Energies

15 pages, 2920 KiB

Open AccessArticle

Battery Health Diagnosis via Neural Surrogate Model: From Lab to Field

by Hojin Cheon, Jihun Jeon, Byungil Jung and Hongseok Kim

Energies 2025, 18(9), 2405; https://doi.org/10.3390/en18092405 - 7 May 2025

Batteries degrade over time. Such degradation leads to performance loss, but more importantly, safety issues arise. To evaluate the battery degradation, traditional diagnostic techniques rely on model-based or data-driven approaches; however, those methods often require controlled conditions or specific tests, which may not [...] Read more.

Batteries degrade over time. Such degradation leads to performance loss, but more importantly, safety issues arise. To evaluate the battery degradation, traditional diagnostic techniques rely on model-based or data-driven approaches; however, those methods often require controlled conditions or specific tests, which may not be applicable in real fields. In this regard, we propose a deep learning-based method addressing these limitations by accurately modeling batteries using real-world operational data from photovoltaic (PV)-integrated battery energy storage system (BESSs), where charging currents vary dynamically and SOC is capped at 70% by regulation. The proposed method is based on a neural surrogate model for batteries, employing a sequence-to-sequence architecture, which directly captures the dynamic behavior of batteries from operational data, eliminating the need for specialized characterization tests or feature extraction. The proposed model synthesizes the terminal voltage with a mean absolute error of 6.4 mV for lithium–iron–phosphate (LFP) cells and 49 mV for nickel–cobalt–manganese (NCM) battery modules, respectively, which is only 0.4% and 0.29% of the voltage swing. As a health indicator, we also propose the concept of voltage deviation (VD), defined as the deviation between the synthesized and actual terminal voltages. We demonstrate that VD can be evaluated not only in laboratory data but also in field data. Full article

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

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20 pages, 8835 KiB

Open AccessArticle

Integrating Laboratory-Measured Contact Angles into Time-Dependent Wettability-Adjusted LBM Simulations for Oil–Water Relative Permeability

by Chenglin Liu, Changwei Sun, Ling Dai, Guanqun Wang, Haipeng Shao, Wei Li and Wei Long

Energies 2025, 18(9), 2404; https://doi.org/10.3390/en18092404 - 7 May 2025

Abstract

Oil–water relative permeability is essential for reservoir development and enhanced oil recovery (EOR). Traditional core displacement experiments assume static wettability, whereas in real reservoirs, wettability evolves over time due to waterflooding and rock–fluid interactions, significantly altering flow behavior. Existing numerical methods, including conventional [...] Read more.

Oil–water relative permeability is essential for reservoir development and enhanced oil recovery (EOR). Traditional core displacement experiments assume static wettability, whereas in real reservoirs, wettability evolves over time due to waterflooding and rock–fluid interactions, significantly altering flow behavior. Existing numerical methods, including conventional lattice Boltzmann models (LBM), fail to account for these changes and lead to inaccurate predictions. This study integrates laboratory-measured contact angles into a time-dependent wettability-adjusted LBM framework, ensuring real-time wettability updates during simulation. Micro-CT imaging captures oil–water displacement and contact angle evolution at different flooding stages, which are incorporated into the Shan–Chen LBM model. Results show that neglecting the time-dependent wettability overestimates the residual oil saturation and underestimates the water-phase permeability. In contrast, our method reduces the residual oil saturation by up to 35% and expands the two-phase flow region by 15%, aligning closely with experimental observations. This approach enhances the accuracy of relative permeability modeling, providing a more reliable tool for optimizing waterflooding strategies and improving oil recovery efficiency. Full article

(This article belongs to the Special Issue Unconventional Hydrocarbon Resources: Innovations in Occurrence, Exploration and Production)

24 pages, 7107 KiB

Open AccessArticle

A Synergistic Planning Framework for Low-Carbon Power Systems: Integrating Coal-Fired Power Plant Retrofitting with a Carbon and Green Certificate Market Coupling Mechanism

by Zifan Tang, Yue Yin, Chao Chen, Changle Liu, Zhuoxun Li and Benyao Shi

Energies 2025, 18(9), 2403; https://doi.org/10.3390/en18092403 - 7 May 2025

Abstract

The intensifying impacts of climate change induced by carbon emissions necessitate the implementation of urgent mitigation strategies. Given that the power sector is a major contributor to global carbon emissions, strategic decarbonization planning in this sector is of paramount importance. This study proposes [...] Read more.

The intensifying impacts of climate change induced by carbon emissions necessitate the implementation of urgent mitigation strategies. Given that the power sector is a major contributor to global carbon emissions, strategic decarbonization planning in this sector is of paramount importance. This study proposes a synergistic planning framework for low-carbon power systems that integrates coal-fired power plants (CFPPs) and a carbon and green certificate market coupling mechanism, thereby facilitating a “security–economic–low-carbon” tri-objective transition in power systems. The proposed framework facilitates dynamic decision-making regarding the retrofitting of CFPPs, investments in renewable energy resources, and energy storage systems. By evaluating three distinct CFPP retrofitting pathways, the framework enhances economic efficiency and reduces carbon emissions, achieving reductions of 28.67% in total system costs and 2.96% in CO₂ emissions. Implementing the carbon–green certificate market coupling mechanism further unlocks the market value of green certificates, thereby providing economic incentives for clean energy projects and increasing flexibility in the allocation of carbon emission quotas for enterprises. Relative to cases that consider only carbon trading or only green certificate markets, the coupled mechanism reduces the total cost by 10.96% and 15.56%, and decreases carbon emissions by 27.10% and 47.36%, respectively. The collaborative planning framework introduced in this study enhances economic performance, increases renewable energy penetration, and reduces carbon emissions, thus facilitating the low-carbon transition of power systems. Full article

(This article belongs to the Special Issue New Power System Planning and Scheduling)

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30 pages, 1946 KiB

Open AccessArticle

Energy Potential of Zea mays Grown in Cadmium-Contaminated Soil

by Agata Borowik, Jadwiga Wyszkowska, Magdalena Zaborowska and Jan Kucharski

Energies 2025, 18(9), 2402; https://doi.org/10.3390/en18092402 - 7 May 2025

Abstract

Cadmium is a non-essential element for proper plant growth and development and is highly toxic to humans and animals, in part because it inters with calcium-dependent processes in living organisms. For this reason, a study was conducted to assess the potential for producing [...] Read more.

Cadmium is a non-essential element for proper plant growth and development and is highly toxic to humans and animals, in part because it inters with calcium-dependent processes in living organisms. For this reason, a study was conducted to assess the potential for producing maize (Zea mays) biomass in cadmium-contaminated soil for energy purposes. The energy potential of Zea mays was evaluated by determining the heat of combustion (Q), heating value (Hv), and the amount of energy produced from the biomass. Starch, compost, fermented bark, humic acids, molecular sieve, zeolite, sepiolite, expanded clay, and calcium carbonate were assessed as substances supporting biomass production from Zea mays. The accumulation and redistribution of cadmium in the plant were also investigated. The study was conducted in a vegetation hall as part of a pot experiment. Zea mays was grown in uncontaminated soil and in soil contaminated with 15 mg Cd²⁺ kg⁻¹. A strong toxic effect of cadmium on the cultivated plants was observed, causing a 62% reduction in the biomass of aerial parts and 61% in the roots. However, it did not alter the heat of combustion and heating value of the aerial part biomass, which were 18.55 and 14.98 MJ kg⁻¹ d.m., respectively. Of the nine substances tested to support biomass production, only four (molecular sieve, compost, HumiAgra, and expanded clay) increased the yield of Zea mays grown in cadmium-contaminated soil. The molecular sieve increased aerial part biomass production by 74%, compost by 67%, expanded clay by 19%, and HumiAgra by 15%, but none of these substances completely eliminated the toxic effects of cadmium on the plant. At the same time, the bioaccumulation factor (BAF) of cadmium was higher in the roots (0.21–0.23) than in the aerial parts (0.04–0.03), with the roots showing greater bioaccumulation. Full article

(This article belongs to the Special Issue Sustainable Energy Development in Liquid Waste and Biomass: 2nd Edition)

17 pages, 2364 KiB

Open AccessArticle

Battery Health Prediction with Singular Spectrum Analysis and Grey Wolf Optimized Long Short-Term Memory Networks

by Chengti Huang, Na Li, Jianqing Zhu and Shengming Shi

Energies 2025, 18(9), 2401; https://doi.org/10.3390/en18092401 - 7 May 2025

Abstract

To tackle the intricate challenges of nonlinearity and non-stationarity in lead-acid battery degradation data, this paper introduces the SG-LSTM model, an innovative approach to battery health prediction. This model uniquely integrates Singular Spectrum Analysis (SSA) and Grey Wolf Optimization (GWO) with Long Short-Term [...] Read more.

To tackle the intricate challenges of nonlinearity and non-stationarity in lead-acid battery degradation data, this paper introduces the SG-LSTM model, an innovative approach to battery health prediction. This model uniquely integrates Singular Spectrum Analysis (SSA) and Grey Wolf Optimization (GWO) with Long Short-Term Memory (LSTM) networks, forming a sophisticated predictive framework. By targeting key degradation features, such as the charging time of multiple voltage rise segments from the charging curve, the model effectively captures critical battery health dynamics. SSA plays a vital role by filtering outliers from these feature sequences, ensuring high-quality data for analysis and enhancing the robustness and accuracy of predictions. The refined data are then processed by a GWO-optimized LSTM network, where GWO’s bio-inspired optimization fine-tunes the LSTM parameters for optimal performance. Experimental results demonstrate that the SG-LSTM model outperforms existing models in prediction accuracy and stability; specifically, SG-LSTM achieves 0.27 RMSE, outperforming LSTM (0.84), SSA-LSTM (0.4), and SSA-BP (0.6). Full article

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30 pages, 12182 KiB

Open AccessArticle

Electromagnetic Investigation of Innovative Stator–Permanent Magnet Motors

by Mohammad Reza Sarshar, Mohammad Amin Jalali Kondelaji, Pedram Asef and Mojtaba Mirsalim

Energies 2025, 18(9), 2400; https://doi.org/10.3390/en18092400 - 7 May 2025

Abstract

Owing to the distinct advantages of stator–permanent magnet (PM) motors over other PM machines, their prominence in high-power-density applications is surging dramatically, capturing growing interest across diverse applications. This article proposes an innovative design procedure for two primary stator–PM motor types, flux switching [...] Read more.

Owing to the distinct advantages of stator–permanent magnet (PM) motors over other PM machines, their prominence in high-power-density applications is surging dramatically, capturing growing interest across diverse applications. This article proposes an innovative design procedure for two primary stator–PM motor types, flux switching and biased flux, yielding 30 novel motor designs. The procedure involves splitting teeth, incorporating a flux reversal effect, and embedding flux barriers into the conventional structure. The analytical reasons behind the novel motors’ architecture are mathematically expressed and verified using finite element analysis (FEA). Through an effective optimisation based on a multi-objective genetic algorithm, various feasible stator/rotor pole combinations are explored, with over 36,000 samples evaluated using FEA coupled with the algorithm. The electromagnetic characteristics of promising motors are analysed, revealing that adding the flux reversal effect and flux barriers, which reduce PM volume while decreasing leakage flux and enhancing air gap flux, improves torque production by up to 68%. Beyond torque enhancement, other electromagnetic parameters, including torque ripple, core loss, and the power factor, are also improved. The proposed motors enhance the PM torque density significantly by about 115% compared to conventional motors and reduce the motor costs. A generalised decision-making process and thermal analysis are applied to the top-performing motors. Additionally, the prototyping measures and considerations are thoroughly discussed. Finally, a comprehensive conclusion is reached. Full article

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56 pages, 9312 KiB

Open AccessReview

Advancing Electrochemical Energy Storage: A Review of Electrospinning Factors and Their Impact

by Muhammad Kashif, Sadia Rasul, Mohamedazeem M. Mohideen and Yong Liu

Energies 2025, 18(9), 2399; https://doi.org/10.3390/en18092399 - 7 May 2025

Abstract

The imperative for sustainable energy has driven the demand for efficient energy storage systems that can harness renewable resources and store surplus energy for off-peak usage. Among the numerous advancements in energy storage technology, polymeric nanofibers have emerged as promising nanomaterials, offering high [...] Read more.

The imperative for sustainable energy has driven the demand for efficient energy storage systems that can harness renewable resources and store surplus energy for off-peak usage. Among the numerous advancements in energy storage technology, polymeric nanofibers have emerged as promising nanomaterials, offering high specific surface areas that facilitate increased charge storage and enhanced energy density, thereby improving electrochemical performance. This review delves into the pivotal role of nanofibers in determining the optimal functionality of energy storage systems. Electrospinning emerged as a facile and cost-effective method for generating nanofibers with customizable nanostructures, making it attractive for energy storage applications. Our comprehensive review article examines the latest developments in electrospun nanofibers for electrochemical storage devices, highlighting their use as separators and electrode materials. We provide an in-depth analysis of their application in various battery technologies, including supercapacitors, lithium-ion batteries, sodium-ion batteries, potassium-ion batteries, lithium–sulfur batteries, and lithium–oxygen batteries, with a focus on their electrochemical performance. Furthermore, we summarize the diverse fabrication techniques, optimization of key influencing factors, and environmental implications of nanofiber production and their properties. This review aims to offer an inclusive understanding of electrospinning’s role in advancing electrochemical energy storage, providing insights into the factors that drive the performance of these critical materials. Full article

(This article belongs to the Special Issue Research on Advanced Energy Materials for Meeting Global Energy Challenges)

17 pages, 3398 KiB

Open AccessArticle

Multilayer Gas-Bearing System and Productivity Characteristics in Carboniferous–Permian Tight Sandstones: Taking the Daning–Jixian Block, Eastern Ordos Basin, as an Example

by Ming Chen, Bo Wang, Haonian Tian, Junyi Sun, Lei Liu, Xing Liang, Benliang Chen, Baoshi Yu and Zhuo Zhang

Energies 2025, 18(9), 2398; https://doi.org/10.3390/en18092398 - 7 May 2025

Abstract

The Carboniferous–Permian strata in the Daning–Jixian Block, located on the eastern edge of the Ordos Basin, host multiple sets of tight gas reservoirs. However, systematic research on the characteristics and gas production differences of multilayer tight sandstone gas-bearing systems remains limited. Based on [...] Read more.

The Carboniferous–Permian strata in the Daning–Jixian Block, located on the eastern edge of the Ordos Basin, host multiple sets of tight gas reservoirs. However, systematic research on the characteristics and gas production differences of multilayer tight sandstone gas-bearing systems remains limited. Based on geochemical signatures, reservoir pressure coefficients, and sequence stratigraphy, the tight sandstone gas systems are subdivided into upper and lower systems, separated by regionally extensive Taiyuan Formation limestone. The upper system is further partitioned into four subsystems. Depositional variability from the Benxi Formation to the He 8 Member has generated diverse litho-mineralogical characteristics. The Shan 1 and He 8 Members, deposited in low-energy delta-front subaqueous distributary channels with gentle topography, exhibit lower quartz content (predominantly feldspar lithic sandstone and lithic quartz sand-stone) and elevated lithic fragments, matrix, and clay minerals (particularly chlorite). These factors increase displacement and median pressures, resulting in inferior reservoir quality. By comparing and evaluating the gas production effects under different extraction methods, targeted optimization recommendations are provided to offer both theoretical support and practical guidance for the efficient development of this block. Full article

(This article belongs to the Special Issue Exploration and Development of Unconventional Oil and Gas Resources: Latest Advances and Prospects: 3rd Edition)

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20 pages, 4956 KiB

Open AccessArticle

Unbalanced Magnetic Pull Calculation in Ironless Axial Flux Motors

by Guoqing Zhu and Jian Luo

Energies 2025, 18(9), 2397; https://doi.org/10.3390/en18092397 - 7 May 2025

Abstract

Axial flux motors have gained widespread attention in the field of electric vehicles. The stator may exert a unilateral axial force on the dual rotors under uneven air gaps. The unbalanced magnetic pull can influence the production and processing of the motor, leading [...] Read more.

Axial flux motors have gained widespread attention in the field of electric vehicles. The stator may exert a unilateral axial force on the dual rotors under uneven air gaps. The unbalanced magnetic pull can influence the production and processing of the motor, leading to issues such as vibrations, bearing degradation, reduced lifespan, and torque reduction attributed to the bearings. Accurate evaluation of the unilateral magnetic pull can reduce costs associated with bearing protection. For dual-rotor motors, the axial forces of the rotors act in opposite directions with nearly equal magnitudes, resulting in the catastrophic cancellation of unbalanced magnetic pull calculations. A similar phenomenon may occur between coils, introducing computational errors. To avoid these errors, the stator was selected as the computational target for unilateral axial force calculations. The integration domain was defined to encompass the entire air region containing all windings, rather than summing individual force components. This merged integration approach was mathematically validated through the Maxwell stress tensor method. Finally, the obtained stator axial force closely matched the rotor axial force in magnitude, demonstrating the accuracy of the proposed method. Full article

(This article belongs to the Section E: Electric Vehicles)

18 pages, 393 KiB

Open AccessArticle

Research on Resource Utilization of Bi-Level Non-Cooperative Game Systems Based on Unit Resource Return

by Bo Fu, Peiwen Li and Yi Quan

Energies 2025, 18(9), 2396; https://doi.org/10.3390/en18092396 - 7 May 2025

Abstract

In a competitive market, due to differences in the nature of various power generation entities, there is a decline in resource utilization and difficulties in ensuring a return on investment for generating units within the system. A bi-level non-cooperative game model based on [...] Read more.

In a competitive market, due to differences in the nature of various power generation entities, there is a decline in resource utilization and difficulties in ensuring a return on investment for generating units within the system. A bi-level non-cooperative game model based on the Unit Resource Return (URR) is proposed to safeguard the interests and demands of each power generation unit while improving the overall resource utilization rate of the system. Firstly, we construct a comprehensive energy-trading framework for the overall system and analyze the relationship between the Independent System Operator (ISO) and the generation units. Secondly, we propose the Unit Resource Return (URR), inspired by the concept of input-output efficiency in economics. URR evaluates the return on unit resource input by taking the maximum generation potential of each unit as the benchmark. Finally, a bi-level non-cooperative game model is established. In the lower-level non-cooperative game, the generating units safeguard their own interests, while in the upper-level, the ISO adjusts the output allocation and engages in a master–slave game between generating units to ensure the overall operational efficiency of the system. URR is adopted as the ISO’s price-clearing equilibrium criterion, enabling the optimization of both resource profitability and allocation. Ultimately, both the upper and lower-level decision variables reach a Nash equilibrium. The experimental results show that the bi-level non-cooperative game model based on the Unit Resource Return improves the overall resource utilization of the system and enhances the long-term operational motivation of the generating units. Full article

30 pages, 3662 KiB

Open AccessArticle

Analysis and Diagnosis of the Stator Turn-to-Turn Short-Circuit Faults in Wound-Rotor Synchronous Generators

by Haotian Mao, Khashayar Khorasani and Yingqing Guo

Energies 2025, 18(9), 2395; https://doi.org/10.3390/en18092395 - 7 May 2025

Abstract

In this paper, we introduce a health parameter and estimation algorithm to assess the severity of stator turn-to-turn/inter-turn short-circuit (TTSC) faults in wound-rotor synchronous generators (WRSG). Our methodology establishes criteria for evaluating the severity of stator TTSC faults in WRSG and provides a [...] Read more.

In this paper, we introduce a health parameter and estimation algorithm to assess the severity of stator turn-to-turn/inter-turn short-circuit (TTSC) faults in wound-rotor synchronous generators (WRSG). Our methodology establishes criteria for evaluating the severity of stator TTSC faults in WRSG and provides a specific solution for estimating both the severity of these faults and the resultant power loss. Our assessment methodology directly reflects the intrinsic impact of stator TTSC faults on the WRSG, offering enhanced efficiency, accuracy, and resilience to interference compared with traditional methods in estimating and gauging the TTSC severity. First, we demonstrate that it is impossible to determine the two fault parameters of the WRSG stator TTSC faults solely based on the voltage and current measurements. Subsequently, we introduce a novel health parameter for the WRSG stator TTSC faults and show that for a given generator and load, the dynamics of voltage and current during these faults as well as the resulting power loss are determined by this health parameter. We then detail the characteristics of the proposed health parameter and criteria for evaluating the severity of the WRSG stator TTSC faults. Furthermore, we present an estimation algorithm that is capable of accurately estimating the health parameter and power loss, demonstrating its minimal estimation error. Finally, we provide a comprehensive set of simulation results, including Monte Carlo results, to validate our proposed methodology and illustrate that our approach offers significant improvements in terms of the efficiency, accuracy, and robustness of the WRSG stator TTSC fault detection and isolation (FDI) over conventional methods. Full article

17 pages, 914 KiB

Open AccessArticle

Robust Assessment Method for Hosting Capacity of Distribution Network in Mountainous Areas for Distributed Photovoltaics

by Youzhuo Zheng, Kun Zhou, Yekui Yang, Hanbin Diao, Long Hua, Renzhi Wang, Kang Liu and Qi Guo

Energies 2025, 18(9), 2394; https://doi.org/10.3390/en18092394 - 7 May 2025

Abstract

The penetration rate of distributed photovoltaic (PV) in mountainous distribution networks is increasing year by year, and the assessment of distributed PV hosting capacity (PVHC) in distribution networks in mountainous areas is also becoming more and more important. To this end, this paper [...] Read more.

The penetration rate of distributed photovoltaic (PV) in mountainous distribution networks is increasing year by year, and the assessment of distributed PV hosting capacity (PVHC) in distribution networks in mountainous areas is also becoming more and more important. To this end, this paper proposes a robust assessment method for distributed PVHC of flexible distribution networks in mountainous areas. The method utilizes soft open point (SOP) and energy storage to realize the flexible interconnection of distribution networks in mountainous areas, connecting the low-voltage nodes at the end of distribution networks in mountainous areas and improving the overall power quality of distribution networks. Secondly, the output curves of distributed PV output and load demand are analyzed and the distributed PV uncertainty model is drawn, so as to construct a two-layer robust assessment model of distributed PVHC for mountainous flexible distribution networks. Finally, the dual-layer robust assessment model, which cannot be solved directly, is transformed into a solvable mixed-integer linear programming model using the pairwise method, and the effectiveness of this paper’s method is verified by the simulation results of the IEEE 33-node distribution network system. Full article

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

27 pages, 1069 KiB

Open AccessReview

Recent Advances in Electrified Methane Pyrolysis Technologies for Turquoise Hydrogen Production

by Hossein Rohani, Galina Sudiiarova, Stephen Matthew Lyth and Arash Badakhsh

Energies 2025, 18(9), 2393; https://doi.org/10.3390/en18092393 - 7 May 2025

Abstract

The global campaign to reach net zero will necessitate the use of hydrogen as an efficient way to store renewable electricity at large scale. Methane pyrolysis is rapidly gaining traction as an enabling technology to produce low-cost hydrogen without directly emitting carbon dioxide. [...] Read more.

The global campaign to reach net zero will necessitate the use of hydrogen as an efficient way to store renewable electricity at large scale. Methane pyrolysis is rapidly gaining traction as an enabling technology to produce low-cost hydrogen without directly emitting carbon dioxide. It offers a scalable and sustainable alternative to steam reforming whilst being compatible with existing infrastructure. The process most commonly uses thermal energy to decompose methane (CH₄) into hydrogen gas (H₂) and solid carbon (C). The electrification of this reaction is of great significance, allowing it to be driven by excess renewable electricity rather than fossil fuels, and eliminating indirect emissions. This review discusses the most recent technological advances in electrified methane pyrolysis and the relative merits of the mainstream reactor technologies in this space (plasma, microwave, fluidised bed, and direct resistive heating). This study also examines the economic viability of the process, considering energy costs, and the market potential of both turquoise hydrogen and solid carbon products. Whilst these technologies offer emission-free hydrogen production, challenges such as carbon deposition, reactor stability, and high energy consumption must be addressed for large-scale adoption. Future research should focus on process optimisation, advanced reactor designs, and policy frameworks to support commercialisation. With continued technological innovation and sufficient investment, electrified methane pyrolysis has the potential to become the primary route for sustainable production of hydrogen at industrial scale. Full article

(This article belongs to the Section A5: Hydrogen Energy)

19 pages, 3200 KiB

Open AccessArticle

Effects of Ethanol–Diesel Blends on Cylinder Pressure, Ignition Delay, and NO_x Emissions in a Diesel Engine

by Krzysztof Górski, Dimitrios Tziourtzioumis, Ruslans Smigins and Rafał Longwic

Energies 2025, 18(9), 2392; https://doi.org/10.3390/en18092392 - 7 May 2025

Abstract

This study examined how adding ethanol to diesel fuel affects combustion characteristics, cylinder pressure and NO_x emissions in an AVL engine. The research focused on key engine parameters, including autoignition delay, in-cylinder pressure rise rates, the peaks of the mean in-cylinder temperature [...] Read more.

This study examined how adding ethanol to diesel fuel affects combustion characteristics, cylinder pressure and NO_x emissions in an AVL engine. The research focused on key engine parameters, including autoignition delay, in-cylinder pressure rise rates, the peaks of the mean in-cylinder temperature and NO_x emissions. Three fuel types were tested: pure diesel (DF) and blends with 10 and 20% ethanol by volume (DF10 and DF20). The results obtained indicate that increasing the ethanol content in diesel fuel significantly affects the combustion process of the fuel mixture, particularly in its early stage, reducing the benefits of the pilot fuel injection. Moreover, it was observed that the combustion of the DF20 mixture leads to a substantially higher pressure increase in the cylinder, exceeding the values recorded for pure diesel fuel by approximately 25%. Furthermore, the study revealed that ethanol addition increases the peaks of the mean in-cylinder temperature, with a recorded difference of up to 60 °C between pure diesel fuel and DF20. Since NO_x formation is highly temperature-dependent, this temperature rise is likely to result in higher NO_x concentration. Additionally, a slight effect of ethanol on increasing the ignition delay angle was observed. This remained minor, and did not exceed approximately 1 CA. These findings highlight the complex relationship between ethanol content in diesel fuel, combustion dynamics, and emissions. They emphasize the need for optimizing the injection process for ethanol–diesel blends to balance the benefits of ethanol addition with potential challenges related to combustion efficiency, engine load and NO_x concentration. Full article

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

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24 pages, 8094 KiB

Open AccessArticle

Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing

by Damir Jakus, Joško Novaković, Josip Vasilj and Danijel Jolevski

Energies 2025, 18(9), 2391; https://doi.org/10.3390/en18092391 - 7 May 2025

Abstract

The integration of renewable energy sources, particularly solar photovoltaics, into household power supply has become increasingly popular due to its potential to reduce energy costs and environmental impact. However, solar power variability and new regulative changes concerning excess solar energy compensation schemes call [...] Read more.

The integration of renewable energy sources, particularly solar photovoltaics, into household power supply has become increasingly popular due to its potential to reduce energy costs and environmental impact. However, solar power variability and new regulative changes concerning excess solar energy compensation schemes call for effective energy storage management and sizing to ensure a stable and profitable electricity supply. This paper focuses on optimizing residential battery storage systems under different electricity pricing schemes such as time-of-use tariffs, dynamic pricing, and different excess solar energy compensation schemes. The central question addressed is how different pricing mechanisms and compensation strategies for excess solar energy, as well as varying battery storage investment costs, determine the optimal sizing of battery storage systems. A comprehensive mixed-integer linear programming model is developed to analyze these factors, incorporating various financial and operational parameters. The model is applied to a residential case study in Croatia, examining the impact of monthly net metering/billing, 15 min net billing, and dynamic pricing on optimal battery storage sizing and economic viability. Full article

(This article belongs to the Special Issue Novel Energy Management Approaches in Microgrid Systems)

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17 pages, 3971 KiB

Open AccessArticle

Condensation Heat Transfer Efficiency Analysis of Horizontal Double-Sided Enhanced Tubes

by Jianghui Zhang, Junjie Wu, He Zhou, Jiaxiang Yu, Bin Zhang, Wei Li and Yan He

Energies 2025, 18(9), 2390; https://doi.org/10.3390/en18092390 - 7 May 2025

Abstract

The enhanced tubes in this study, referred to as E1 and E2, represent significant improvements in the design and performance of smooth tubes. By increasing the surface area on their fin side and optimizing the condensation drainage design, the heat transfer capacity of [...] Read more.

The enhanced tubes in this study, referred to as E1 and E2, represent significant improvements in the design and performance of smooth tubes. By increasing the surface area on their fin side and optimizing the condensation drainage design, the heat transfer capacity of the finned tubes has been further enhanced. These modifications will provide superior thermal management performance for condenser tubes in practical applications, facilitating their widespread use across various engineering fields. In this experiment, R134a was used as the working fluid, with a test section length (L) of 248 mm for the experimental tubes E1 and E2. The experiments were conducted at a saturation temperature of 40 °C, where the refrigerant condensed outside the tube while deionized water circulated inside. The results indicated that, at a heat flux density below 94 kW/m², the condensation heat transfer coefficient of the E1 tube was 2–5% higher than that of the E2 tube, achieving values that were 11.63–14.42 times and 10.94–14.67 times that of smooth tubes of identical dimensions and materials, respectively. At a heat flux density of 94 kW/m², the heat transfer coefficient of E2 exceeded that of E1, with E1 exhibiting a more pronounced decline. Under constant water velocity, the heat transfer coefficient outside the tube initially decreased and then increased as the heat flux density rose. The corresponding effective heat transfer area of E1 increased, leading to better overall heat transfer performance compared to E2. Full article

(This article belongs to the Topic Advanced Heat and Mass Transfer Technologies)

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15 pages, 2504 KiB

Open AccessCommunication

From Climate Risks to Resilient Energy Systems: Addressing the Implications of Climate Change on Indonesia’s Energy Policy

by Agus Setiawan, Dea Mardha Mentari, Dzikri Firmansyah Hakam and Risa Saraswani

Energies 2025, 18(9), 2389; https://doi.org/10.3390/en18092389 - 7 May 2025

Abstract

Climate change has presented significant challenges to Indonesia’s energy sector, increasing vulnerabilities in power generation, infrastructure resilience, and energy security. Rising sea levels, extreme weather events, and increasing temperatures disrupt energy systems, highlighting the urgent need to build resilient energy systems. To support [...] Read more.

Climate change has presented significant challenges to Indonesia’s energy sector, increasing vulnerabilities in power generation, infrastructure resilience, and energy security. Rising sea levels, extreme weather events, and increasing temperatures disrupt energy systems, highlighting the urgent need to build resilient energy systems. To support Indonesia’s energy transition, this study addresses a critical gap by providing an integrated analysis of climate resilience, renewable energy policies, and Indonesia’s socio-economic and environmental goals, emphasizing the importance of enabling policies and financial mechanisms. The recommendations mentioned in this study include increasing renewable energy capacity through solar and geothermal projects, modernizing infrastructure to enhance resilience, and adopting decentralized energy systems to reduce dependency on centralized networks. Strengthened governance and stakeholder collaboration are also essential for the successful implementation of energy policies. This study underscores the importance of having comprehensive energy policies to address climate change, promote sustainable development, and help Indonesia achieve its renewable energy targets and long-term goal of net-zero emissions. Full article

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

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18 pages, 18892 KiB

Open AccessArticle

A Bidding Strategy for Power Suppliers Based on Multi-Agent Reinforcement Learning in Carbon–Electricity–Coal Coupling Market

by Zhiwei Liao, Chengjin Li, Xiang Zhang, Qiyun Hu and Bowen Wang

Energies 2025, 18(9), 2388; https://doi.org/10.3390/en18092388 - 7 May 2025

Abstract

The deepening operation of the carbon emission trading market has reshaped the cost–benefit structure of the power generation side. In the process of participating in the market quotation, power suppliers not only need to calculate the conventional power generation cost but also need [...] Read more.

The deepening operation of the carbon emission trading market has reshaped the cost–benefit structure of the power generation side. In the process of participating in the market quotation, power suppliers not only need to calculate the conventional power generation cost but also need to coordinate the superimposed impact of carbon quota accounting on operating income, which causes the power suppliers a multi-time-scale decision-making collaborative optimization problem under the interaction of the carbon market, power market, and coal market. This paper focuses on the multi-market-coupling decision optimization problem of thermal power suppliers. It proposes a collaborative bidding decision framework based on a multi-agent deep deterministic policy gradient (MADDPG). Firstly, aiming at the time-scale difference of multi-sided market decision making, a decision-making cycle coordination scheme for the carbon–electricity–coal coupling market is proposed. Secondly, upper and lower optimization models for the bidding decision making of power suppliers are constructed. Then, based on the MADDPG algorithm, the multi-generator bidding scenario is simulated to solve the optimal multi-generator bidding strategy in the carbon–electricity–coal coupling market. Finally, the multi-scenario simulation based on the IEEE-5 node system shows that the model can effectively analyze the differential influence of a multi-market structure on the bidding strategy of power suppliers, verifying the superiority of the algorithm in convergence speed and revenue optimization. Full article

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22 pages, 4226 KiB

Open AccessArticle

Analysis of the Possibility of Using CO₂ Capture in a Coal-Fired Power Plant

by Łukasz Mika and Karol Sztekler

Energies 2025, 18(9), 2387; https://doi.org/10.3390/en18092387 - 7 May 2025

Abstract

Global trends in environmental protection place emphasis on the reduction of CO₂ emissions, a key factor in the greenhouse effect. Commercial power generation, mainly based on coal, is the largest emitter of CO₂, which justifies work on its reduction. Technologies [...] Read more.

Global trends in environmental protection place emphasis on the reduction of CO₂ emissions, a key factor in the greenhouse effect. Commercial power generation, mainly based on coal, is the largest emitter of CO₂, which justifies work on its reduction. Technologies involving CO₂ capture from flue gases based on adsorption methods are not yet widely used, and therefore, there is a lack of complete data on their impact on power units. With the use of computer simulations, relevant information can be obtained, eliminating the need for costly tests on actual systems. A model of a reference power unit and CO₂ separation system based on adsorption methods was developed in the IPSEpro environment. Simulations were carried out, analysing the impact of parameters such as temperature and pressure of the flue gas and of bled steam on the efficiency of the separation system. Optimal adsorption and desorption conditions were determined, and the separation model was then integrated into a power unit. The analysis of CO₂ capture in power units indicates that while complete separation of CO₂ from the flue gas of an 830 MWe unit is technically feasible, it results in substantial efficiency losses and high energy consumption. Capturing and liquefying CO₂ leads to a power output reduction of approximately 358 MWe and a 15.4% decrease in efficiency. Simulation analyses allowed the impact of the CO₂ capture system on the operation of the unit to be assessed and the amount of non-emitted gas to be estimated, thus reducing the environmental harm of the power plant. Full article

(This article belongs to the Special Issue Carbon Capture Technologies for Sustainable Energy Production)

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