Sifan Yu, Jing Yuan, Nian Lv, Yu Ling, Zheng Peng, Haoyan Zhang and Hongwei Mei

Energies 2025, 18(14), 3890; https://doi.org/10.3390/en18143890 - 21 Jul 2025

Viewed by 2398

Abstract

In the context of increasing the complexity and intelligence of modern power systems, traditional maintenance approaches for circuit breakers have shown limitations in meeting both reliability and economic requirements. This paper proposes a multi-sensor data fusion fault detection method based on the RF-Adaboost [...] Read more.

In the context of increasing the complexity and intelligence of modern power systems, traditional maintenance approaches for circuit breakers have shown limitations in meeting both reliability and economic requirements. This paper proposes a multi-sensor data fusion fault detection method based on the RF-Adaboost algorithm for spring-operated circuit breakers. By integrating pressure, speed, coil current, and energy storage motor sensors into the mechanism, multi-source operational data are acquired and processed via denoising and feature extraction techniques. A fault detection model is then constructed using the RF-Adaboost classifier. The experimental results demonstrate that the proposed method achieves over 96% accuracy in identifying typical fault states such as coil voltage deviation, reset spring fatigue, and closing spring degradation, outperforming conventional approaches. These results validate the model’s effectiveness and robustness in diagnosing complex mechanical failures in circuit breakers. Full article

(This article belongs to the Special Issue Advanced Control and Monitoring of High Voltage Power Systems)

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27 pages, 2186 KB

Open AccessArticle

Oil Futures Dynamics and Energy Transition: Evidence from Macroeconomic and Energy Market Linkages

by Xiaomei Yuan, Fang-Rong Ren and Tao-Feng Wu

Energies 2025, 18(14), 3889; https://doi.org/10.3390/en18143889 - 21 Jul 2025

Viewed by 537

Abstract

Understanding the price dynamics of oil futures is crucial for advancing green finance strategies and supporting sustainable energy transitions. This study investigates the macroeconomic and energy market determinants of oil futures prices through Granger causality, cointegration analysis, and the error correction model, using [...] Read more.

Understanding the price dynamics of oil futures is crucial for advancing green finance strategies and supporting sustainable energy transitions. This study investigates the macroeconomic and energy market determinants of oil futures prices through Granger causality, cointegration analysis, and the error correction model, using daily data. It focuses on the influence of economic development levels, exchange rate fluctuations, and inter-energy price linkages. The empirical findings indicate that (1) oil futures prices exhibit strong correlations with other energy prices, macroeconomic factors, and exchange rate variables; (2) economic development significantly affects oil futures prices, while exchange rate impacts are statistically insignificant based on the daily data analyzed; (3) there exists a stable long-term equilibrium relationship between oil futures prices and variables representing economic activity, exchange rates, and energy market trends; (4) oil futures prices exhibit significant short-term dynamics while adjusting steadily toward a long-run equilibrium driven by macroeconomic and energy market fundamentals. By enhancing the accuracy of oil futures price forecasting, this study offers practical insights for managing financial risks associated with fossil energy markets and contributes to the formulation of low-carbon investment strategies. The findings provide a valuable reference for integrating energy pricing models into sustainable finance and climate-aligned portfolio decisions. Full article

(This article belongs to the Topic Energy Economics and Sustainable Development)

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22 pages, 1475 KB

Open AccessSystematic Review

A Systematic Review of Grid-Forming Control Techniques for Modern Power Systems and Microgrids

by Paul Arévalo, Carlos Ramos and Agostinho Rocha

Energies 2025, 18(14), 3888; https://doi.org/10.3390/en18143888 - 21 Jul 2025

Viewed by 1727

Abstract

Looking toward the future, governments around the world have started to change their energy mix due to climate change. The new energy mix will consist mainly of Inverter-Based Resources (IBRs), such as wind and solar power. This transition from a synchronous to a [...] Read more.

Looking toward the future, governments around the world have started to change their energy mix due to climate change. The new energy mix will consist mainly of Inverter-Based Resources (IBRs), such as wind and solar power. This transition from a synchronous to a non-synchronous grid introduces new challenges in stability, resilience, and synchronization, necessitating advanced control strategies. Among these, Grid-Forming (GFM) control techniques have emerged as an effective solution for ensuring stable operations in microgrids and large-scale power systems with high IBRs integration. This paper presents a systematic review of GFM control techniques, focusing on their principles and applications. Using the PRISMA 2020 methodology, 75 studies published between 2015 and 2025 were synthesized to evaluate the characteristics of GFM control strategies. The review organizes GFM strategies, evaluates their performance under varying operational scenarios, and emphasizes persistent challenges like grid stability, inertia emulation, and fault ride-through capabilities. Furthermore, this study examines real-world implementations of GFM technology in modern power grids. Notable projects include the UK’s National Grid Pathfinder Program, which integrates GFM inverters to enhance stability, and Australia’s Hornsdale Power Reserve, where battery energy storage with GFM capabilities supports grid frequency regulation. Full article

(This article belongs to the Topic Modern Power Systems and Units)

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26 pages, 9458 KB

Open AccessArticle

Wettability Characteristics of Mixed Sedimentary Shale Reservoirs in Saline Lacustrine Basins and Their Impacts on Shale Oil Energy Replenishment: Insights from Alternating Imbibition Experiments

by Lei Bai, Shenglai Yang, Dianshi Xiao, Hongyu Wang, Jian Wang, Jin Liu and Zhuo Li

Energies 2025, 18(14), 3887; https://doi.org/10.3390/en18143887 - 21 Jul 2025

Viewed by 465

Abstract

Due to the complex mineral composition, low clay content, and strong heterogeneity of the mixed sedimentary shale in the Xinjiang Salt Lake Basin, the wettability characteristics of the reservoir and their influencing factors are not yet clear, which restricts the evaluation of oil-bearing [...] Read more.

Due to the complex mineral composition, low clay content, and strong heterogeneity of the mixed sedimentary shale in the Xinjiang Salt Lake Basin, the wettability characteristics of the reservoir and their influencing factors are not yet clear, which restricts the evaluation of oil-bearing properties and the identification of sweet spots. This paper analyzed mixed sedimentary shale samples from the Lucaogou Formation of the Jimsar Sag and the Fengcheng Formation of the Mahu Sag. Methods such as petrographic thin sections, X-ray diffraction, organic matter content analysis, and argon ion polishing scanning electron microscopy were used to examine the lithological and mineralogical characteristics, geochemical characteristics, and pore space characteristics of the mixed sedimentary shale reservoir. Alternating imbibition and nuclear magnetic resonance were employed to quantitatively characterize the wettability of the reservoir and to discuss the effects of compositional factors, lamina types, and pore structure on wettability. Research findings indicate that the total porosity, measured by the alternate imbibition method, reached 72% of the core porosity volume, confirming the effectiveness of alternate imbibition in filling open pores. The Lucaogou Formation exhibits moderate to strong oil-wet wettability, with oil-wet pores predominating and well-developed storage spaces; the Fengcheng Formation has a wide range of wettability, with a higher proportion of mixed-wet pores, strong heterogeneity, and weaker oil-wet properties compared to the Lucaogou Formation. TOC content has a two-segment relationship with wettability, where oil-wet properties increase with TOC content at low TOC levels, while at high TOC levels, the influence of minerals such as carbonates dominates; carbonate content shows an “L” type response to wettability, enhancing oil-wet properties at low levels (<20%), but reducing it due to the continuous weakening effect of minerals when excessive. Lamina types in the Fengcheng Formation significantly affect wettability differentiation, with carbonate-shale laminae dominating oil pores, siliceous laminae contributing to water pores, and carbonate–feldspathic laminae forming mixed pores; the Lucaogou Formation lacks significant laminae, and wettability is controlled by the synergistic effects of minerals, organic matter, and pore structure. Increased porosity strengthens oil-wet properties, with micropores promoting oil adsorption through their high specific surface area, while macropores dominate in terms of storage capacity. Wettability is the result of the synergistic effects of multiple factors, including TOC, minerals, lamina types, and pore structure. Based on the characteristic that oil-wet pores account for up to 74% in shale reservoirs (mixed-wet 12%, water-wet 14%), a wettability-targeted regulation strategy is implemented during actual shale development. Surfactants are used to modify oil-wet pores, while the natural state of water-wet and mixed-wet pores is maintained to avoid interference and preserve spontaneous imbibition advantages. The soaking period is thus compressed from 30 days to 3–5 days, thereby enhancing matrix displacement efficiency. Full article

(This article belongs to the Special Issue Sustainable Development of Unconventional Geo-Energy)

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24 pages, 5470 KB

Open AccessArticle

Research on Improved Technology of Totem-Pole Bridgeless PFC Circuit Based on Triangular Current Mode

by Pingjuan Niu, Jingying Guo, Zhigang Gao, Jingwen Yan and Shengwei Gao

Energies 2025, 18(14), 3886; https://doi.org/10.3390/en18143886 - 21 Jul 2025

Viewed by 778

Abstract

The totem-pole bridgeless power factor correction (PFC) circuit based on the triangular current mode (TCM) in the front-end PFC of a switching power supply has the advantage of realizing zero-voltage switching (ZVS) in the full working range. However, the TCM control based on [...] Read more.

The totem-pole bridgeless power factor correction (PFC) circuit based on the triangular current mode (TCM) in the front-end PFC of a switching power supply has the advantage of realizing zero-voltage switching (ZVS) in the full working range. However, the TCM control based on the critical conduction mode (CRM) further increases the inductance current ripple, and the traditional input voltage AC sampling circuit increases the circuit complexity and device cost. Therefore, this paper studies the corresponding improvement technology from two dimensions. Firstly, the coordinated interleaved parallel technology is employed to design the system’s overall control-improvement strategy. This approach not only achieves full working-range ZVS but also reduces both the inductor current ripple and power device stress. Simultaneously, an optimized input voltage sampling circuit is designed to accommodate varying voltage requirements of control chip pins. This circuit demonstrates strong synchronization in both voltage and phase sampling, and the structural characteristics of the optocoupler can also suppress electrical signal interference. Finally, a 600 W totem-pole bridgeless PFC prototype is developed. The experimental results demonstrate the effectiveness of the proposed improved method. The prototype efficiency peak reaches 97.3%. Full article

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17 pages, 1390 KB

Open AccessArticle

Microbial Valorization of Sunflower Husk for Sustainable Biohydrogen and Biomass Production

by Liana Vanyan, Akerke Toleugazykyzy, Kaisar Yegizbay, Ayaulym Daniyarova, Lyudmila Zuloyan, Gayane Mikoyan, Anait Vassilian, Anna Poladyan, Kairat Bekbayev and Karen Trchounian

Energies 2025, 18(14), 3885; https://doi.org/10.3390/en18143885 - 21 Jul 2025

Viewed by 520

Abstract

Various pretreatment methods for the valorization of sunflower husks (SHs) for H₂ gas generation through fermentation by Escherichia coli were investigated. We analyzed thermal treatment (TT), acid hydrolysis (AH), and alkaline hydrolysis (AlkH) at different substrate concentrations (50 g L⁻¹, [...] Read more.

Various pretreatment methods for the valorization of sunflower husks (SHs) for H₂ gas generation through fermentation by Escherichia coli were investigated. We analyzed thermal treatment (TT), acid hydrolysis (AH), and alkaline hydrolysis (AlkH) at different substrate concentrations (50 g L⁻¹, 75 g L⁻¹, 100 g L⁻¹, and 150 g L⁻¹) and dilution levels (undiluted, 2× diluted, and 5× diluted). A concentration of 75 g L⁻¹ SH that was acid-hydrolyzed and dissolved twice in the medium yielded optimal microbial growth, reaching 0.3 ± 0.1 g cell dry weight (CDW) L⁻¹ biomass. The highest substrate level enabling effective fermentation was 100 g L⁻¹, producing 0.37 ± 0.13 (g CDW) × L⁻¹ biomass after complete fermentation, while 150 g L⁻¹ exhibited pronounced inhibitory effects. It is worth mentioning that the sole alkaline treatment was not optimal for growth and H₂ production. Co-fermentation with glycerol significantly enhanced both biomass formation (up to 0.42 ± 0.15 (g CDW) × L⁻¹)) and H₂ production. The highest H₂ yield was observed during batch growth at 50 g L⁻¹ SH hydrolysate with 5× dilution, reaching up to 5.7 mmol H₂ (g sugar)⁻¹ with glycerol supplementation. This study introduces a dual-waste valorization strategy that combines agricultural and biodiesel industry residues to enhance clean energy generation. The novelty lies in optimizing pretreatment and co-substrate fermentation conditions to maximize both biohydrogen yield and microbial biomass using E. coli, a widely studied and scalable host. Full article

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35 pages, 28111 KB

Open AccessReview

Review of Aging Mechanism and Diagnostic Methods for Lithium-Ion Batteries

by Tiansi Wang, Hao Wang, Xiaoling Shen, Chenhao Lu, Lei Pei, Yixiang Xu, Wanlin Wang and Huanhuan Li

Energies 2025, 18(14), 3884; https://doi.org/10.3390/en18143884 - 21 Jul 2025

Viewed by 1195

Abstract

As an important component of current power and energy storage systems, lithium-ion batteries have essential scientific significance and application value in terms of accurately and reliably diagnosing their aging to determine system performance, identify potential faults in modules, and prolong their service life. [...] Read more.

As an important component of current power and energy storage systems, lithium-ion batteries have essential scientific significance and application value in terms of accurately and reliably diagnosing their aging to determine system performance, identify potential faults in modules, and prolong their service life. For this purpose, this paper first briefly describes the working principle of lithium-ion batteries and illustrates the possible impacts of various aging mechanisms on the state of battery capacity. Secondly, starting from both implementable and laboratory perspectives, it sorts out and summarizes the diagnostic mechanisms and applicable scenarios of current typical battery aging state assessment and diagnosis methods. Then, targeting the specific aging mechanisms involved in batteries, it elaborates on the targeted diagnosis processes for each aging mechanism. Finally, combined with implementable and laboratory diagnosis methods, it systematically summarizes a highly standardized and universal routine diagnosis process for battery aging. In addition, in combination with the latest development of aging diagnosis and related technologies, this paper reflects on and discusses the possible future development directions of battery diagnosis technologies. Full article

(This article belongs to the Section L: Energy Sources)

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54 pages, 3087 KB

Open AccessEditor’s ChoiceReview

Application of Energy Storage Systems to Enhance Power System Resilience: A Critical Review

by Muhammad Usman Aslam, Md Sazal Miah, B. M. Ruhul Amin, Rakibuzzaman Shah and Nima Amjady

Energies 2025, 18(14), 3883; https://doi.org/10.3390/en18143883 - 21 Jul 2025

Cited by 1 | Viewed by 1046

Abstract

The growing frequency and severity of extreme events, both natural and human-induced, have heightened concerns about the resilience of power systems. Enhancing the resilience of power systems alleviates the adverse impacts of power outages caused by unforeseen events, delivering substantial social and economic [...] Read more.

The growing frequency and severity of extreme events, both natural and human-induced, have heightened concerns about the resilience of power systems. Enhancing the resilience of power systems alleviates the adverse impacts of power outages caused by unforeseen events, delivering substantial social and economic benefits. Energy storage systems play a crucial role in enhancing the resilience of power systems. Researchers have proposed various single and hybrid energy storage systems to enhance power system resilience. However, a comprehensive review of the latest trends in utilizing energy storage systems to address the challenges related to improving power system resilience is required. This critical review, therefore, discusses various aspects of energy storage systems, such as type, capacity, and efficacy, as well as modeling and control in the context of power system resilience enhancement. Finally, this review suggests future research directions leading to optimal use of energy storage systems for enhancing resilience of power systems. Full article

(This article belongs to the Special Issue Climate Change in Power and Energy Systems: Challenges, Innovations, and Solutions)

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20 pages, 2324 KB

Open AccessArticle

Local and Neighboring Effects of China’s New Energy Demonstration City Policy on Inclusive Green Growth

by Yalin Duan, Hsing Hung Chen and Yuting Deng

Energies 2025, 18(14), 3882; https://doi.org/10.3390/en18143882 - 21 Jul 2025

Viewed by 555

Abstract

Amid mounting global climate change, resource scarcity, and environmental pressures, regional economies are accelerating their transition towards green and inclusive growth models. This research examines how China’s New Energy Demonstration City (NEDC) policy influences inclusive green growth (IGG), including its underlying mechanisms. Harnessing [...] Read more.

Amid mounting global climate change, resource scarcity, and environmental pressures, regional economies are accelerating their transition towards green and inclusive growth models. This research examines how China’s New Energy Demonstration City (NEDC) policy influences inclusive green growth (IGG), including its underlying mechanisms. Harnessing policy interventions as quasi-natural experiments, we use 2006–2022 panel datasets of 284 Chinese cities to develop a spatial difference-in-differences (SDID) model for causal inference. The findings are as follows: (1) The NEDC policy significantly enhances IGG in pilot cities while generating positive spatial spillover effects on neighboring cities, exhibiting an inverted U-shaped pattern; (2) The policy effects demonstrate pronounced regional heterogeneity, with the strongest impact observed in western China; (3) Mechanism analysis confirms that green technology innovation serves as a critical pathway through which the NEDC policy drives IGG. These findings provide robust empirical evidence for designing scalable policy promotion mechanisms and refining innovation-driven governance frameworks. Full article

(This article belongs to the Special Issue Available Energy and Environmental Economics: Volume II)

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22 pages, 5102 KB

Open AccessArticle

Approaches to Proxy Modeling of Gas Reservoirs

by Alexander Perepelkin, Anar Sharifov, Daniil Titov, Zakhar Shandrygolov, Denis Derkach and Shamil Islamov

Energies 2025, 18(14), 3881; https://doi.org/10.3390/en18143881 - 21 Jul 2025

Viewed by 401

Abstract

In the gas industry, accurate forecasting of gas production is critical for optimizing well operating conditions. Although traditional hydrodynamic models offer high accuracy, they are often computationally intensive and time-consuming, prompting a growing interest in proxy-based alternatives. This study proposes a hybrid methodology [...] Read more.

In the gas industry, accurate forecasting of gas production is critical for optimizing well operating conditions. Although traditional hydrodynamic models offer high accuracy, they are often computationally intensive and time-consuming, prompting a growing interest in proxy-based alternatives. This study proposes a hybrid methodology based on Spatio-Temporal Graph Neural Networks (ST-GNNs) for gas production forecasting. The methodology integrates graph neural networks to account for spatial interdependencies between wells with recurrent and convolutional neural networks for time-series analysis. The model was validated using an extensive set of hydrodynamic simulation calculations and real-world field data. On average, the ST-GNN method reduces computational time by a factor of 4.3 compared to traditional hydrodynamic models, with a median predictive error not exceeding 10% across diverse datasets, despite variability in specific scenarios. The ST-GNN framework demonstrates promising potential as a tool for operational and strategic planning. 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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21 pages, 985 KB

Open AccessArticle

Assessment of Grid-Tied Renewable Energy Systems’ Voltage Support Capability Under Various Reactive Power Compensation Devices

by Jie Cao, Mingshun Liu, Qinfeng Ma, Junqiu Fan, Dongkuo Song, Xia Zhou, Jianfeng Dai and Hao Wu

Energies 2025, 18(14), 3880; https://doi.org/10.3390/en18143880 - 21 Jul 2025

Viewed by 527

Abstract

The weak grid strength in regions with large-scale renewable energy integration has emerged as a universal challenge, limiting the further expansion of renewable energy development. Currently, the short-circuit ratio (SCR) is widely used to quantify the relative strength between AC systems and renewable [...] Read more.

The weak grid strength in regions with large-scale renewable energy integration has emerged as a universal challenge, limiting the further expansion of renewable energy development. Currently, the short-circuit ratio (SCR) is widely used to quantify the relative strength between AC systems and renewable energy. To address this issue, this study first analyzes and compares how different reactive power compensation methods enhance the SCR. It then proposes calculation frameworks for both the SCR and critical short-circuit ratio (CSCR) in renewable energy grid-connected systems integrated with reactive power compensation. Furthermore, based on these formulations, a quantitative evaluation methodology for voltage support strength is developed to systematically assess the improvement effects of various compensation approaches on grid strength. Finally, case studies verify that reactive power compensation provided by synchronous condensers effectively strengthens grid strength and facilitates the safe expansion of the renewable energy integration scale. Full article

(This article belongs to the Special Issue AI-Enhanced Operation and Management of Renewable Energy-Integrated Power Systems)

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18 pages, 3268 KB

Open AccessArticle

In Situ Emulsification Synergistic Self-Profile Control System on Offshore Oilfield: Key Influencing Factors and EOR Mechanism

by Liangliang Wang, Minghua Shi, Jiaxin Li, Baiqiang Shi, Xiaoming Su, Yande Zhao, Qing Guo and Yuan Yuan

Energies 2025, 18(14), 3879; https://doi.org/10.3390/en18143879 - 21 Jul 2025

Viewed by 420

Abstract

The in situ emulsification synergistic self-profile control system has wide application prospects for efficient development on offshore oil reservoirs. During water flooding in Bohai heavy oil reservoirs, random emulsification occurs with superimposed Jamin effects. Effectively utilizing this phenomenon can enhance the efficient development [...] Read more.

The in situ emulsification synergistic self-profile control system has wide application prospects for efficient development on offshore oil reservoirs. During water flooding in Bohai heavy oil reservoirs, random emulsification occurs with superimposed Jamin effects. Effectively utilizing this phenomenon can enhance the efficient development of offshore oilfields. This study addresses the challenges hindering water flooding development in offshore oilfields by investigating the emulsification mechanism and key influencing factors based on oil–water emulsion characteristics, thereby proposing a novel in situ emulsification flooding method. Based on a fundamental analysis of oil–water properties, key factors affecting emulsion stability were examined. Core flooding experiments clarified the impact of spontaneous oil–water emulsification on water flooding recovery. Two-dimensional T1–T2 NMR spectroscopy was employed to detect pure fluid components, innovating the method for distinguishing oil–water distribution during flooding and revealing the characteristics of in situ emulsification interactions. The results indicate that emulsions formed between crude oil and formation water under varying rheometer rotational speeds (500–2500 r/min), water cuts (30–80%), and emulsification temperatures (40–85 °C) are all water-in-oil (W/O) type. Emulsion viscosity exhibits a positive correlation with shear rate, with droplet sizes primarily ranging between 2 and 7 μm and a viscosity amplification factor up to 25.8. Emulsion stability deteriorates with increasing water cut and temperature. Prolonged shearing initially increases viscosity until stabilization. In low-permeability cores, spontaneous oil–water emulsification occurs, yielding a recovery factor of only 30%. For medium- and high-permeability cores (water cuts of 80% and 50%, respectively), recovery factors increased by 9.7% and 12%. The in situ generation of micron-scale emulsions in porous media achieved a recovery factor of approximately 50%, demonstrating significantly enhanced oil recovery (EOR) potential. During emulsification flooding, the system emulsifies oil at pore walls, intensifying water–wall interactions and stripping wall-adhered oil, leading to increased T2 signal intensity and reduced relaxation time. Oil–wall interactions and collision frequencies are lower than those of water, which appears in high-relaxation regions (T1/T2 > 5). The two-dimensional NMR spectrum clearly distinguishes oil and water distributions. Full article

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23 pages, 5040 KB

Open AccessFeature PaperArticle

Intelligent Modelling Techniques for Enhanced Thermal Comfort and Energy Optimisation in Residential Buildings

by Shamaila Iram, Hafiz Muhammad Athar Farid, Abduljelil Adeola Akande and Hafiz Muhammad Shakeel

Energies 2025, 18(14), 3878; https://doi.org/10.3390/en18143878 - 21 Jul 2025

Viewed by 446

Abstract

This study examines the utilisation of sophisticated predictive methodologies to enhance the energy efficiency and comfort of residential structures. The ASHRAE Global Thermal Comfort Database II was employed to construct and evaluate machine learning models that were designed to predict thermal comfort levels [...] Read more.

This study examines the utilisation of sophisticated predictive methodologies to enhance the energy efficiency and comfort of residential structures. The ASHRAE Global Thermal Comfort Database II was employed to construct and evaluate machine learning models that were designed to predict thermal comfort levels while optimising energy consumption. Air temperature, garment insulation, metabolic rate, air velocity, and humidity were identified as critical comfort determinants. Numerous predictive models were assessed, and XGBoost demonstrated improved performance as a result of hyperparameter optimisation (R² = 0.9394, MSE = 0.0224). The study underscores the ability of sophisticated algorithms to clarify the complex relationships between environmental factors and occupant comfort. This sophisticated modelling methodology provides a practical approach to enhancing the efficiency of residential energy consumption while simultaneously ensuring the comfort of the occupants, thereby promoting more sustainable and comfortable living environments. Full article

(This article belongs to the Special Issue The Implementation of Artificial Intelligence in Energy Internet and Smart Grid Digitization)

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26 pages, 2178 KB

Open AccessEditor’s ChoiceArticle

Optimizing Agri-PV System: Systematic Methodology to Assess Key Design Parameters

by Kedar Mehta and Wilfried Zörner

Energies 2025, 18(14), 3877; https://doi.org/10.3390/en18143877 - 21 Jul 2025

Cited by 1 | Viewed by 890

Abstract

Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, [...] Read more.

Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, shading factor, land equivalent ratio, photosynthetically active radiation (PAR) utilization, crop yield stability index, water use efficiency, and return on investment. We introduce a novel dual matrix Analytic Hierarchy Process (AHP) to evaluate their relative significance. An international panel of eighteen Agri-PV experts, encompassing academia, industry, and policy, provided pairwise comparisons of these indicators under two objectives: maximizing annual energy yield and sustaining crop output. The high consistency observed in expert responses allowed for the derivation of normalized weight vectors, which form the basis of two Weighted Influence Matrices. Analysis of Total Weighted Influence scores from these matrices reveal distinct priority sets: panel tilt, coverage ratio, and elevation are most influential for energy optimization, while PAR utilization, yield stability, and elevation are prioritized for crop productivity. This methodology translates qualitative expert knowledge into quantitative, actionable guidance, clearly delineating both synergies, such as the mutual benefit of increased elevation for energy and crop outcomes, and trade-offs, exemplified by the negative impact of high photovoltaic coverage on crop yield despite gains in energy output. By offering a transparent, expert-driven decision-support tool, this framework enables practitioners to customize Agri-PV system configurations according to local climatic, agronomic, and economic contexts. Ultimately, this approach advances the optimization of the food energy nexus and supports integrated sustainability outcomes in Agri-PV deployment. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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16 pages, 1856 KB

Open AccessArticle

Gas in Transition: An ARDL Analysis of Economic and Fuel Drivers in the European Union

by Olena Pavlova, Kostiantyn Pavlov, Oksana Liashenko, Andrzej Jamróz and Sławomir Kopeć

Energies 2025, 18(14), 3876; https://doi.org/10.3390/en18143876 - 21 Jul 2025

Viewed by 724

Abstract

This study investigates the short- and long-run drivers of natural gas consumption in the European Union using an ARDL bounds testing approach. The analysis incorporates GDP per capita, liquid fuel use, and solid fuel use as explanatory variables. Augmented Dickey–Fuller tests confirm mixed [...] Read more.

This study investigates the short- and long-run drivers of natural gas consumption in the European Union using an ARDL bounds testing approach. The analysis incorporates GDP per capita, liquid fuel use, and solid fuel use as explanatory variables. Augmented Dickey–Fuller tests confirm mixed integration orders, allowing valid ARDL estimation. The results reveal a statistically significant long-run relationship (cointegration) between gas consumption and the energy–economic system. In the short run, the use of liquid fuel exerts a strong positive influence on gas demand, while the effects of GDP materialise only after a two-year lag. Solid fuels show a delayed substitutive impact, reflecting the ongoing transition from coal. An error correction model confirms rapid convergence to equilibrium, with 77% of deviations corrected within one period. Recursive residual and CUSUM tests indicate structural stability over time. These findings highlight the responsiveness of EU gas demand to both economic and policy signals, offering valuable insights for energy modelling and strategic planning under the European Green Deal. Full article

(This article belongs to the Special Issue Towards Sustainable Energy Development: Energy Efficiency and Economic Growth)

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17 pages, 2649 KB

Open AccessArticle

Effect of Low-Temperature Preheating on the Physicochemical Properties and Energy Quality of Pine Sawdust

by Tingzhou Lei, Yang Mei, Yuanna Li, Yunbo Wang, Suyang Liu and Yantao Yang

Energies 2025, 18(14), 3875; https://doi.org/10.3390/en18143875 - 21 Jul 2025

Cited by 1 | Viewed by 387

Abstract

The advantages of torrefaction preheating, including the production of a hydrophobic solid product, improved particle size distribution, enhanced fuel properties with fewer environmental issues, decreased moisture content, and reduced volatile content. In order to meet the technical requirements of biomass oriented value-added and [...] Read more.

The advantages of torrefaction preheating, including the production of a hydrophobic solid product, improved particle size distribution, enhanced fuel properties with fewer environmental issues, decreased moisture content, and reduced volatile content. In order to meet the technical requirements of biomass oriented value-added and energy saving and emission reduction, pine sawdust (PS) was taken as the research object, and the physicochemical properties of the PS samples preheated at a low temperature were analyzed by synchronous thermal analysis (TG-DSC), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), and organic element analyzer (EA). The effect of preheating at a lower temperature on the physicochemical properties of PS was discussed. The results showed that, under the preheating condition of 200 °C, compared with PS, the water content of PS-200 decreased by 3.23%, the volatile content decreased by 3.69%, the fixed carbon increased by 6.81%, the calorific value increased by 6.90%, the equilibrium water content decreases from 7.06% to 4.46%, and the hydrophobicity increases. This research, based on the improvement of the quality of agricultural and forestry waste and the promotion of the strategy of converting waste into energy, has contributed to the advancement of sustainable energy production. Full article

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33 pages, 7013 KB

Open AccessArticle

Towards Integrated Design Tools for Water–Energy Nexus Solutions: Simulation of Advanced AWG Systems at Building Scale

by Lucia Cattani, Roberto Figoni, Paolo Cattani and Anna Magrini

Energies 2025, 18(14), 3874; https://doi.org/10.3390/en18143874 - 21 Jul 2025

Viewed by 761

Abstract

This study investigated the integration of advanced Atmospheric Water Generators (AWGs) within the design process of building energy systems, focusing on the water–energy nexus in the context of a real-life hospital building. It is based on a simulation approach, recognised as a viable [...] Read more.

This study investigated the integration of advanced Atmospheric Water Generators (AWGs) within the design process of building energy systems, focusing on the water–energy nexus in the context of a real-life hospital building. It is based on a simulation approach, recognised as a viable means to analyse and enhance AWG potentialities. However, the current state of research does not address the issue of AWG integration within building plant systems. This study contributes to fill such a research gap by building upon an authors’ previous work and proposing an enhanced methodology. The methodology describes how to incorporate a multipurpose AWG system into the energy simulation environment of DesignBuilder (DB), version 7.0.0116, through its coupling with AWGSim, version 1.20d, a simulation tool specifically developed for atmospheric water generators. The chosen case study is a wing of the Mondino Hospital in Pavia, Italy, selected for its complex geometry and HVAC requirements. By integrating AWG outputs—covering water production, heating, and cooling—into DB, this study compared two configurations: the existing HVAC system and an enhanced version that includes the AWG as plant support. The simulation results demonstrated a 16.3% reduction in primary energy consumption (from 231.3 MWh to 193.6 MWh), with the elimination of methane consumption and additional benefits in water production (257 m³). This water can be employed for photovoltaic panel cleaning, further reducing the primary energy consumption to 101.9 MWh (55.9% less than the existing plant), and for human consumption or other technical needs. Moreover, this study highlights the potential of using AWG technology to supply purified water, which can be a pivotal solution for hospitals located in areas affected by water crises. This research contributes to the atmospheric water field by addressing the important issue of simulating AWG systems within building energy design tools, enabling informed decisions regarding water–energy integration at the project stage and supporting a more resilient and sustainable approach to building infrastructure. Full article

(This article belongs to the Special Issue Performance Analysis of Building Energy Efficiency)

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2 pages, 126 KB

Open AccessCorrection

Correction: Esfandi et al. Energy, Exergy, Economic, and Exergoenvironmental Analyses of a Novel Hybrid System to Produce Electricity, Cooling, and Syngas. Energies 2020, 13, 6453

by Saeed Esfandi, Simin Baloochzadeh, Mohammad Asayesh, Mehdi Ali Ehyaei, Abolfazl Ahmadi, Amir Arsalan Rabanian, Biplab Das, Vitor A. F. Costa and Afshin Davarpanah

Energies 2025, 18(14), 3873; https://doi.org/10.3390/en18143873 - 21 Jul 2025

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Abstract

There was an error in the original publication [...] Full article

19 pages, 2382 KB

Open AccessArticle

A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm

by Shanshan Zhou, Jingguang Huang, Yuanning Zhang and Yulong Li

Energies 2025, 18(14), 3872; https://doi.org/10.3390/en18143872 - 21 Jul 2025

Viewed by 361

Abstract

To circumvent the computational bottlenecks associated with the intermediate steps (e.g., least squares fitting) in conventional sine wave similarity principles and directly acquire the energy metrics required for stabilized sinusoidal waveform characterization, this study leverages time domain probability distribution theory. From a complementary [...] Read more.

To circumvent the computational bottlenecks associated with the intermediate steps (e.g., least squares fitting) in conventional sine wave similarity principles and directly acquire the energy metrics required for stabilized sinusoidal waveform characterization, this study leverages time domain probability distribution theory. From a complementary advantage perspective, a novel transformer inrush current identification criterion is developed using the Wasserstein distance metric. The methodology employs feature discretization to extract target/template signals, transforming them into state vectors for sample labelling. By quantifying inter-signal energy distribution disparities through this framework, it achieves a precise waveform similarity assessment in sinusoidal regimes. The theoretical analysis and simulations demonstrate that the approach eliminates frequency domain computations while maintaining implementation simplicity. Compared with conventional sine wave similarity methods, the solution streamlines protection logic and significantly enhances practical applicability with accelerated response times. Furthermore, tests conducted on field-recorded circuit breaker closing waveforms using MATLAB R2022a confirm the effectiveness of the proposed method in improving transformer protection performance. Full article

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11 pages, 2972 KB

Open AccessArticle

ZnCu Metal–Organic Framework Electrocatalysts for Efficient Ammonia Decomposition to Hydrogen

by Mingguang Ouyang, Geng Chen, Weitao Ning, Xiaoyang Wang, Xiaojiang Mu and Lei Miao

Energies 2025, 18(14), 3871; https://doi.org/10.3390/en18143871 - 21 Jul 2025

Viewed by 558

Abstract

The electrocatalytic decomposition of ammonia represents a promising route for sustainable hydrogen production, yet current systems rely heavily on noble metal catalysts with prohibitive costs and limited durability. A critical challenge lies in developing non-noble electrocatalysts that simultaneously achieve high active site exposure, [...] Read more.

The electrocatalytic decomposition of ammonia represents a promising route for sustainable hydrogen production, yet current systems rely heavily on noble metal catalysts with prohibitive costs and limited durability. A critical challenge lies in developing non-noble electrocatalysts that simultaneously achieve high active site exposure, optimized electronic configurations, and robust structural stability. Addressing these requirements, this study strategically engineered Cu-doped ZIF-8 architectures via in situ growth on nickel foam (NF) substrates through a facile room-temperature hydrothermal synthesis approach. Systematic optimization of the Cu/Zn molar ratio revealed that Cu_0.7Zn_0.3-ZIF/NF achieved optimal performance, exhibiting a distinctive nanoflower-like architecture that substantially increased accessible active sites. The hybrid catalyst demonstrated superior electrocatalytic performance with a current density of 124 mA cm⁻² at 1.6 V vs. RHE and a notably low Tafel slope of 30.94 mV dec⁻¹, outperforming both Zn-ZIF/NF (39.45 mV dec⁻¹) and Cu-ZIF/NF (31.39 mV dec⁻¹). Combined XPS and EDS analyses unveiled a synergistic electronic structure modulation between Zn and Cu, which facilitated charge transfer and enhanced catalytic efficiency. A gas chromatography product analysis identified H₂ and N₂ as the primary gaseous products, confirming the predominant occurrence of the ammonia oxidation reaction (AOR). This study not only presents a noble metal-free electrocatalyst with exceptional efficiency and durability for ammonia decomposition but also demonstrates the significant potential of MOF-derived materials in sustainable hydrogen production technologies. Full article

(This article belongs to the Special Issue Advanced Energy Conversion Technologies Based on Energy Physics)

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24 pages, 2575 KB

Open AccessArticle

Performance Evaluation Model of Overhead Transmission Line Anti-Icing Strategies Considering Time Evolution

by Xuyang Li, Xiaojuan Xi, Zhengwei Guo, Yongjie Li, Muzi Li and Bing Fan

Energies 2025, 18(14), 3870; https://doi.org/10.3390/en18143870 - 21 Jul 2025

Viewed by 318

Abstract

Icing disasters can significantly reduce the reliability of overhead transmission lines, while limited budgets of power grid enterprises constrain the scale of investment. To improve investment efficiency, it is essential to balance the reliability and economic performance of anti-icing strategies. Most existing studies [...] Read more.

Icing disasters can significantly reduce the reliability of overhead transmission lines, while limited budgets of power grid enterprises constrain the scale of investment. To improve investment efficiency, it is essential to balance the reliability and economic performance of anti-icing strategies. Most existing studies on the performance evaluation of anti-icing strategies for transmission lines focus primarily on reliability, neglecting their economic implications. To address this gap, this paper proposes a time-evolution-based performance evaluation model for overhead transmission line anti-icing strategies. First, a lifetime distribution function of transmission lines during the icing period is constructed based on the Nelson–Aalen method and metal deformation theory. Subsequently, a quantitative risk model for iced transmission lines is developed, incorporating the failure rate, value of lost load, and amount of lost load, providing a monetary-based indicator for icing risk. Finally, a performance evaluation method for anti-icing strategies is developed based on the risk quantification model. Implementation cost is treated as risk control expenditure, and strategy performance is assessed by integrating it with residual risk cost to identify the optimal strategy through composite cost analysis. The proposed model enables a comprehensive assessment of anti-icing strategy performance, improving the accuracy of strategy selection and achieving a dynamic balance between implementation cost and transmission line reliability. The case study results demonstrate that the proposed method effectively reduces the risk of failure in overhead transmission lines under ice disasters while lowering anti-icing costs. Compared with two existing strategy selection approaches, the strategy based on this method achieved 46.11% and 32.56% lower composite cost, and 60.26% and 48.41% lower residual risk cost, respectively. Full article

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17 pages, 1224 KB

Open AccessArticle

Economic Efficiency of Renewable Energy Investments in Photovoltaic Projects: A Regression Analysis

by Adem Akbulut, Marcin Niemiec, Kubilay Taşdelen, Leyla Akbulut, Monika Komorowska, Atılgan Atılgan, Ahmet Coşgun, Małgorzata Okręglicka, Kamil Wiktor, Oksana Povstyn and Maria Urbaniec

Energies 2025, 18(14), 3869; https://doi.org/10.3390/en18143869 - 21 Jul 2025

Viewed by 639

Abstract

Energy Performance Contracts (EPC) are performance-based financing mechanisms designed to improve energy efficiency and support renewable energy adoption in the public sector. This study examines the economic efficiency of a 1710.72 kWp solar power plant (SPP), implemented under an EPC at Alanya Alaaddin [...] Read more.

Energy Performance Contracts (EPC) are performance-based financing mechanisms designed to improve energy efficiency and support renewable energy adoption in the public sector. This study examines the economic efficiency of a 1710.72 kWp solar power plant (SPP), implemented under an EPC at Alanya Alaaddin Keykubat University, using a regression-based analysis. The model evaluates the effects of solar radiation, investment cost, and electricity sales price on unit production cost, and its predictions were compared with actual production data. Results show the system exceeded the EPC contract target by 16.2%, producing 2,423,472.28 kWh in its first year and preventing 1168.64 tons of CO₂ emissions. The developed multiple linear regression model achieved a predictive error margin of 14.7%, confirming its validity. This study highlights the technical, economic, and environmental benefits of EPC applications in Türkiye’s public institutions and offers a practical decision-support framework for policymakers. The novelty lies in integrating a regression model with operational data and providing a comparative assessment of planned, predicted, and actual outcomes. Full article

(This article belongs to the Special Issue Towards Sustainable Energy Development: Energy Efficiency and Economic Growth)

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24 pages, 4004 KB

Open AccessArticle

Assessing the Impact of Solar Spectral Variability on the Performance of Photovoltaic Technologies Across European Climates

by Ivan Bevanda, Petar Marić, Ante Kristić and Tihomir Betti

Energies 2025, 18(14), 3868; https://doi.org/10.3390/en18143868 - 21 Jul 2025

Viewed by 530

Abstract

Precise photovoltaic (PV) performance modeling is essential for optimizing system design, operational monitoring, and reliable power forecasting—yet spectral correction is often overlooked, despite its significant impact on energy yield uncertainty. This study employs the FARMS-NIT model to assess the impact of spectral irradiance [...] Read more.

Precise photovoltaic (PV) performance modeling is essential for optimizing system design, operational monitoring, and reliable power forecasting—yet spectral correction is often overlooked, despite its significant impact on energy yield uncertainty. This study employs the FARMS-NIT model to assess the impact of spectral irradiance on eight PV technologies across 79 European sites, grouped by Köppen–Geiger climate classification. Unlike previous studies limited to clear-sky or single-site analysis, this work integrates satellite-derived spectral data for both all-sky and clear-sky scenarios, enabling hourly, tilt-optimized simulations that reflect real-world operating conditions. Spectral analyses reveal European climates exhibit blue-shifted spectra versus AM1.5 reference, only 2–5% resembling standard conditions. Thin-film technologies demonstrate superior spectral gains under all-sky conditions, though the underlying drivers vary significantly across climatic regions—a distinction that becomes particularly evident in the clear-sky analysis. Crystalline silicon exhibits minimal spectral sensitivity (<1.6% variations), with PERC/PERT providing highest stability. CZTSSe shows latitude-dependent performance with ≤0.7% variation: small gains at high latitudes and losses at low latitudes. Atmospheric parameters were analyzed in detail, revealing that air mass (AM), clearness index (K_t), precipitable water (W), and aerosol optical depth (AOD) play key roles in shaping spectral effects, with different parameters dominating in distinct climate groups. Full article

(This article belongs to the Special Issue Modern Technologies for Renewable Energy Development and Utilization: 5th Edition)

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19 pages, 11513 KB

Open AccessArticle

Experimental Study and CFD Analysis of a Steam Turbogenerator Based on a Jet Turbine

by Oleksandr Meleychuk, Serhii Vanyeyev, Serhii Koroliov, Olha Miroshnychenko, Tetiana Baha, Ivan Pavlenko, Marek Ochowiak, Andżelika Krupińska, Magdalena Matuszak and Sylwia Włodarczak

Energies 2025, 18(14), 3867; https://doi.org/10.3390/en18143867 - 21 Jul 2025

Viewed by 398

Abstract

Implementing energy-efficient solutions and developing energy complexes to decentralise power supply are key objectives for enhancing national security in Ukraine and Eastern Europe. This study compares the design, numerical, and experimental parameters of a channel-type jet-reaction turbine. A steam turbogenerator unit and a [...] Read more.

Implementing energy-efficient solutions and developing energy complexes to decentralise power supply are key objectives for enhancing national security in Ukraine and Eastern Europe. This study compares the design, numerical, and experimental parameters of a channel-type jet-reaction turbine. A steam turbogenerator unit and a pilot industrial experimental test bench were developed to conduct full-scale testing of the unit. The article presents experimental data on the operation of a steam turbogenerator unit with a capacity of up to 475 kW, based on a channel-type steam jet-reaction turbine (JRT), and includes the validation of a computational fluid dynamics (CFD) model against the obtained results. For testing, a pilot-scale experimental facility and a turbogenerator were developed. The turbogenerator consists of two parallel-mounted JRTs operating on a single electric generator. During experimental testing, the system achieved an electrical output power of 404 kW at a turbine rotor speed of 25,000 rpm. Numerical modelling of the steam flow in the flow path of the jet-reaction turbine was performed using ANSYS CFX 25 R1 software. The geometry and mesh setup were described, boundary conditions were defined, and computational calculations were performed. The experimental results were compared with those obtained from numerical simulations. In particular, the discrepancy in the determination of the power and torque on the shaft of the jet-reaction turbine between the numerical and full-scale experimental results was 1.6%, and the discrepancy in determining the mass flow rate of steam at the turbine inlet was 1.34%. JRTs show strong potential for the development of energy-efficient, low-power turbogenerators. The research results confirm the feasibility of using such units for decentralised energy supply and recovering secondary energy resources. This contributes to improved energy security, reduces environmental impact, and supports sustainable development goals. Full article

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28 pages, 19285 KB

Open AccessArticle

PV System Design in Different Climates: A BIM-Based Methodology

by Annamaria Ciccozzi, Tullio de Rubeis, Yun Ii Go and Dario Ambrosini

Energies 2025, 18(14), 3866; https://doi.org/10.3390/en18143866 - 21 Jul 2025

Viewed by 674

Abstract

One of the goals of Agenda 2030 is to increase the share of renewable energy in the global energy mix. In this context, photovoltaic systems play a key role in the transition to clean energy. According to the International Energy Agency, in 2023, [...] Read more.

One of the goals of Agenda 2030 is to increase the share of renewable energy in the global energy mix. In this context, photovoltaic systems play a key role in the transition to clean energy. According to the International Energy Agency, in 2023, solar photovoltaic alone accounted for three-quarters of renewable capacity additions worldwide. Designing a performing photovoltaic system requires careful planning that takes into account various factors, both internal and external, in order to maximize energy production and optimize costs. In addition to the technical characteristics of the system (internal factors), the positions and the shapes of external buildings and surrounding obstacles (external factors) have a significant impact on the output of photovoltaic systems. However, given the complexity of these environmental factors, they cannot be treated accurately in manual design practice. For this reason, this paper proposes a Building Information Modeling-based workflow for the design of a photovoltaic system that can guide the professional step-by-step throughout the design process, starting from the embryonic phase to the definitive, and therefore more detailed, one. The developed methodology allows for an in-depth analysis of the shading, the photovoltaic potential of the building, the performance of the photovoltaic system, and the costs for its construction in order to evaluate the appropriateness of the investment. The main aim of the paper is to create a standardized procedure applicable on a large scale for photovoltaic integration within Building Information Modeling workflows. The methodology is tested on two case studies, characterized by different architectural features and geographical positions. Full article

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21 pages, 4259 KB

Open AccessArticle

Transient Subcooled Boiling in Minichannels: Experimental Study and Numerical Modelling Using Trefftz Functions and ADINA

by Beata Maciejewska, Magdalena Piasecka and Paweł Łabędzki

Energies 2025, 18(14), 3865; https://doi.org/10.3390/en18143865 - 20 Jul 2025

Viewed by 514

Abstract

This study focuses on the phenomenon of boiling heat transfer during fluid flow (Fluorinert FC-72) in minichannels. The research stand was built around a specially designed test section incorporating sets of aligned minichannels, each 1 mm deep. These channel arrays varied in number, [...] Read more.

This study focuses on the phenomenon of boiling heat transfer during fluid flow (Fluorinert FC-72) in minichannels. The research stand was built around a specially designed test section incorporating sets of aligned minichannels, each 1 mm deep. These channel arrays varied in number, comprising configurations with 7, 15, 17, 19, 21, and 25 parallel channels. The test section was vertically orientated with upward fluid flow. To address the heat transfer problem associated with transient flow boiling, two numerical approaches grounded in the finite element method (FEM) were employed. One used the Trefftz function formulation, while the other relied on simulations performed using the commercial software ADINA (version 9.2). In both approaches, the heat transfer coefficient at the interface between the heated foil and the working fluid was determined by applying a Robin-type boundary condition, which required knowledge of the temperatures in both the foil and the fluid, along with the temperature gradient within the foil. The outcomes of both FEM-based models, as well as those of a simplified 1D method based on Newton’s cooling law, yielded satisfactory results. Full article

(This article belongs to the Special Issue Modeling, Optimization and Experimental Investigation of Heat Exchangers for Power Plants)

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26 pages, 6864 KB

Open AccessReview

Key Factors, Degradation Mechanisms, and Optimization Strategies for SCO₂ Heat Transfer in Microchannels: A Review

by Lianghui Guo, Ran Liu, Xiaoqin Xiong, Xinzhe Li, Aoxiang Yin, Runyao Han, Jiahao Zhang, Zhuoqian Liu and Keke Zhi

Energies 2025, 18(14), 3864; https://doi.org/10.3390/en18143864 - 20 Jul 2025

Viewed by 422

Abstract

Despite a growing body of research on supercritical carbon dioxide (SCO₂) heat transfer in microchannels, comprehensive reviews remain scarce. Existing studies predominantly focus on isolated experiments or simulations, yielding inconsistent findings and lacking a unified theory or optimization framework. This review [...] Read more.

Despite a growing body of research on supercritical carbon dioxide (SCO₂) heat transfer in microchannels, comprehensive reviews remain scarce. Existing studies predominantly focus on isolated experiments or simulations, yielding inconsistent findings and lacking a unified theory or optimization framework. This review systematically consolidates recent SCO₂ microchannel heat transfer advancements, emphasizing key performance factors, degradation mechanisms, and optimization strategies. We critically analyze over 260 studies (1962–2024), evaluating the experimental and numerical methodologies, heat transfer deterioration (HTD) phenomena, and efficiency enhancement techniques. Key challenges include the complexity of heat transfer mechanisms, discrepancies in experimental outcomes, and the absence of standardized evaluation criteria. Future research directions involve refining predictive models, developing mitigation strategies for HTD, and optimizing microchannel geometries to enhance thermal performance. This work not only integrates the current knowledge but also provides actionable insights for advancing SCO₂-based technologies in energy systems. Full article

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

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22 pages, 1400 KB

Open AccessArticle

Reliability Study of Electric Buses in the Urban Public Transport System

by Andrzej Niewczas, Joanna Rymarz, Marcin Ślęzak, Dariusz Kasperek and Piotr Hołyszko

Energies 2025, 18(14), 3863; https://doi.org/10.3390/en18143863 - 20 Jul 2025

Viewed by 664

Abstract

Contemporary research on electric buses focuses mainly on the following issues: energy efficiency, range and transport costs, and traction battery technology. However, little research has been conducted on operational reliability. This article presents a comparative assessment of the reliability of electric buses in [...] Read more.

Contemporary research on electric buses focuses mainly on the following issues: energy efficiency, range and transport costs, and traction battery technology. However, little research has been conducted on operational reliability. This article presents a comparative assessment of the reliability of electric buses in relation to combustion engine buses. The research was conducted under real conditions in the city of Lublin, Poland. The reliability functions of buses and their structural components were determined based on the Weibull distribution. It was shown that electric buses have a shorter distance between failures than combustion engine buses of analogous capacity. The statistical significance of the differences in reliability between electric and combustion engine buses was verified. The suitability of the Weibull model as a model of bus reliability in comparative studies was verified. The results of the research can be used to monitor current sustainable public transport development programs and to improve bus diagnostic and maintenance systems in transport companies. Full article

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23 pages, 9064 KB

Open AccessArticle

A Computational Thermo-Fluid Dynamics Simulation of Slot Jet Impingement Using a Generalized Two-Equation Turbulence Model

by Antonio Mezzacapo, Rossella D’Addio and Giuliano De Stefano

Energies 2025, 18(14), 3862; https://doi.org/10.3390/en18143862 - 20 Jul 2025

Viewed by 1637

Abstract

In this study, a computational thermo-fluid dynamics simulation of a wide-slot jet impingement heating process is performed. The present configuration consists of a turbulent incompressible air jet impinging orthogonally on an isothermal cold plate at a Reynolds number of around 11,000. The two-dimensional [...] Read more.

In this study, a computational thermo-fluid dynamics simulation of a wide-slot jet impingement heating process is performed. The present configuration consists of a turbulent incompressible air jet impinging orthogonally on an isothermal cold plate at a Reynolds number of around 11,000. The two-dimensional mean turbulent flow field is numerically predicted by solving Reynolds-averaged Navier–Stokes (RANS) equations, where the two-equation eddy viscosity k-

ω

model is utilized for turbulence closure. As the commonly used shear stress transport variant overpredicts heat transfer at the plate due to excessive turbulent diffusion, the recently developed generalized k-

ω

(GEKO) model is considered for the present analysis, where the primary model coefficients are suitably tuned. Through a comparative analysis of the various solutions against one another, in addition to reference experimental and numerical data, the effectiveness of the generalized procedure in predicting both the jet flow characteristics and the heat transfer at the plate is thoroughly evaluated, while determining the optimal set of model parameters. By improving accuracy within the RANS framework, the importance of model adaptability and parameter tuning for this specific fluid engineering application is demonstrated. This study offers valuable insights for improving predictive capability in turbulent jet simulations with broad engineering implications, particularly for industrial heating or cooling systems relying on wide-slot jet impingement. Full article

(This article belongs to the Special Issue Computational Fluids Dynamics in Energy Conversion and Heat Transfer)

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17 pages, 3065 KB

Open AccessFeature PaperArticle

Soot Mass Concentration Prediction at the GPF Inlet of GDI Engine Based on Machine Learning Methods

by Zhiyuan Hu, Zeyu Liu, Jiayi Shen, Shimao Wang and Piqiang Tan

Energies 2025, 18(14), 3861; https://doi.org/10.3390/en18143861 - 20 Jul 2025

Viewed by 368

Abstract

To improve the prediction accuracy of soot load in gasoline particulate filters (GPFs) and the control accuracy during GPF regeneration, this study developed a prediction model to predict the soot mass concentration at the GPF inlet of gasoline direct injection (GDI) engines using [...] Read more.

To improve the prediction accuracy of soot load in gasoline particulate filters (GPFs) and the control accuracy during GPF regeneration, this study developed a prediction model to predict the soot mass concentration at the GPF inlet of gasoline direct injection (GDI) engines using advanced machine learning methods. Three machine learning approaches, namely, support vector regression (SVR), deep neural network (DNN), and a Stacking integration model of SVR and DNN, were employed, respectively, to predict the soot mass concentration at the GPF inlet. The input data includes engine speed, torque, ignition timing, throttle valve opening angle, fuel injection pressure, and pulse width. Exhaust gas soot mass concentration at the three-way catalyst (TWC) outlet is obtained by an engine bench test. The results show that the correlation coefficients (R²) of SVR, DNN, and Stacking integration model of SVR and DNN are 0.937, 0.984, and 0.992, respectively, and the prediction ranges of soot mass concentration are 0–0.038 mg/s, 0–0.030 mg/s, and 0–0.07 mg/s, respectively. The distribution, median, and data density of prediction results obtained by the three machine learning approaches fit well with the test results. However, the prediction result of the SVR model is poor when the soot mass concentration exceeds 0.038 mg/s. The median of the prediction result obtained by the DNN model is closer to the test result, specifically for data points in the 25–75% range. However, there are a few negative prediction results in the test dataset due to overfitting. Integrating SVR and DNN models through stacked models extends the predictive range of a single SVR or DNN model while mitigating the overfitting of DNN models. The results of the study can serve as a reference for the development of accurate prediction algorithms to estimate soot loads in GPFs, which in turn can provide some basis for the control of the particulate mass and particle number (PN) emitted from GDI engines. Full article

(This article belongs to the Special Issue Internal Combustion Engines: Research and Applications—3rd Edition)

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