Energy Science & Engineering最新文献

{"title":"Synthesis and Evaluation of Ceramic-Anchored Cu-Ce-MnOx Catalyst for Low Temperature Reduction of Diesel Engine NOx Emissions Using Liquefied Petroleum Gas or Adblue as Reductants","authors":"Brian O. Obita,&nbsp;Simon Ngigi Mbugua,&nbsp;Clare I. Muhanji,&nbsp;Joseph O. Lalah","doi":"10.1002/ese3.70522","DOIUrl":"https://doi.org/10.1002/ese3.70522","url":null,"abstract":"<p>Manganese oxide-based catalyst doped with copper and cerium was synthesized through microwave irradiation and successfully anchored on a ceramic support. Fourier Transform Infrared Radiation study showed Mn-O bond at 529 cm⁻¹ while X-ray Fluorescence confirmed the availability of Cu, Ce and Mn in the ceramic matrix. Examination by SEM revealed active sites in addition to the catalyst aggregate particle size diameter as 707 mm. Energy Dispersive X-ray established the presence of copper, cerium and manganese after catalyst synthesis. Catalytic effect of Cu-Ce-MnO_x was studied using liquefied petroleum gas as the hydrocarbon reductant and performance comparison was made with NH₃, a commonly used reductant from AdBlue solution. Sulfur dioxide poisoning resistance, hydrothermal stability and low temperature activity (&lt; 50°C) were the critical parameters investigated by having Cu-Ce-MnO_x catalyst placed after the water-cooling unit. The parameters were optimized by testing Cu-Ce-MnO_x catalyst at 3, 6, and 9 kg engine loads to reflect the expected real driving NO_x emission reduction potential of the catalyst. NO_x reduction efficiency was 26% at 28°C for LPG-Cu-Ce-MnO_x and 60% at 29°C for NH₃-Cu-Ce-MnO_x. White biuret deposits were observed around the injection point due to low temperature decomposition of AdBlue solution. Biuret would lower the catalytic activity by clogging hence reduced number of catalyst active sites. This work successfully shows that this ceramic anchored Cu-Ce-MnO_x catalyst has a potential application at almost room temperature NO_x reduction. The anchored catalyst has the potential for integration in Diesel automobile exhaust, though it has a lower NO_x conversion efficiency with LPG, compared to the conventional AdBlue.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 7","pages":"3149-3161"},"PeriodicalIF":3.6,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70522","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148533315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Assessment and Benchmarking of Metaheuristic Algorithms for Dynamic Photovoltaic Array Reconfiguration Under Diverse Shading Environments","authors":"Manoharan Premkumar,&nbsp;Ravichandran Sowmya,&nbsp;Jagarapu S. V. Siva Kumar,&nbsp;Mustafa Abdullah","doi":"10.1002/ese3.70530","DOIUrl":"https://doi.org/10.1002/ese3.70530","url":null,"abstract":"<p>The solar photovoltaic (PV) installations, which are essential for renewable energy systems, are vulnerable to partial shading, resulting in considerable power losses and operational inefficiencies. The dynamic reconfiguration of PV arrays has become an effective strategy to mitigate these effects by adaptively modifying the array topology to optimize power output. This paper presents a detailed comparative analysis of dynamic PV array reconfigurations for a 6 × 6 total-cross-tied array under various operating conditions. The comparative analysis includes 10 recent metaheuristics that have shown performance in complex optimization problems across different domains. The proposed methodology assesses the effectiveness of each algorithm in identifying optimal reconfiguration patterns, enhancing power extraction, and reducing mismatch losses across both uniform and multiple partial shading conditions. Simulation results prove the strengths and robustness of each algorithm, providing detailed insights into their appropriateness for real-time adaptive PV systems. The findings clarify the potential of metaheuristic-driven dynamic reconfigurations to improve PV system performance and establish a basis for choosing the most effective algorithmic approach in practical applications.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 7","pages":"3272-3309"},"PeriodicalIF":3.6,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70530","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148522905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid Osprey-Salp Swarm Optimization Algorithm for Single and Multiobjective Optimal Power Flow in Smart Grids With Renewable Energy Integration","authors":"Mujtaba Ali,&nbsp;Muhammad Yaqoob Javed,&nbsp;Aamer Bilal Asghar,&nbsp;Gang Xiong,&nbsp;Krzysztof Ejsmont,&nbsp;Xiaoli Liu","doi":"10.1002/ese3.70536","DOIUrl":"https://doi.org/10.1002/ese3.70536","url":null,"abstract":"<p>The increasing integration of renewable energy sources into smart grids presents substantial challenges in solving the nonlinear and nonconvex optimal power flow (OPF) problem. This paper proposes a comprehensive OPF model that incorporates conventional thermal generators, solar photovoltaic generators, and hydroelectric power generators, while effectively addressing the uncertainties associated with renewable power generation. A lognormal probability distribution models solar irradiance variability in solar generators, while a Gumbel distribution captures water availability fluctuations in hydro generators. The paper proposes a novel hybrid optimization approach, hybrid osprey-salp swarm optimization (HOSSO), to solve this complex OPF problem. The HOSSO leverages the exploration–exploitation balance of Osprey Optimization alongside the adaptive leadership and follower dynamics of Salp Swarm Optimization. The proposed methodology is validated on Institute of Electrical and Electronics Engineers 30-, 57-, and 118-bus test systems across five distinct optimization scenarios: economic cost minimization, emission cost minimization, combined economic–environmental cost minimization, voltage deviation penalty cost minimization, and renewable generation uncertainty penalty cost minimization. The model incorporates reserve and penalty costs for renewable generation uncertainty and integrates carbon emission taxation to enhance grid reliability and sustainability. Comparative analysis against classical and hybrid optimization techniques demonstrates the superior performance of HOSSO across most test scenarios, consistently achieving competitive solutions while satisfying system constraints and stability requirements. The algorithm delivers improvements ranging from 0.4% to 17% in cost minimization, 3%–23% in voltage deviation minimization, and 2%–8% in uncertainty management over competing methods, with performance advantages becoming increasingly pronounced as system scale grows. The algorithm exhibits rapid convergence within 20–50 iterations, effectively avoids local optima, and proves well-suited for both single- and multiobjective OPF problems in renewable energy-integrated power systems. The results highlight HOSSO's potential for real-time power system applications and its adaptability to smart grids with high renewable energy penetration.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 7","pages":"3346-3387"},"PeriodicalIF":3.6,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70536","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technoeconomic Assessment of Wind Power Potential in the Vicinity of GolGohar Sirjan Mining and Industrial Company","authors":"Hossein Amiri","doi":"10.1002/ese3.70528","DOIUrl":"https://doi.org/10.1002/ese3.70528","url":null,"abstract":"<p>Wind energy is a central pillar of sustainable energy transition; however, its feasibility strongly depends on site-specific wind regimes and economic conditions. This study investigates the technical, environmental, and economic feasibility of developing a small-scale wind farm near GolGohar Sirjan Mining and Industrial Company, Sirjan, Kerman Province, Iran. Two complementary data sets were analyzed: measured meteorological data from the GolGohar station for the period 2020–2023 and long-term satellite-based data from the EMD International A/S-Weather Research and Forecasting model Middle-East model covering 1994–2019. Wind resource assessment and energy simulations were conducted using WindPRO software for 12 candidate locations, employing a Vestas V20 wind turbine with a rated capacity of 100 kW at a hub height of 60 m. Alongside the technical evaluation, environmental impacts including noise, visual disturbance, and shadow flicker were analyzed, and economic viability was assessed by calculating the levelized cost of energy (LCOE) with a sensitivity analysis on the discount rate. Results show generally low-wind conditions, with an overall average of 4.6 m/s at hub height, and site-specific wind classes ranging from Class 1 to Class 2. Chahmil Village (T5, Class 2) demonstrates the highest potential, producing 205.1 MWh/year with a 23.4% capacity factor (CF). Technical results show an average CF of 12.5% and an overall efficiency of 22.1%. Economic evaluation yields a baseline LCOE of 311.2 €/MWh, varying from 229.1 to 404.6 €/MWh depending on the discount rate. Environmental assessment indicates that turbine noise remains within acceptable limits (around 45 dB), while visual and shadow flicker impacts are manageable.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 7","pages":"3226-3249"},"PeriodicalIF":3.6,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70528","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148522906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Simplified Two-Vector Approach for Common-Mode Voltage Reduction in Model Predictive Control Drives of Permanent Magnet Synchronous Motor","authors":"Javad Amini,&nbsp;Reza Roshanafekr","doi":"10.1002/ese3.70571","DOIUrl":"https://doi.org/10.1002/ese3.70571","url":null,"abstract":"<p>In this study, a model predictive control (MPC) strategy is proposed for electrical drivers of the permanent magnet synchronous motors (PMSMs). The proposed method is designed not only to ensure optimal current and torque control but also to significantly reduce common-mode voltage (CMV). CMV is considered one of the main challenges in motor drive systems because it can lead to increased electromagnetic interference, bearing leakage currents, and a reduced lifetime of electrical and mechanical components. To address this issue, a simplified two-vector MPC method that applies two nonzero switching vectors at each sampling instant was developed. This approach was designed to improve stator current total harmonic distortion (THD) while reducing computational burden and system complexity. First, the three-phase two-level inverter and PMSM dynamics are modeled, and then an MPC controller is designed to simultaneously maintain high-quality current/torque control and reduce CMV. The effectiveness of the proposed simplified two-vector approach is validated through MATLAB/Simulink simulations and experimental implementation on a digital signal processor–based hardware platform. The experimental results confirm that the proposed simplified two-vector MPC method results 40% reduction of CMV and 25.5% reduction of stator current THD in comparison with the conventional MPC drive.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 7","pages":"3109-3117"},"PeriodicalIF":3.6,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70571","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization and Cost Evaluation of an Autonomous Hybrid Renewable Energy System for Electrifying Rural Areas in Nigeria","authors":"Ibrahim Seidu,&nbsp;Sani Salisu,&nbsp;Abdullahi Abubakar Mas'ud,&nbsp;Umar Musa,&nbsp;Ibrahim Abdullahi Shehu,&nbsp;Adamu Abubakar Sa'idu,&nbsp;Firdaus Muhammad-Sukki,&nbsp;Mohd Khairul Amri Kamarudin","doi":"10.1002/ese3.70532","DOIUrl":"https://doi.org/10.1002/ese3.70532","url":null,"abstract":"<p>Reliable and affordable electricity supply remains a challenge in rural communities where grid extension is technically and economically unattractive. This paper evaluates the techno-economic and environmental performance of hybrid renewable energy systems for rural electrification in Auchi, Edo State, Nigeria, with a daily load demand of 2255 kWh and a peak load of 213.53 kW. Three fully renewable configurations PV/WT/Battery, PV/Battery, and WT/Battery are analyzed under identical resource and economic conditions using HOMER Pro. Results show that the PV–WT–Battery configuration is the optimal solution, achieving a Cost of Energy (COE) of $0.0850/kWh, a Net Present Cost (NPC) of $904,122, and an initial capital cost of $502,690. The optimal system consists of 1177 kW PV, two wind turbines, 1,033 batteries, and a 198 kW converter, supplying 100% renewable electricity with zero CO₂ emissions. Excess electricity is 57.5%, while unmet load is limited to 0.0693%. Comparative analysis indicates higher costs for the WT/Battery system and higher excess generation for the PV/Battery system. The results show that the hybrid PV/WT/Battery system can provide reliable, cost-effective, and zero-emission electricity for rural electrification in Nigeria. Sensitivity analysis identifies solar irradiation and nominal discount rate as the most influential parameters affecting system economics.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 7","pages":"3310-3323"},"PeriodicalIF":3.6,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70532","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent Control Framework of District Heating Systems Considering Waste Heat Utilization in Data Centers","authors":"Rendong Shen,&nbsp;Ruifan Zheng,&nbsp;Shengyuan Zhong,&nbsp;Lei Gu,&nbsp;Dongfang Yang,&nbsp;Jun Zhao","doi":"10.1002/ese3.70501","DOIUrl":"https://doi.org/10.1002/ese3.70501","url":null,"abstract":"<p>A significant proportion of power consumption in data centers is ultimately converted into low-grade waste heat (WH), which is typically discharged into the atmosphere, resulting in substantial energy loss and environmental degradation. Utilizing heat pump (HP) systems to recover this WH for district heating presents a promising approach to improving energy efficiency and reducing environmental impact. While previous research primarily focused on the feasibility and technical implementation of such recovery systems, limited attention has been given to the co-optimization of WH utilization, particularly in systems that integrate HPs with energy storage. To address this gap, this study proposes an intelligent control framework that integrates user-side demand response with deep reinforcement learning to optimize system performance. Specifically, the twin delayed deep deterministic policy gradient algorithm is employed to generate real-time, adaptive control strategies. Additionally, a feasible action screening mechanism is introduced to ensure that control actions conform to the physical constraints of the system, thereby enhancing training stability and learning efficiency. Simulation results demonstrate that, compared with a benchmark model, the proposed approach improves system profit by 61.8% and increases renewable energy surplus by 25.7%.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 6","pages":"2704-2720"},"PeriodicalIF":3.4,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70501","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Investigation of Sensitivity for Coal and Gas Outburst Risk Prediction Indexes in Raw and Tectonic Composite Coal Seams","authors":"Haijun Guo,&nbsp;Xi Xi,&nbsp;Kai Wang,&nbsp;Liang Wang,&nbsp;Yulin Li","doi":"10.1002/ese3.70505","DOIUrl":"https://doi.org/10.1002/ese3.70505","url":null,"abstract":"<p>The prediction of coal and gas outburst risk is a critical first step in preventing and controlling gas-related accidents. To evaluate the sensitivity of outburst risk prediction indexes in raw and tectonic composite coal seams, both regional and local indexes for the No. 3 coal seam in the Daning Coal Mine were analyzed. Results indicate that tectonic coal exhibits higher initial gas desorption capacity and faster desorption rates than those of raw coal, resulting in a greater risk of coal and gas outbursts in tectonic coal seams. Among the regional outburst risk prediction indexes for the raw and tectonic composite coal seams, gas content was found to be more sensitive than gas pressure. A gas content of 8.00 m³/ton is identified as a safer critical threshold for the No. 3 coal seam. For local outburst risk prediction indexes, a comparison of gas desorption characteristics and index values under consistent laboratory-determined pressure conditions reveals that the drilling cuttings gas desorption index <i>K</i>₁ exhibits lower determination error and higher sensitivity than Δ<i>h</i>₂, enabling more accurate prediction of coal and gas outburst risk. Furthermore, a <i>K</i>₁ value of 0.46 mL/(g·min^0.5) is identified as a safer critical threshold for the No. 3 coal seam. These findings provide a crucial theoretical foundation for guiding the prevention and control of coal and gas outbursts and can inform process engineering design and coal mine safety practices.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 6","pages":"2772-2784"},"PeriodicalIF":3.4,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70505","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148209003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimized Parameter Extraction in Triple Diode Solar PV Models Using Kookaburra-based Dwarf Mongoose Approach","authors":"Chappani Sankaran Sundar Ganesh,&nbsp;Chandrasekaran Kumar,&nbsp;Thangavel Swaminathan Sivakumaran,&nbsp;Sourav Barua","doi":"10.1002/ese3.70516","DOIUrl":"https://doi.org/10.1002/ese3.70516","url":null,"abstract":"<p>Improving photovoltaics (PV) system performance through simulation requires accurate PV models. The nonlinear relationship between current and voltage, coupled with incomplete manufacturer data, presents a significant challenge in parameter estimation. This research work presents an innovative optimization framework designed to extract the parameters of a triple-diode model representing an unknown Solar PV module. The proposed approach leverages a novel hybrid optimization technique called the Kookaburra-based Dwarf Mongoose (KO-DM) Optimization Algorithm. It determines the unknown parameter that helps to characterize the equivalent circuit of the PV cell described by the triple-diode model. The performance of the proposed KO-DM algorithm was assessed using two distinct datasets: (1) 25°C with 1000 W/m² and (2) 45°C with 1000 W/m². The proposed method offers superior performance, exhibiting the ability to efficiently solve complex nonlinear optimization problems, converge rapidly to the global optimum, and involve a simple computational procedure.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 6","pages":"2996-3012"},"PeriodicalIF":3.4,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70516","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid Oxygen Enrichment and Preheating Strategy for Performance Recovery in Ultra-Lean Micro–Trapped Vortex Combustors","authors":"Anouar Benzitouni,&nbsp;Abdelhakim Settar,&nbsp;Boudinar Naouam,&nbsp;Salaheddine Azzouz,&nbsp;Zakaria Mansouri","doi":"10.1002/ese3.70518","DOIUrl":"https://doi.org/10.1002/ese3.70518","url":null,"abstract":"<p>Ultra-lean operation in micro-combustion-based thermophotovoltaic systems offers significant benefits including low pollutant emissions and increased longevity due to reduced thermal stresses, but it is hindered by low thermal performance. This paper numerically addresses the potential of oxygen enrichment and preheating to counteract performance losses in a hydrogen-powered micro-trapped vortex combustor operating under ultra-lean conditions. A Taguchi design of 16 cases was conducted at a fixed equivalence ratio of <i>ϕ</i> = 0.3, varying inlet temperature from 300 to 450 K and O₂ levels from 21% to 30%, to evaluate their impact on radiative power, energy conversion efficiency, combustion efficiency, and NO_x emissions. Results indicate that excessive enrichment (30% O₂) at high inlet temperature (≥ 400 K) leads to flame flashback, establishing an upper safety limit. Within the stable operating region, O₂ enrichment substantially improved radiative power by up to 56%, while preheating enhanced radiative efficiency by up to 73%, with both factors exhibiting equal influence on combustion efficiency. However, the use of oxygen-enriched air remarkably increased NOx emissions compared to the baseline case at 21% O₂. Moreover, the optimal configuration with <i>T</i>_in = 450 K and X_O2 = 0.27 has achieved 41% higher energy efficiency and 99% lower pollutant emissions compared to the lean case at <i>ϕ</i> = 0.8.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 6","pages":"3028-3041"},"PeriodicalIF":3.4,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70518","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}