Energies

18 pages, 6313 KB

Open AccessArticle

Passivity Enhancement Strategy for Voltage-Controlled Aviation Converters with High Harmonic Mitigation Performance

by Xin Zhao, Anzhen Wu, Yaoshun Jia, Xiliang Chen, Xiangke Li and Xiaohua Wu

Energies 2025, 18(20), 5551; https://doi.org/10.3390/en18205551 - 21 Oct 2025

Viewed by 284

The rapid advancement of more electric aircraft technology has led to the widespread integration of non-linear loads into aircraft power supply systems. Passivity-based control (PBC) is a well-established method for enhancing system stability. However, existing research mainly focuses on current-controlled converters with control [...] Read more.

The rapid advancement of more electric aircraft technology has led to the widespread integration of non-linear loads into aircraft power supply systems. Passivity-based control (PBC) is a well-established method for enhancing system stability. However, existing research mainly focuses on current-controlled converters with control strategies confined to the fundamental component, while studies on passivity control for voltage-controlled converters incorporating harmonic mitigation remain limited. To enhance the stability of the standalone converters in aircraft power systems, this paper first proposes a method that transforms the converter output impedance into a product of two sub-impedances, thereby revealing the compensation mechanism of the output current feedforward active damping on the converter output impedance. Based on this insight, a second-order generalized integrator based active damping strategy is introduced to achieve sub-impedance phase compensation. Furthermore, to mitigate the adverse effect on converter passivity introduced by resonant controllers, a phase lead angle design strategy is proposed to ensure converter passivity from 0 Hz to the Nyquist frequency without compromising harmonic mitigation capability. Experimental results on a 5 kW three-phase converter validate the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Advanced Power Converters in Transportation Electrification)

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24 pages, 6101 KB

Open AccessArticle

Research on Energy-Saving Optimization of Mushroom Growing Control Room Based on Neural Network Model Predictive Control

by Yifan Song, Wengang Zheng, Guoqiang Guo, Mingfei Wang, Changshou Luo, Cheng Chen and Zuolin Li

Energies 2025, 18(20), 5550; https://doi.org/10.3390/en18205550 - 21 Oct 2025

Viewed by 310

Abstract

In the heating, ventilation, and air conditioning (HVAC) systems of mushroom growing control rooms, traditional rule-based control methods are commonly adopted. However, these methods are characterized by response delays, leading to underutilization of energy-saving potential and energy costs that constitute a disproportionately high [...] Read more.

In the heating, ventilation, and air conditioning (HVAC) systems of mushroom growing control rooms, traditional rule-based control methods are commonly adopted. However, these methods are characterized by response delays, leading to underutilization of energy-saving potential and energy costs that constitute a disproportionately high share of overall production costs. Therefore, minimizing the running time of the air conditioning system is crucial while maintaining the optimal growing environment for mushrooms. To address the aforementioned issues, this paper proposed a sensor optimization method based on the combination of principal component analysis (PCA) and information entropy. Furthermore, model predictive control (MPC) was implemented using a gated recurrent unit (GRU) neural network with an attention mechanism (GRU-Attention) as the prediction model to optimize the air conditioning system. First, a method combining PCA and information entropy was proposed to select the three most representative sensors from the 16 sensors in the mushroom room, thus eliminating redundant information and correlations. Then, a temperature prediction model based on GRU-Attention was adopted, with its hyperparameters optimized using the Optuna framework. Finally, an improved crayfish optimization algorithm (ICOA) was proposed as an optimizer for MPC. Its objective was to solve the control sequence with high accuracy and low energy consumption. The average energy consumption was reduced by approximately 11.2%, achieving a more stable temperature control effect. Full article

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18 pages, 4260 KB

Open AccessArticle

Simulation Modeling and Working Fluid Usage Reduction for Small-Scale Low-Temperature Organic Rankine Cycle (ORC) Plate Heat Exchangers

by Qingxu Ma, Yupei Lv, Haohan Sha, Haiming Yu and Siyi Luo

Energies 2025, 18(20), 5549; https://doi.org/10.3390/en18205549 - 21 Oct 2025

Viewed by 285

Abstract

In response to the increasingly severe energy crisis and global warming, ORC systems have attracted considerable attention owing to their ability to harness waste heat for power generation. Reducing the amount of organic working fluid in the heat exchanger can improve the economic [...] Read more.

In response to the increasingly severe energy crisis and global warming, ORC systems have attracted considerable attention owing to their ability to harness waste heat for power generation. Reducing the amount of organic working fluid in the heat exchanger can improve the economic performance of the ORC system. To achieve this aim, a new simulation model for plate evaporators and condensers of small/micro-scale ORC systems was developed, which can estimate the amount of organic working fluid and the outlet parameters. An ORC test rig was constructed to validate the model. Several experiments cases with different inlet temperatures were conducted. After validation, the impact of adjusting the operational and geometry parameters of the heat exchangers on the amount of organic working fluid was investigated. The results showed that appropriately increasing the temperature of the heat sources and cold sources or narrowing the heat exchanger width reduced the amount of working fluid in both the condenser and evaporator by over 30%. When adjusting the operational flow rate, the comprehensive impact on both the evaporator and condenser must be considered. The maximum mass was reduced by approximately 15.4%. The study results offer insights into designing plate evaporators and condensers for small/micro-scale ORC systems. Full article

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

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21 pages, 625 KB

Open AccessArticle

The Problem of Transforming the Energy System Towards Renewable Energy Sources as Perceived by Inhabitants of Rural Areas in South-Eastern Poland

by Ewa Chomać-Pierzecka, Magdalena Kowalska and Krzysztof Czyrka

Energies 2025, 18(20), 5548; https://doi.org/10.3390/en18205548 - 21 Oct 2025

Viewed by 377

Abstract

The current transformation of global energy systems has been the subject of a multi-faceted scientific discourse for years. Researchers focus on technical and technological aspects, seeking new and improved alternatives to current solutions. They also analyse formal and legal frameworks of the changes [...] Read more.

The current transformation of global energy systems has been the subject of a multi-faceted scientific discourse for years. Researchers focus on technical and technological aspects, seeking new and improved alternatives to current solutions. They also analyse formal and legal frameworks of the changes and evaluate their economic aspects or environmental effects. The public’s attitude towards the changes in light of demanding environmental conditions is investigated the least. In particular, little heed is paid to the opinions of rural populations, especially in Poland. In light of the above, this paper aims to analyse the issue of Poland’s energy transition and the public’s perception of the challenges of environmental protection and the resulting need to improve energy solutions to promote the dissemination of renewable energy sources. The research area was Poland, and detailed research was conducted in five districts (Małopolska region), where the age of the respondents was taken as the differentiating feature. The study was based on a literature review and, at a detailed level, on a diagnostic survey among residents of Wadowicki, Miechowski, Krakowski, Limanowski, and Tarnowski Districts. The 2024 CAPI (Computer Assisted Personal Interviewing) survey involved 300 randomly selected interviewees. The study employed a qualitative and quantitative approach, utilising statistical tools such as Spearman’s rank correlation coefficient analysis, the Kruskal–Wallis rank test, and the nonparametric Mann–Whitney U test. The statistical analysis was supported by IBM’s SPSS v.25. The results show that the majority of the population understand and agree with the need for an energy transition in Poland towards renewable energy. Indications of no opinion or in favour of non-renewable energy in the Polish energy system are distinct. This class of indications is determined by the interviewees’ age and suggests potential for improving public awareness of the matter in the group of mature respondents. Full article

(This article belongs to the Special Issue Socio-Economic and Environmental Aspects of the Energy Transition—Development Towards a Secure Future)

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27 pages, 5321 KB

Open AccessArticle

Beyond R²: The Role of Polynomial Degree in Modeling External Temperature and Its Impact on Heat-Pump Energy Demand

by Maciej Masiukiewicz, Giedrė Streckienė and Arkadiusz Gużda

Energies 2025, 18(20), 5547; https://doi.org/10.3390/en18205547 - 21 Oct 2025

Viewed by 245

Abstract

Missing values in hourly outdoor air temperature series are common and can bias building energy assessments that rely on uninterrupted temperature profiles. This paper examines how the polynomial degree can be used to reconstruct incomplete temperature data from the duration curve, which affect [...] Read more.

Missing values in hourly outdoor air temperature series are common and can bias building energy assessments that rely on uninterrupted temperature profiles. This paper examines how the polynomial degree can be used to reconstruct incomplete temperature data from the duration curve, which affect the energy indicators of an air-source heat pump (ASHP). Using an operational dataset from Opole, Poland (1 September 2019–31 August 2020; 5.1% gaps), global polynomials of degree n = 3…11 were fitted to the sorted hourly temperatures, and the reconstructions were mapped back to time. The reconstructions drive a building–ASHP model evaluated for two supply-water regimes (L_WT, leaving water temperature = 35 °C and 45 °C). Accuracy is assessed with mean absolute error (MAE), root-mean-square error (RMSE), and R² on observed, filled, and full subsets—including cold/hot tails—and propagated to energy metrics: seasonal space-heating demand (Q_season); electricity use (E_el); seasonal coefficient of performance (SCOP); peak electrical power (P_el,max); seasonal minimum coefficient of performance (COP_min); and the share of error due to filled hours (WFE_fill). All degrees satisfy

|{R E}_{Q_{s e a s o n}}| \leq 2 %

. For L_WT = 35 °C, relative changes span

{R E}_{E_{e l}}

≈ −2.22…−1.63% and

{R E}_{N_{e l, m a x}}

≈ −21.6…−7.7%, with

{E R}_{S C O P}

≈ +0.53…+0.80%. For L_WT = 45 °C,

{R E}_{E_{e l}}

remains ≈ −0.43% across degrees. A multi-criterion selection (seasonal bias, stability of energy indicators, tail errors, and WFE_fill) identifies n = 7 as the lowest sufficient degree: increasing n beyond seven yields negligible improvements while raising the overfitting risk. The proposed, data-driven procedure makes degree selection transparent and reproducible for gap-filled temperature inputs in ASHP studies. Full article

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20 pages, 5454 KB

Open AccessArticle

Investigation of Roadway Anti-Icing Without Auxiliary Heat Using Hydronic Heated Pavements Coupled with Borehole Thermal Energy Storage

by Sangwoo Park, Annas Fiaz Abbasi, Hizb Ullah, Wonjae Ha and Seokjae Lee

Energies 2025, 18(20), 5546; https://doi.org/10.3390/en18205546 - 21 Oct 2025

Viewed by 248

Abstract

Roadway anti-icing requires low-carbon alternatives to chloride salts and electric heating. This study evaluated a seasonal thermal energy storage system that couples a geothermal hydronic heated pavement (HHPS-G) with borehole thermal energy storage (BTES), operated without auxiliary heat. A coupled transient HHPS-G–BTES model [...] Read more.

Roadway anti-icing requires low-carbon alternatives to chloride salts and electric heating. This study evaluated a seasonal thermal energy storage system that couples a geothermal hydronic heated pavement (HHPS-G) with borehole thermal energy storage (BTES), operated without auxiliary heat. A coupled transient HHPS-G–BTES model was developed and validated against independent experimental data. A continuous cycle was then simulated, consisting of three months of summer pavement heat harvesting and BTES, followed by three months of winter heat discharge. A parametric analysis varied borehole depth (10, 20, and 40 m) and number of units (1, 2, and 4). Results indicated that depth is consistently more effective than unit number. Deeper fields produced larger summer pavement surface cooling with less long-term drift and yielded more persistent winter anti-icing performance. The 40 m 4-unit case lowered the end-of-summer surface temperature by 3.8 °C relative to the no-operation case and kept the surface at or above 0 °C throughout winter. In contrast, the 10 m–1-unit case was near 0 °C by late winter. A depth-first BTES design, supplemented by spacing or edge placement to limit interference, showed practical potential for anti-icing without auxiliary heat. Full article

(This article belongs to the Special Issue Geothermal Energy Heating Systems)

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26 pages, 5373 KB

Open AccessArticle

Toward Reliable FOWT Modeling: A New Calibration Approach for Extreme Environmental Loads

by Ho-Seong Yang, Ali Alkhabbaz and Young-Ho Lee

Energies 2025, 18(20), 5545; https://doi.org/10.3390/en18205545 - 21 Oct 2025

Viewed by 339

Abstract

The current paper presents a comparative analysis between a high-fidelity simulation tool and computational fluid dynamics (CFD) in evaluating the behavior of a fully coupled floating offshore wind turbine (FOWT) system subjected to three distinct design load cases, with a particular emphasis on [...] Read more.

The current paper presents a comparative analysis between a high-fidelity simulation tool and computational fluid dynamics (CFD) in evaluating the behavior of a fully coupled floating offshore wind turbine (FOWT) system subjected to three distinct design load cases, with a particular emphasis on extreme weather scenarios. While both approaches yielded comparable results under standard operational conditions, noticeable discrepancies emerged in surge drift and mooring line tension during typhoon conditions. The present work highlighted a significant limitation of standard calibration methods based on free-deck motion that are not reflective of the unique features of extreme environmental responses. To address this limitation, a novel calibration methodology is suggested that uses drag coefficients derived from direct measurement of extreme load cases. The prediction accuracy of the high-fidelity simulation model was significantly improved by refining the transverse component of the drag coefficients of major structural components, decreasing prediction accuracy of surge and mooring tension responses from almost 30% error to about 5%. Further, despite increasing the fidelity of calibration under extreme environmental conditions, it is primarily contingent on high-fidelity measurements corresponding to the use of the most conventional calibration approach under normal environmental conditions. Ultimately, the results demonstrate the need for accurate calibration approaches to provide reliable performance predictions of FOWT systems under varying extreme environmental conditions. Full article

(This article belongs to the Special Issue Advanced Wind Energy Systems: Comprehensive Insights into Analysis, Design, Control, and Optimization)

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19 pages, 1977 KB

Open AccessArticle

Research on the Evaluation Model for Natural Gas Pipeline Capacity Allocation Under Fair and Open Access Mode

by Xinze Li, Dezhong Wang, Yixun Shi, Jiaojiao Jia and Zixu Wang

Energies 2025, 18(20), 5544; https://doi.org/10.3390/en18205544 - 21 Oct 2025

Viewed by 308

Abstract

Compared with other fossil energy sources, natural gas is characterized by compressibility, low energy density, high storage costs, and imbalanced usage. Natural gas pipeline supply systems possess unique attributes such as closed transportation and a highly integrated upstream, midstream, and downstream structure. Moreover, [...] Read more.

Compared with other fossil energy sources, natural gas is characterized by compressibility, low energy density, high storage costs, and imbalanced usage. Natural gas pipeline supply systems possess unique attributes such as closed transportation and a highly integrated upstream, midstream, and downstream structure. Moreover, pipelines are almost the only economical means of onshore natural gas transportation. Given that the upstream of the pipeline features multi-entity and multi-channel supply including natural gas, coal-to-gas, and LNG vaporized gas, while the downstream presents a competitive landscape with multi-market and multi-user segments (e.g., urban residents, factories, power plants, and vehicles), there is an urgent social demand for non-discriminatory and fair opening of natural gas pipeline network infrastructure to third-party entities. However, after the fair opening of natural gas pipeline networks, the original “point-to-point” transaction model will be replaced by market-driven behaviors, making the verification and allocation of gas transmission capacity a key operational issue. Currently, neither pipeline operators nor government regulatory authorities have issued corresponding rules, regulations, or evaluation plans. To address this, this paper proposes a multi-dimensional quantitative evaluation model based on the Analytic Hierarchy Process (AHP), integrating both commercial and technical indicators. The model comprehensively considers six indicators: pipeline transportation fees, pipeline gas line pack, maximum gas storage capacity, pipeline pressure drop, energy consumption, and user satisfaction and constructs a quantitative evaluation system. Through the consistency check of the judgment matrix (CR = 0.06213 < 0.1), the weights of the respective indicators are determined as follows: 0.2584, 0.2054, 0.1419, 0.1166, 0.1419, and 0.1357. The specific score of each indicator is determined based on the deviation between each evaluation indicator and the theoretical optimal value under different gas volume allocation schemes. Combined with the weight proportion, the total score of each gas volume allocation scheme is finally calculated, thereby obtaining the recommended gas volume allocation scheme. The evaluation model was applied to a practical pipeline project. The evaluation results show that the AHP-based evaluation model can effectively quantify the advantages and disadvantages of different gas volume allocation schemes. Notably, the gas volume allocation scheme under normal operating conditions is not the optimal one; instead, it ranks last according to the scores, with a score 0.7 points lower than that of the optimal scheme. In addition, to facilitate rapid decision-making for gas volume allocation schemes, this paper designs a program using HTML and develops a gas volume allocation evaluation program with JavaScript based on the established model. This self-developed program has the function of automatically generating scheme scores once the proposed gas volume allocation for each station is input, providing a decision support tool for pipeline operators, shippers, and regulatory authorities. The evaluation model provides a theoretical and methodological basis for the dynamic optimization of natural gas pipeline gas volume allocation schemes under the fair opening model. It is expected to, on the one hand, provide a reference for transactions between pipeline network companies and shippers, and on the other hand, offer insights for regulatory authorities to further formulate detailed and fair gas transmission capacity transaction methods. Full article

(This article belongs to the Special Issue New Advances in Oil, Gas and Geothermal Reservoirs—3rd Edition)

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26 pages, 6714 KB

Open AccessArticle

Techno-Economic Analysis of Marine Hybrid Clusters for Use in Chile and Mexico

by Emiliano Gorr-Pozzi, Jorge Olmedo-González, Diego Selman-Caro, Manuel Corrales-González, Héctor García-Nava, Fabiola García-Vega, Itxaso Odériz, Giuseppe Giorgi, Rosa de G. González-Huerta, José A. Zertuche-González and Rodolfo Silva

Energies 2025, 18(20), 5543; https://doi.org/10.3390/en18205543 - 21 Oct 2025

Viewed by 383

Abstract

This study assesses the feasibility and profitability of marine hybrid clusters, combining wave energy converters (WECs) and offshore wind turbines (OWTs) to power households and marine aquaculture. Researchers analyzed two coastal sites: La Serena, Chile, with high and consistent wave energy resources, and [...] Read more.

This study assesses the feasibility and profitability of marine hybrid clusters, combining wave energy converters (WECs) and offshore wind turbines (OWTs) to power households and marine aquaculture. Researchers analyzed two coastal sites: La Serena, Chile, with high and consistent wave energy resources, and Ensenada, Mexico, with moderate and more variable wave power. Two WEC technologies, Wave Dragon (WD) and Pelamis (PEL), were evaluated alongside lithium-ion battery storage and green hydrogen production for surplus energy storage. Results show that La Serena’s high wave power (26.05 kW/m) requires less hybridization than Ensenada’s (13.88 kW/m). The WD device in La Serena achieved the highest energy production, while PEL arrays in Ensenada were more effective. The PEL-OWT cluster proved the most cost-effective in Ensenada, whereas the WD-OWT performed better in La Serena. Supplying electricity for seaweed aquaculture, particularly in La Serena, proves more profitable than for households. Ensenada’s clusters generate more surplus electricity, suitable for the electricity market or hydrogen conversion. This study emphasizes the importance of tailoring emerging WEC systems to local conditions, optimizing hybridization strategies, and integrating consolidated industries, such as aquaculture, to enhance both economic and environmental benefits. Full article

(This article belongs to the Special Issue Advanced Technologies for the Integration of Marine Energies)

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19 pages, 3418 KB

Open AccessArticle

Effect of Performance Packages on Fuel Consumption Optimization in Heavy-Duty Diesel Vehicles: A Real-World Fleet Monitoring Study

by Maria Antonietta Costagliola, Luca Marchitto, Marco Piras and Alessandra Berra

Energies 2025, 18(20), 5542; https://doi.org/10.3390/en18205542 - 21 Oct 2025

Viewed by 459

Abstract

In line with EU decarbonization targets for the heavy-duty transport sector, this study proposes an analytical methodology to assess the impact of diesel performance additives on fuel consumption in Euro 6 heavy-duty vehicles, the prevailing standard in the circulating European road tractor fleet. [...] Read more.

In line with EU decarbonization targets for the heavy-duty transport sector, this study proposes an analytical methodology to assess the impact of diesel performance additives on fuel consumption in Euro 6 heavy-duty vehicles, the prevailing standard in the circulating European road tractor fleet. A fleet of five N3-category road tractors equipped with tanker semi-trailers was monitored over two phases. During the first 10-month baseline phase, the vehicles operated with standard EN 590 diesel (containing 6–7% FAME); in the second phase, they used a commercially available premium diesel containing performance-enhancing additives. Fuel consumption and route data were collected using a GPS-based system interfaced with the engine control unit via the OBD port and integrated with the fleet tracking platform. After applying data filtering to exclude low-quality or non-representative trips, a 1% reduction in fuel consumption was observed with the use of fuel with additives. Route-level analysis revealed higher savings (up to 5.1%) in high-load operating conditions, while most trips showed improvements between −1.6% and −3.4%. Temporal analysis confirmed the general trend across varying vehicle usage patterns. Aggregated fleet-level data proved to be the most robust approach to mitigate statistical variability. To evaluate the potential impact at scale, a European scenario was developed: a 1% reduction in fuel consumption across the 6.75 million heavy-duty vehicles in the EU could yield annual savings of 2 billion liters of diesel and avoid approximately 6 million tons of CO₂ emissions. Even partial adoption could lead to meaningful environmental benefits. Alongside emissions reductions, fuel additives also offer economic value by lowering operating costs, improving engine efficiency, and reducing maintenance needs. Full article

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22 pages, 5276 KB

Open AccessArticle

An Approach to Identifying Factors Affecting Residential Energy Consumption at the Urban Block Scale: A Case Study of Gaziantep

by Mert Sercan Sagdicoglu, M. Serhat Yenice and F. Demet Aykal

Energies 2025, 18(20), 5541; https://doi.org/10.3390/en18205541 - 21 Oct 2025

Viewed by 329

Abstract

Previous studies on building energy performance have focused on single buildings or theoretical scenarios, remaining largely at the building scale and emphasizing envelope parameters. This study addresses this gap by systematically examining morphological parameters at the urban block scale through a five-step framework [...] Read more.

Previous studies on building energy performance have focused on single buildings or theoretical scenarios, remaining largely at the building scale and emphasizing envelope parameters. This study addresses this gap by systematically examining morphological parameters at the urban block scale through a five-step framework derived from the historical zoning evolution of Gaziantep (Turkiye), a city in a hot–dry climate. Four representative neighborhoods, reflecting different planning periods, were modeled in DesignBuilder v6.1 under a standardized envelope defined by national regulations. The analysis considered building orientation (15° vs. 45°), number of storeys (5–15), inter-building distance, and number of apartments per floor. Simulation results indicate that cooling energy demand is significantly higher than heating, with potential savings of up to 22% in total energy consumption depending on urban fabric parameters. The Alleben neighborhood, characterized by the oldest planned fabric, consumed 30% less cooling energy compared to the other regions. Orientation alone increased cooling demand by up to 12%. At the same time, compact urban forms reduced loads through mutual shading, while higher apartments per floor increased energy use due to the larger façade area and internal gains. By linking historical zoning evolution with block-scale simulations, this study provides a transferable framework that highlights the decisive role of planning parameters and offers practical guidance for climate-sensitive urban development. Full article

(This article belongs to the Section G: Energy and Buildings)

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16 pages, 1424 KB

Open AccessArticle

A Levelized Cost of Energy (LCOE) Analysis of a Reverse Electrodialysis (RED) Plant in Tuxpan, Mexico

by Monserrat Ortiz, Graciela Rivera and Edgar Mendoza

Energies 2025, 18(20), 5540; https://doi.org/10.3390/en18205540 - 21 Oct 2025

Viewed by 375

Abstract

The transition towards low-carbon energy systems requires the adoption of emerging renewable technologies that can diversify energy matrices and reduce greenhouse gas emissions. The present study evaluates the technical and economic feasibility of implementing a Reverse Electrodialysis (RED) plant for Salinity Gradient Energy [...] Read more.

The transition towards low-carbon energy systems requires the adoption of emerging renewable technologies that can diversify energy matrices and reduce greenhouse gas emissions. The present study evaluates the technical and economic feasibility of implementing a Reverse Electrodialysis (RED) plant for Salinity Gradient Energy (SGE) generation on the coast of Tuxpan, Veracruz, Mexico. This area has significant freshwater and seawater resources but high fossil-fuel dependence. A conceptual design was developed considering local hydrological and salinity conditions, membrane performance, and pre-treatment requirements. The analysis applied Levelized Cost of Energy (LCOE) and Net Present Value (NPV) methodologies to six water source combinations. Results indicate that the most favorable scenario, combining effluents from the municipal wastewater treatment plant and the Tuxpan river mouth, achieved the highest potential energy yield. However, high capital (USD 1.54 million) and operational costs resulted in negative NPVs, limiting short-term economic viability. Environmental assessment suggests RED could improve water quality and reduce pollutant discharge, though potential construction and operational impacts require mitigation. Despite current cost barriers, RED integration in coastal regions with similar characteristics offers a promising pathway for clean energy generation and environmental restoration, particularly if coupled with cost-reduction strategies and policy incentives. Full article

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

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30 pages, 2475 KB

Open AccessArticle

Can Hydrogen Be Produced Cost-Effectively from Heavy Oil Reservoirs?

by Chinedu J. Okere and James J. Sheng

Energies 2025, 18(20), 5539; https://doi.org/10.3390/en18205539 - 21 Oct 2025

Viewed by 407

Abstract

The potential for hydrogen production from heavy oil reservoirs has gained significant attention as a dual-benefit process for both enhanced oil recovery and low-carbon energy generation. This study investigates the technical and economic feasibility of producing hydrogen from heavy oil reservoirs using two [...] Read more.

The potential for hydrogen production from heavy oil reservoirs has gained significant attention as a dual-benefit process for both enhanced oil recovery and low-carbon energy generation. This study investigates the technical and economic feasibility of producing hydrogen from heavy oil reservoirs using two primary in situ combustion gasification strategies: cyclic steam/air and CO₂ + O₂ injection. Through a comprehensive analysis of technical barriers, economic drivers, and market conditions, we assess the hydrogen production potential of each method. While both strategies show promise, they face considerable challenges: the high energy demands associated with steam generation in the steam/air strategy, and the complexities of CO₂ procurement, capture, and storage in the CO₂ + O₂ method. The novelty of this work lies in combining CMG-STARS reservoir simulations with GoldSim techno-economic modeling to quantify hydrogen yields, production costs, and oil–hydrogen revenue trade-offs under realistic field conditions. The analysis reveals that under current technological and market conditions, the cost of hydrogen production significantly exceeds the market price, rendering the process economically uncompetitive. Furthermore, the dominance of oil production as the primary revenue source in both methods limits the economic viability of hydrogen production. Unless substantial advancements are made in technology or a more cost-efficient production strategy is developed, hydrogen production from heavy oil reservoirs is unlikely to become commercially viable in the near term. This study provides crucial insights into the challenges that must be addressed for hydrogen production from heavy oil reservoirs to be considered a competitive energy source. Full article

(This article belongs to the Section B: Energy and Environment)

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18 pages, 9888 KB

Open AccessArticle

Measuring and Simulating Wind Farm Wakes in the North Sea for Use in Assessing Other Regions

by Richard J. Foreman, Cristian Birzer and Beatriz Cañadillas

Energies 2025, 18(20), 5538; https://doi.org/10.3390/en18205538 - 21 Oct 2025

Viewed by 426

Abstract

“Wind theft”, the extraction of upstream wind resources by neighboring wind farms on account of wind farm or cluster wakes, is receiving wider popular attention. Cluster wakes need to be accounted for in wider planning strategies, for which measurements and wake models can [...] Read more.

“Wind theft”, the extraction of upstream wind resources by neighboring wind farms on account of wind farm or cluster wakes, is receiving wider popular attention. Cluster wakes need to be accounted for in wider planning strategies, for which measurements and wake models can be deployed to aid this process. To contribute to such planning measures, a flight campaign for investigating cluster waking and other phenomena in the North Sea was conducted in 2020 and 2021 to contribute extra flight data obtained during the first flight campaign of 2016 and 2017. We report the latest results of the 2020–2021 flight campaign following the work and methodology of Cañadillas et al. (2020), where, using the 2016–2017 flight measurements, wake lengths extending up to approximately 60 km in stable stratification were inferred, consistent with an explicit stability-dependent analytical model. Analysis of the recent 2020–2021 flight data is approximately consistent with the results of Cañadillas et al. (2020) in stable conditions, albeit with greater scatter. This is because Cañadillas et al. (2020) analyzed only flights in which the wind conditions remained nearly constant during the measurement period, whereas the current dataset includes more variable conditions. Comparisons with the analytical-based engineering model show good first-order agreement with the flight data, but higher-order effects, such as flow non-homogeneity, are not accounted for. The application of these results to the stability information for developing offshore wind energy regions such as the East Coast of the USA and Bass Strait, Australia gives an outline of the expected wake lengths there. Simple engineering models, such as that demonstrated here, though primarily designed for commercial applications, need to be further developed into advanced spatial planning frameworks for offshore wind energy areas. Full article

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

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16 pages, 6320 KB

Open AccessArticle

The Impact of Brine Saturation and Distribution on Lean Gas Huff-n-Puff EOR Performance of Tight Oil Reservoirs: Examples from the Montney Formation (Canada)

by Chengyao Song, Amin Ghanizadeh and Christopher R. Clarkson

Energies 2025, 18(20), 5537; https://doi.org/10.3390/en18205537 - 21 Oct 2025

Viewed by 259

Abstract

Oil recovery from low-permeability (‘tight’) oil reservoirs remains low despite the application of modern drilling and completions technologies, which has increased interest in trialing enhanced oil recovery (EOR) schemes. Cyclic gas injection (Huff-n-Puff, HNP) is a promising approach to EOR for these reservoirs. [...] Read more.

Oil recovery from low-permeability (‘tight’) oil reservoirs remains low despite the application of modern drilling and completions technologies, which has increased interest in trialing enhanced oil recovery (EOR) schemes. Cyclic gas injection (Huff-n-Puff, HNP) is a promising approach to EOR for these reservoirs. However, the underlying mechanisms of EOR using the HNP scheme in tight reservoirs are not yet fully understood. This laboratory study investigates the performance of lean gas (80%C₁ + 20%C₂; approximating produced gas compositions from the field) HNP using low-permeability core plug samples from the Montney Formation of Canada. An objective of the study was to evaluate the effects of induced fractures, and brine saturation and distribution, on the efficiency of lean gas HNP performance. Both intact and artificially fractured core plugs were studied. The introduction of fractures into the low-permeability core plugs improved recovery factors by 17.5–18.5%. However, the presence of brine limited oil production from both intact and fractured core plugs. Notably, when brine was concentrated along the fracture surfaces, the recovery factor dropped significantly, down to just 1.2% of original oil in place (OOIP). This reduction is primarily attributed to the low solubility of methane and ethane (C₁ + C₂) in brine, which hinders the injectant’s ability to diffuse into the core matrix and mobilize oil. The findings of this study will be of interest to operators evaluating the potential of cyclic gas injection in low-permeability reservoirs. Full article

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

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33 pages, 2631 KB

Open AccessSystematic Review

Battery Sizing and Composition in Energy Storage Systems for Domestic Renewable Energy Applications: A Systematic Review

by Ludovica Apa, Livio D’Alvia, Zaccaria Del Prete and Emanuele Rizzuto

Energies 2025, 18(20), 5536; https://doi.org/10.3390/en18205536 - 21 Oct 2025

Viewed by 473

Abstract

Renewable energy sources, such as photovoltaic panels and wind turbines, are increasingly integrated into domestic systems to address energy scarcity, rising demand, and climate change. However, their intermittent nature requires efficient energy storage systems (ESS) for stability and reliability. This systematic review, conducted [...] Read more.

Renewable energy sources, such as photovoltaic panels and wind turbines, are increasingly integrated into domestic systems to address energy scarcity, rising demand, and climate change. However, their intermittent nature requires efficient energy storage systems (ESS) for stability and reliability. This systematic review, conducted in accordance with PRISMA guidelines, aimed to evaluate the size and chemical composition of battery energy storage systems (BESS) in household renewable energy applications. A literature search was conducted in Scopus in August 2025 using predefined keywords, and studies published in English from 2015 onward were included. Exclusion criteria included book chapters, duplicate conference proceedings, geographically restricted case studies, systems without chemistry or size details, and those focusing solely on electric vehicle batteries. Of 308 initially retrieved records, 83 met the eligibility criteria and were included in the analysis. The majority (92%) employed simulation-based approaches, while 8% reported experimental setups. No formal risk-of-bias tool was applied, but a methodological quality check was conducted. Data were synthesized narratively and tabulated by chemistry, nominal voltage, capacity, and power. Lithium-ion batteries were the most prevalent (49%), followed by lead–acid (13%), vanadium redox flow (3.6%), and nickel–metal hydride (1.2%), with the remainder unspecified. Lithium-ion dominated due to high energy density, long cycle life, and efficiency. Limitations of the evidence include reliance on simulation studies, heterogeneity in reporting, and limited experimental validation. Overall, this review provides a framework for selecting and integrating appropriately sized and composed BESS into domestic renewable systems, offering implications for stability, efficiency, and household-level sustainability. The study was funded by the PNRR NEST project and Sapienza University of Rome Grant. Full article

(This article belongs to the Special Issue Thermo-Mechanical and Electrical Measurements for Energy Systems: 2nd Edition)

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35 pages, 2174 KB

Open AccessSystematic Review

The Real Option Approach to Investment Decisions in Hybrid Renewable Energy Systems: A Systematic Literature Review

by Anna Carozzani and Chiara D’Alpaos

Energies 2025, 18(20), 5535; https://doi.org/10.3390/en18205535 - 21 Oct 2025

Viewed by 439

Abstract

In recent years, the global energy crisis, concerns about energy security and grid parity, and the pressure to develop policies for reducing the environmental impact of anthropogenic activities have accelerated investments in renewable energy. A growing body of literature applies the real options [...] Read more.

In recent years, the global energy crisis, concerns about energy security and grid parity, and the pressure to develop policies for reducing the environmental impact of anthropogenic activities have accelerated investments in renewable energy. A growing body of literature applies the real options approach (ROA) to renewable energy projects, recognizing its value in capturing irreversibility and flexibility under uncertainty. The present work provides a detailed state-of-the-art analysis on the adoption of real options to evaluate mixes of energy technologies for power generation, with a special emphasis on investments in hydropower and solar photovoltaics. The objective is to assess current applications, identify knowledge gaps, and outline priorities for advancing decision-making tools in this domain. We performed a systematic literature review following the PRISMA protocol, identifying 38 papers from the Scopus database up to February 2024. Eligible studies were peer-reviewed articles in English applying the ROA to power generation, following a technology selection process; policy evaluation or research and development studies were excluded. The selected papers were analyzed to identify trends over time and space, adopted energy technology, types of real options with valuation methods, and sources of uncertainty. The present paper also discusses the main findings and emerging gaps, providing an overview of hybrid renewable energy systems. Our analysis suggests that, despite the significant advances achieved in this area, further research is needed to exploit the potential of the ROA in investment decisions for combined renewable energy technologies, especially in cases where internal uncertainty and community perspectives need to be explicitly considered. By linking the ROA to the challenges of mixed renewable energy projects, this study enhances understanding of investment decision-making under uncertainty and identifies pathways toward more robust and adaptive project evaluation. Full article

(This article belongs to the Special Issue New Approaches and Valuation in Electricity Markets: 2nd Edition)

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18 pages, 3728 KB

Open AccessArticle

Assessment of Potential of Organic Waste Methane for Implementation in Energy Self-Sufficient Wastewater Treatment Facilities

by Pawel Marczewski, Katarzyna Sytek-Szmeichel and Monika Zubrowska-Sudol

Energies 2025, 18(20), 5534; https://doi.org/10.3390/en18205534 - 21 Oct 2025

Viewed by 238

Abstract

The water sector faces a dual challenge: reducing energy consumption and carbon footprint while improving wastewater treatment efficiency. Anaerobic digestion (AD) remains the primary method for energy recovery in wastewater treatment plants (WWTPs). To enhance methane production and move toward carbon neutrality, co-digestion [...] Read more.

The water sector faces a dual challenge: reducing energy consumption and carbon footprint while improving wastewater treatment efficiency. Anaerobic digestion (AD) remains the primary method for energy recovery in wastewater treatment plants (WWTPs). To enhance methane production and move toward carbon neutrality, co-digestion of sewage sludge with external substrates is gaining attention. This study evaluated nine organic substrates for their methane potential using the standardized Automatic Methane Potential Test System (AMPTS). The highest methane yield was obtained from sediment from a wine tank, reaching 1387 NmL CH₄/g VS, followed by yeast slurry, with 524 NmL CH₄/g VS. These values were over 6 and 2.5 times higher, respectively, compared to the methane potential of conventional mixed municipal sludge. Apple pomace, whey, food biowaste, and herbal maceration waste showed moderate improvements (301–388 NmL CH₄/gVS). When considering methane yield per gram of wet substrate, herbal maceration waste was the most efficient. A techno-economic analysis revealed that this substrate consistently achieved a net-positive energy balance (up to 170%) in large WWTPs, even at transport distances of 50 km. Other substrates also showed high potential, covering nearly 100% of energy demand under optimal conditions. In contrast, whey showed limited applicability due to transport constraints. These findings highlight the importance of substrate selection, particularly in practical efforts aimed at achieving energy self-sufficiency in wastewater treatment plants. It also provides WWTP operators with clear and practical insights into enhancing methane yields from anaerobic digesters while minimizing the risk of process inhibition. Full article

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29 pages, 3574 KB

Open AccessArticle

CBATE-Net: An Accurate Battery Capacity and State-of-Health (SoH) Estimation Tool for Energy Storage Systems

by Fazal Ur Rehman, Concettina Buccella and Carlo Cecati

Energies 2025, 18(20), 5533; https://doi.org/10.3390/en18205533 - 21 Oct 2025

Viewed by 404

Abstract

In battery energy storage systems, accurately estimating battery capacity and state of health is crucial to ensure satisfactory operation and system efficiency and reliability. However, these tasks present particular challenges under irregular charge–discharge conditions, such as those encountered in renewable energy integration and [...] Read more.

In battery energy storage systems, accurately estimating battery capacity and state of health is crucial to ensure satisfactory operation and system efficiency and reliability. However, these tasks present particular challenges under irregular charge–discharge conditions, such as those encountered in renewable energy integration and electric vehicles, where heterogeneous cycling accelerates degradation. This study introduces a hybrid deep learning framework to address these challenges. It combines convolutional layers for localized feature extraction, bidirectional recurrent units for sequential learning and a temporal attention mechanism. The proposed hybrid deep learning model, termed CBATE-Net, uses ensemble averaging to improve stability and emphasizes degradation-critical intervals. The framework was evaluated using voltage, current and temperature signals from four benchmark lithium-ion cells across complete life cycles, as part of the NASA dataset. The results demonstrate that the proposed method can accurately track both smooth and abrupt capacity fade while maintaining stability near the end of the life cycle, an area in which conventional models often struggle. Integrating feature learning, temporal modelling and robustness enhancements in a unified design provides the framework with the ability to make accurate and interpretable predictions, making it suitable for deployment in real-world battery energy storage applications. Full article

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

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5 pages, 162 KB

Open AccessEditorial

Energy-Efficient Chemistry

by Gabriella Fiorentino

Energies 2025, 18(20), 5532; https://doi.org/10.3390/en18205532 - 21 Oct 2025

Viewed by 222

Abstract

The growing environmental concerns related to climate change and resource depletion urgently call for a global and profound innovation of industrial production models and energy systems to foster the adoption of environmentally efficient technologies, circular economy principles, and long-term sustainable value chains [...] [...] Read more.

The growing environmental concerns related to climate change and resource depletion urgently call for a global and profound innovation of industrial production models and energy systems to foster the adoption of environmentally efficient technologies, circular economy principles, and long-term sustainable value chains [...] Full article

(This article belongs to the Collection Energy-Efficient Chemistry)

18 pages, 9828 KB

Open AccessArticle

Study on Surface Charge Inversion and Accumulation Characteristics of DC Pillar Insulators Based on B-Spline Basis Functions

by Xi Yang, Houde Xu, Jie Wang, Jian Zhang, Shun Li and Xinran Fang

Energies 2025, 18(20), 5531; https://doi.org/10.3390/en18205531 - 21 Oct 2025

Viewed by 228

Abstract

Surface charge accumulation is an important cause of flashover accidents for DC pillar insulators and the failure of DC gas insulation equipment. In this paper, the DC pillar insulator is taken as the research object, and a surface potential measurement system is built. [...] Read more.

Surface charge accumulation is an important cause of flashover accidents for DC pillar insulators and the failure of DC gas insulation equipment. In this paper, the DC pillar insulator is taken as the research object, and a surface potential measurement system is built. The surface potential distribution of the pillar insulator under different voltages is measured. An inversion algorithm based on the B-spline basis function is proposed. The electric field simulation model of the DC pillar insulator considering the gas’s weak ionization and surface conductance is established. The surface charge accumulation characteristics of the pillar insulator under different DC voltages are studied. The results show that the surface potential of the DC pillar insulator presents an oscillating distribution in the axial direction, and the potential distribution is approximately mirror symmetry under positive and negative voltages. The surface charge density is non-uniform in the axial direction, and the surface charge distribution is different under different voltages. In addition, the current density on the solid side gradually approaches and exceeds the current density on the gas side with the increase in the applied voltage, which promotes the accumulation of charges on the insulator surface with the same symbol as the electrode to weaken the field strength and balance the normal electric field components on both sides. Full article

(This article belongs to the Special Issue Insulating Materials for Future Power Systems: Performance Analysis, Defect Detection and Condition Assessment: 2nd Edition)

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25 pages, 9736 KB

Open AccessArticle

Adaptive Sliding Mode Observers for Speed Sensorless Induction Motor Control and Their Comparative Performance Tests

by Halil Burak Demir, Murat Barut, Recep Yildiz and Emrah Zerdali

Energies 2025, 18(20), 5530; https://doi.org/10.3390/en18205530 - 21 Oct 2025

Viewed by 286

Abstract

This paper presents adaptive sliding mode observers (A-SMOs) performing speed estimation for sensorless induction motor drives utilized in both industrial and electrical vehicle (EV) applications due to their computational simplicity. The fact that the constant switching gain (

λ_{0}

) is used [...] Read more.

This paper presents adaptive sliding mode observers (A-SMOs) performing speed estimation for sensorless induction motor drives utilized in both industrial and electrical vehicle (EV) applications due to their computational simplicity. The fact that the constant switching gain (

λ_{0}

) is used in conventional SMOs (C-SMOs) leads to the chattering problem, especially in low-speed regions. To tackle this issue, this paper proposes two different

λ_{0}

adaptation mechanisms based on fuzzy and curve fitting methods. To estimate stator stationary axis components of stator currents and rotor fluxes together with the rotor speed, the proposed A-SMOs only utilize the measured stator currents and voltages of the IM. Here, the difference only between the estimated and measured stator currents is determined as the sliding surface in the proposed A-SMOs. To demonstrate the effectiveness of the proposed fuzzy-based A-SMO (FA-SMO) and curve fitting-based A-SMO (CFA-SMO), they are compared with C-SMO in real-time experiments for different scenarios including wide speed range operations of IM with/without load torque changes. Moreover, the stator and rotor resistances as well as the magnetizing inductance variations are also examined in real-time experiments of the proposed methods and the conventional one. The estimation results demonstrate how positively the

λ_{0}

adaptations in FA-SMO and CFA-SMO affect the performance of C-SMO. Finally, two A-SMOs with improved performance are introduced and verified through real-time experiments. Full article

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23 pages, 4498 KB

Open AccessArticle

Experimental and Numerical Evaluation of CO₂-Induced Wettability Alteration in Carbonate Reservoir CCUS

by Mohammad Al-Ghnemi, Erdal Ozkan and Hossein Kazemi

Energies 2025, 18(20), 5529; https://doi.org/10.3390/en18205529 - 20 Oct 2025

Viewed by 304

Abstract

This study presents both laboratory measurements and numerical modeling of wettability alterations following carbon dioxide (CO₂) injection in limestone carbonate reservoirs. Both synthetic and crude oil systems were evaluated using a Drop Shape Analyzer (DSA-100) to quantitatively measure the contact angle [...] Read more.

This study presents both laboratory measurements and numerical modeling of wettability alterations following carbon dioxide (CO₂) injection in limestone carbonate reservoirs. Both synthetic and crude oil systems were evaluated using a Drop Shape Analyzer (DSA-100) to quantitatively measure the contact angle and interfacial tension (IFT) on limestone core samples under ambient and reservoir conditions. The results demonstrated that carbonated brine significantly reduced the IFT (2.0–4.1 dynes/cm) and contact angle (11.9–16.0°), indicating a shift toward more water-wet conditions, compared with the modest reductions in contact angle achieved with standard brine (1.6–6.7°). Synthetic fluid systems containing naphthenic acid initially exhibited stronger oil-wet behavior but also experienced wettability alterations when exposed to CO₂. A previously developed compositional reservoir simulation model, which was based on assumed relative permeability endpoints, was revised to incorporate the experimental findings of this study as a supporting tool. Incorporating the experimental wettability alteration effect of CO₂ in the numerical model by a 5.2% reduction in the residual oil saturation (the relative permeability endpoint) caused 2% increase in the oil recovery factor and 12% improvement in the CO₂ utilization efficiency (9780 standard cubic feet per stock tank barrel (SCF/STB) vs. 8620 SCF/STB). Overall, this work provides critical laboratory validation and supports by numerical simulation that CO₂-induced wettability alteration is a key mechanism underpinning CO₂-based enhanced oil recovery (EOR) and carbon capture, utilization, and storage (CCUS) deployment in limestone carbonate formations. Full article

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23 pages, 7592 KB

Open AccessArticle

Numerical Modelling of Gas Mixing in Salt Caverns During Cyclic Hydrogen Storage

by Krzysztof Miłek and Wiesław Szott

Energies 2025, 18(20), 5528; https://doi.org/10.3390/en18205528 - 20 Oct 2025

Viewed by 400

Abstract

This study presents the development of a robust numerical model for simulating underground hydrogen storage (UHS) in salt caverns, with a particular focus on the interactions between original gas-methane (CH₄) and injected gas represented by hydrogen (H₂). Using the [...] Read more.

This study presents the development of a robust numerical model for simulating underground hydrogen storage (UHS) in salt caverns, with a particular focus on the interactions between original gas-methane (CH₄) and injected gas represented by hydrogen (H₂). Using the Schlumberger Eclipse 300 compositional reservoir simulator, the cavern was modelled as a highly permeable porous medium to accurately represent gas flow dynamics. Two principal mixing mechanisms were investigated: physical dispersion, modelled by numerical dispersion, and molecular diffusion. Multiple cavern configurations and a range of dispersion–diffusion coefficients were assessed. The results indicate that physical dispersion is the primary factor affecting hydrogen purity during storage cycles, while molecular diffusion becomes more significant during long-term gas storage. Gas mixing was shown to directly impact the calorific value and quality of withdrawn hydrogen. This work demonstrates the effectiveness of commercial reservoir simulators for UHS analysis and proposes a methodological framework for evaluating hydrogen purity in salt cavern storage operations. Full article

(This article belongs to the Special Issue Hydrogen Storage and Transportation: Materials, Technologies, and Infrastructure Development)

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4 pages, 141 KB

Open AccessEditorial

Topic: Water and Energy Monitoring and Their Nexus

by Lucas Pereira, Hugo Morais and Wolf-Gerrit Früh

Energies 2025, 18(20), 5527; https://doi.org/10.3390/en18205527 - 20 Oct 2025

Viewed by 229

Abstract

The global community faces unprecedented pressures on its vital water and energy infrastructures, exacerbated by challenges such as drought, escalating population growth, evolving energy and land use patterns, profound socioeconomic shifts, and a rapidly changing climate [...] Full article

(This article belongs to the Topic Water and Energy Monitoring and Their Nexus)

12 pages, 2216 KB

Open AccessArticle

LightGBM Medium-Term Photovoltaic Power Prediction Integrating Meteorological Features and Historical Data

by Yu Yang, Soon-Hyung Lee, Yong-Sung Choi and Kyung-Min Lee

Energies 2025, 18(20), 5526; https://doi.org/10.3390/en18205526 - 20 Oct 2025

Viewed by 431

Abstract

This paper proposes a Light Gradient Boosting Machine (LightGBM) model for medium-term photovoltaic (PV) power forecasting by integrating meteorological features with historical generation data. This approach addresses prediction biases that often arise when relying solely on a single meteorological data source. Historical power [...] Read more.

This paper proposes a Light Gradient Boosting Machine (LightGBM) model for medium-term photovoltaic (PV) power forecasting by integrating meteorological features with historical generation data. This approach addresses prediction biases that often arise when relying solely on a single meteorological data source. Historical power output and meteorological variables (irradiance, temperature, humidity, etc.) were collected from a PV station and preprocessed through data cleaning, standardization, and temporal alignment to construct a multivariate prediction framework. A comprehensive feature set was then built, including meteorological, temporal, interaction, and lag features. Feature importance analysis and Recursive Feature Elimination (RFE) were employed for input optimization, while feature-layer concatenation was applied for data fusion. Finally, the LightGBM (Version 2.3.1) framework, combined with Bayesian optimization and time-series cross-validation, was used to enhance generalization and predictive robustness. Experimental results confirm that the model achieved an MAE of 37.49, RMSE of 64.67, and R² of 0.89. The model effectively captured high-dimensional nonlinear relationships, thereby improving the accuracy of medium-term photovoltaic forecasts and providing reliable decision support for power system scheduling and renewable energy integration. Full article

(This article belongs to the Special Issue AI Solutions for Energy Management: Smart Grids and EV Charging)

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21 pages, 1266 KB

Open AccessArticle

Risk Assessment of Offshore Wind–Solar–Current Energy Coupling Hydrogen Production Project Based on Hybrid Weighting Method and Aggregation Operator

by Yandong Du, Xiaoli Chen, Yao Dong, Xinyue Zhou, Yangwen Wu and Qiang Lu

Energies 2025, 18(20), 5525; https://doi.org/10.3390/en18205525 - 20 Oct 2025

Viewed by 317

Abstract

Under the dual pressures of global climate change and energy structure transition, the offshore wind–solar–current energy coupling hydrogen production (OCWPHP) system has emerged as a promising integrated energy solution. However, its complex multi-energy structure and harsh marine environment introduce systemic risks that are [...] Read more.

Under the dual pressures of global climate change and energy structure transition, the offshore wind–solar–current energy coupling hydrogen production (OCWPHP) system has emerged as a promising integrated energy solution. However, its complex multi-energy structure and harsh marine environment introduce systemic risks that are challenging to assess comprehensively using traditional methods. To address this, we develop a novel risk assessment framework based on hesitant fuzzy sets (HFS), establishing a multidimensional risk criteria system covering economic, technical, social, political, and environmental aspects. A hybrid weighting method integrating AHP, entropy weighting, and consensus adjustment is proposed to determine expert weights while minimizing risk information loss. Two aggregation operators—AHFOWA and AHFOWG—are applied to enhance uncertainty modeling. A case study of an OCWPHP project in the East China Sea is conducted, with the overall risk level assessed as “Medium.” Comparative analysis with the classical Cumulative Prospect Theory (CPT) method shows that our approach yields a risk value of 0.4764, closely aligning with the CPT result of 0.4745, thereby confirming the feasibility and credibility of the proposed framework. This study provides both theoretical support and practical guidance for early-stage risk assessment of OCWPHP projects. Full article

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

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25 pages, 10087 KB

Open AccessArticle

Stability Assessment and Current Controller Design for Multiple Grid-Connected Inverters Under LC Grid Impedance and Grid Distortions

by Sung-Dong Kim, Min Kang, Seung-Yong Yeo, Luong Duc-Tai Cu and Kyeong-Hwa Kim

Energies 2025, 18(20), 5524; https://doi.org/10.3390/en18205524 - 20 Oct 2025

Viewed by 239

Abstract

The increasing global energy demand is driving the deployment of renewable energy in the electrical power infrastructure, which emphasizes the critical importance of grid-connected inverters (GCIs). As the power injected into the utility grid increases, GCIs commonly operate in parallel. However, interactions between [...] Read more.

The increasing global energy demand is driving the deployment of renewable energy in the electrical power infrastructure, which emphasizes the critical importance of grid-connected inverters (GCIs). As the power injected into the utility grid increases, GCIs commonly operate in parallel. However, interactions between multiple GCIs and the presence of LC grid impedance pose significant challenges to the stable operation of GCIs. Existing control strategies to deal with multiple GCIs often neglect the capacitive component of grid impedance, which results in instability and deteriorated power quality in a complex grid condition. To overcome these problems, this study proposes a current control scheme and stability assessment of multiple GCIs. To effectively mitigate high-frequency resonance, the proposed method is achieved by an incomplete state feedback control which eliminates the feedback control terms for unmeasurable states. Furthermore, resonant and integral control terms are incorporated to reduce steady-state error as well as to improve harmonic compensation induced by the PCC voltages. A full-state observer is employed to reduce sensing requirements and simplify system complexity. Multiple-GCI behavior is comprehensively analyzed under complex grid environments. A comprehensive stability assessment is also conducted to evaluate the interactions of multiple GCI systems with LC grid impedance. The effectiveness of the designed controller in enhancing power quality and guaranteeing system stability is validated by theoretical analysis, PSIM simulations, and experimental tests on a DSP-controlled 2 kW prototype system. Full article

(This article belongs to the Special Issue Advances in Microgrid Power Management: Cutting-Edge Approaches and Emerging Technologies)

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27 pages, 2075 KB

Open AccessReview

Physics-Informed Machine Learning for Intelligent Gas Turbine Digital Twins: A Review

by Hiyam Farhat and Amani Altarawneh

Energies 2025, 18(20), 5523; https://doi.org/10.3390/en18205523 - 20 Oct 2025

Viewed by 720

Abstract

This review surveys recent progress in hybrid artificial intelligence (AI) approaches for gas turbine intelligent digital twins, with an emphasis on models that integrate physics-based simulations and machine learning. The main contribution is the introduction of a structured classification of hybrid AI methods [...] Read more.

This review surveys recent progress in hybrid artificial intelligence (AI) approaches for gas turbine intelligent digital twins, with an emphasis on models that integrate physics-based simulations and machine learning. The main contribution is the introduction of a structured classification of hybrid AI methods tailored to gas turbine applications, the development of a novel comparative maturity framework, and the proposal of a layered roadmap for integration. The classification organizes hybrid AI approaches into four categories: (1) artificial neural network (ANN)-augmented thermodynamic models, (2) physics-integrated operational architectures, (3) physics-constrained neural networks (PcNNs) with computational fluid dynamics (CFD) surrogates, and (4) generative and model discovery approaches. The maturity framework evaluates these categories across five criteria: data dependency, interpretability, deployment complexity, workflow integration, and real-time capability. Industrial case studies—including General Electric (GE) Vernova’s SmartSignal, Siemens’ Autonomous Turbine Operation and Maintenance (ATOM), and the Electric Power Research Institute (EPRI) turbine digital twin—illustrate applications in real-time diagnostics, predictive maintenance, and performance optimization. Together, the classification and maturity framework provide the means for systematic assessment of hybrid AI methods in gas turbine intelligent digital twins. The review concludes by identifying key challenges and outlining a roadmap for the future development of scalable, interpretable, and operationally robust intelligent digital twins for gas turbines. Full article

(This article belongs to the Special Issue AI-Driven Innovations in Turbomachinery Flow Modeling and Design Optimization)

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22 pages, 3030 KB

Open AccessArticle

Energy and Environmental Impacts of Replacing Gasoline with LPG Under Real Driving Conditions

by Edward Kozłowski, Alfredas Rimkus, Magdalena Zimakowska-Laskowska, Jonas Matijošius, Piotr Wiśniowski, Mateusz Traczyński, Piotr Laskowski and Radovan Madlenak

Energies 2025, 18(20), 5522; https://doi.org/10.3390/en18205522 - 20 Oct 2025

Viewed by 466

Abstract

This study investigates the energy and environmental implications of replacing E10 gasoline with Liquefied Petroleum Gas (LPG) in a Euro 4 passenger car under real-world urban driving conditions. A comparative methodology robust to operating-state distribution was applied, combining portable exhaust gas analysis with [...] Read more.

This study investigates the energy and environmental implications of replacing E10 gasoline with Liquefied Petroleum Gas (LPG) in a Euro 4 passenger car under real-world urban driving conditions. A comparative methodology robust to operating-state distribution was applied, combining portable exhaust gas analysis with on-board diagnostic data to calculate energy-specific emissions per crankshaft revolution and to reconstruct emission surfaces in the load–RPM domain using bilinear interpolation. The study revealed that LPG reduces carbon dioxide emissions by 8.35%, demonstrating a clear climate and energy benefit due to its lower carbon intensity. In comparison, carbon monoxide (+9.5%) and hydrocarbons (+8.3%) increased under low-load and idle conditions. Nitrogen oxides showed only minor differences between the fuels (+1.3%). LPG exhibited a more stable CO₂ emission profile, reflecting improved combustion efficiency from an energy perspective, although its performance in terms of incomplete combustion products requires further optimisation. The methodology highlights how linking energy efficiency with pollutant formation provides a comprehensive framework for evaluating alternative fuels in Real Driving Emissions (RDE) tests. The results confirm LPG’s potential to reduce greenhouse gas emissions in transport systems and identify calibration strategies needed to mitigate trade-offs in local pollutant emissions. Full article

(This article belongs to the Special Issue Performance and Emissions of Vehicles and Internal Combustion Engines)

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