Energy Conversion and Management-X最新文献

{"title":"Wind variability and its effect on transmission line capacity estimation","authors":"Nika Mlinarič Hribar ,&nbsp;Matjaž Depolli ,&nbsp;Gregor Kosec","doi":"10.1016/j.ecmx.2026.101633","DOIUrl":"10.1016/j.ecmx.2026.101633","url":null,"abstract":"<div><div>Transmission line ampere capacity, i.e. ampacity, can be determined in real time using dynamic thermal rating (DTR). Standard DTR systems rely on weather data averaged over multi-minute windows. While sufficient for most weather parameters, this approach can introduce considerable inaccuracies due to short-term variability of both wind speed and direction.</div><div>This study investigates the inaccuracies using high-resolution (1-second) wind measurements from an in-service transmission line. We evaluate two commonly used wind-averaging methods and show that variability in wind direction and the relative angle of wind crucially influence the results. In spans with parallel wind, which are often critical spans, i.e. spans that limit the ampacity of the whole line, averaged data commonly underestimates ampacity by more than 10%, with the maximum observed underestimation being over 45%. On the other hand, in perpendicular wind scenarios, averaging may lead to overestimation (by up to 25%), raising operational safety concerns.</div><div>For transmission system operators, incorporating wind-angle sensitivity and leveraging higher-resolution measurements where feasible can improve ampacity accuracy, enhance grid reliability, and unlock additional transfer capacity — contributing to more efficient and secure energy system operation.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101633"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance comparison and suitability evaluation of shell and tube heat exchangers for greenhouse environments using CFD and TRNSYS","authors":"Minjae Son ,&nbsp;Sungwan Park ,&nbsp;Sungmin Lee ,&nbsp;Sang Joon Chung ,&nbsp;Hoon Seonwoo","doi":"10.1016/j.ecmx.2026.101889","DOIUrl":"10.1016/j.ecmx.2026.101889","url":null,"abstract":"<div><div>Heat exchangers are essential for maintaining target temperatures in greenhouse environments, and shell-and-tube heat exchangers (STHEs) provide a high heat-transfer area and structural robustness. However, previous studies have mainly focused either on CFD-based analyses of STHE thermal performance or on greenhouse energy simulations with simplified heat-source representations; therefore, studies that directly incorporate a CFD-derived STHE thermal–hydraulic performance map into a dynamic whole-greenhouse simulation for suitability evaluation under realistic outdoor conditions remain scarce. In this study, CFD was used to quantify STHE heat transfer and pressure drop across operating conditions, and the resulting performance maps were coupled with TRNSYS greenhouse simulations under dynamic outdoor conditions to assess operational suitability. The analyses show that heat transfer and pumping power increase with STHE mass flow rate, indicating a clear trade-off between thermal benefit and hydraulic penalty. Under the investigated conditions, the STHE delivered up to 815.12 W of heat-transfer capacity with a corresponding pumping power of 113.15 W, and the higher mass-flow case (0.25 kg/s) showed improved capability to satisfy greenhouse temperature/load requirements. The proposed CFD–TRNSYS framework can support practical sizing and operation guidelines for selecting suitable STHE operating conditions for greenhouse heating and cooling.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101889"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147802428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel hybrid battery thermal management system based on a central cooling channel with an integrated conductive fin, porous media, and phase change materials","authors":"Mahziyar Ghaedi ,&nbsp;Mahdi Moghimi ,&nbsp;Hamid-Reza Bahrami","doi":"10.1016/j.ecmx.2026.101897","DOIUrl":"10.1016/j.ecmx.2026.101897","url":null,"abstract":"<div><div>Efficient thermal management is vital for the longevity and safety of lithium-ion batteries in demanding conditions. This study introduces a novel hybrid battery thermal management system (BTMS) that combines central liquid cooling with conductive fins, porous media, and phase change materials (PCM) enhanced with metallic foam, and optimized performance to achieve improved thermal efficiency and safety with minimal hydraulic penalties. Five different categories including 13 designs are examined: passive cooling, side-channel liquid cooling, fin-assisted central cooling (with/without porous media), and advanced hybrids with porous media and phase change materials. A three-dimensional conjugate heat transfer model, validated against multiple benchmarks, is employed using computational fluid dynamics, with PCM melting simulated via the enthalpy–porosity method. Results show the fin-assisted central channel reduces maximum battery temperature by 12.1 K and improves temperature uniformity by 49.11% versus a side-channel design. Adding porous media further lowers the maximum temperature by 8.83 K. While plain PCM is ineffective, PCM impregnated with metallic foam reduces highest temperature by up to 10.7 K and achieves uniformity below 2 K. The optimal design— a fin-assisted central channel integrated with porous-enhanced PCM— limits the maximum temperature to 302.16 K, maintains a temperature uniformity of 1.8 K, and, compared with the channel without PCM layers, increases the pressure drop from 3.29 Pa to 3.87 Pa, which is not significant and does not impose a considerable hydraulic penalty on the system. This configuration effectively achieves a balance between energy efficiency and thermal safety, delivering actionable insights for the design of future battery thermal management systems in demanding, high-power settings.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101897"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147858125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Solar- and biomass-assisted hybrid solid oxide fuel cell, thermophotovoltaic, and photovoltaic system for sustainable ammonia and synthetic natural gas production: multi-objective LCA-TEA optimization","authors":"Shayan Rabet ,&nbsp;Shayan Sharafi Laleh ,&nbsp;Haniyeh Sadat Rezaei Mousavi ,&nbsp;Ehsan Gholamian ,&nbsp;Mortaza Yari ,&nbsp;Saeed Soltani ,&nbsp;Ali Saberi Mehr","doi":"10.1016/j.ecmx.2025.101268","DOIUrl":"10.1016/j.ecmx.2025.101268","url":null,"abstract":"<div><div>This study proposes a novel solar- and biomass-assisted hybrid energy system integrating a solid oxide fuel cell (SOFC), thermophotovoltaic (TPV) unit, PV-powered alkaline electrolyzer, and downstream methanation and ammonia synthesis units. The system is designed for multi-product generation, producing electricity, synthetic natural gas (SNG), ammonia, and liquefied CO₂, while efficiently managing carbon using LNG cold energy. Key innovations include TPV-based recovery of high-temperature SOFC radiation for electricity, integration of PV-powered hydrogen production, and combined methanation and ammonia synthesis to enhance product diversity and efficiency. System performance is comprehensively evaluated using energy and exergy analysis, techno-economic assessment, life cycle assessment (LCA), and multi-objective optimization with the Gray Wolf Optimization (GWO) algorithm. At baseline conditions, the system achieves 32.74 % exergy efficiency, 2776 kW net power output, and production rates of 0.67 kg/s CO₂, 0.0264 kg/s methane, and 0.0692 kg/s ammonia, while the unit energy cost is 37.04 $/GJ. LCA confirms the environmental sustainability of the system, and optimization further improves efficiency (up to 33.23 %) and reduces costs (down to 36.06 $/GJ) and emission index (down to 0.0902 kg/kWh). The proposed system demonstrates strong potential for sustainable green fuel production, efficient carbon capture, and enhanced economic performance compared to existing hybrid energy approaches.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101268"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147802426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kinetics and deactivation modelling of fibrous silica-supported Ni-Ga catalysts for COx-free hydrogen production via methane splitting","authors":"Rizwan Ali ,&nbsp;Sadiya Mushtaq ,&nbsp;Chin Kui Cheng ,&nbsp;Mohammad Abu Haija ,&nbsp;Maryam Khaleel ,&nbsp;Khalid Al-Ali","doi":"10.1016/j.ecmx.2026.101662","DOIUrl":"10.1016/j.ecmx.2026.101662","url":null,"abstract":"<div><div>Thermocatalytic methane splitting offers a viable route for hydrogen production without greenhouse gas emissions. In this study, a detailed kinetic and deactivation analysis was conducted for methane splitting over a Ni–Ga/KCC1 catalyst using a fixed-bed reactor at temperatures ranging from 600 to 650 °C and varying methane partial pressures (0.2–0.8 atm). Structure–activity correlations were explored via characterization of fresh and spent catalysts using X-ray diffraction (XRD), nitrogen physisorption, hydrogen temperature-programmed reduction (H₂-TPR), Transmission electron microscopy (TEM) and thermogravimetric analysis (TGA). The intrinsic reaction kinetics revealed a reaction order of 0.56 and an activation energy of 62.16  kJ mol⁻¹. Catalyst deactivation behavior was systematically investigated using two modeling approaches: the Power-Law Model (PLM) and the Exponential Decay Model (EDM). However, EDM provided an overall better fit compared to PLM. Based on decay model parameters (A and τ), the activity factor was quantitatively modeled as a function of methane partial pressure and reaction temperature, showing strong agreement with experimental data. This work establishes a comprehensive kinetic and deactivation framework for Ni–Ga/KCC1-catalyzed methane splitting, providing predictive insights for hydrogen production under varied process<!--> <!-->conditions.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101662"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Floating offshore wind in the Nordic synchronous area: Resource potential, geographical smoothing, and storage integration","authors":"Izabella Simonsson,&nbsp;Erik Jonasson,&nbsp;Irina Temiz,&nbsp;Hans Bernhoff","doi":"10.1016/j.ecmx.2026.101657","DOIUrl":"10.1016/j.ecmx.2026.101657","url":null,"abstract":"<div><div>The Nordic synchronous area strives to achieve a fossil-free energy system, requiring significant expansion of renewable electricity generation. While onshore wind power is technologically mature, offshore wind, particularly floating installations, offers access to stronger and more consistent wind resources in deeper waters. In this study, the potential of floating offshore wind power in the Nordic synchronous area is evaluated through a 21-year (2004–2024) wind resource analysis using ERA5 reanalysis data for 11 geographically distributed sites across several seas. A MATLAB-based model was developed to simulate the wind power generation. Simulating local compressed air energy storage at each site and centralized hydropower storage, the total losses and curtailments of the proposed system are determined. A system with both local and centralized storage demonstrates greater reliability in providing a baseload to the grid than a system with only local storage. Additionally, the geographical smoothing significantly reduces variability, with correlation between sites decaying exponentially with distance. The system has the potential to provide 187.3 TWh annually. Furthermore, the seasonal variation in the Nordic synchronous area was integrated into the model. It showed higher demand during the winter and lower demand during the summer, and demonstrated reliability in providing a baseload to the grid, with an annual output of 189.5 TWh. Floating offshore wind, combined with local storage and existing hydropower flexibility, can contribute to the Nordic synchronous area for baseload supply and enhance system reliability while expanding generation and supporting the region’s decarbonization goals.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101657"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of new and used Lithium-Ion electric motorcycle batteries degradation through cycle testing and surface temperature evaluation for second-life applications","authors":"Suroso ,&nbsp;Triyogi Yuwono ,&nbsp;Alief Wikarta ,&nbsp;Widyastuti ,&nbsp;Surya Putra Andrianto ,&nbsp;Anugrah Andisetiawan ,&nbsp;Romel Hidayat ,&nbsp;Masytha Ramdhiny ,&nbsp;Rifdah Adya Salsabila ,&nbsp;Liyana Labiba Zulfa ,&nbsp;Sikandar Aftab","doi":"10.1016/j.ecmx.2026.101640","DOIUrl":"10.1016/j.ecmx.2026.101640","url":null,"abstract":"<div><div>The growth of electric vehicles (EVs) has driven an increase in the number of used lithium-ion batteries (LiBs). The used LiBs still have the potential to be reused in second-life battery (SLB) applications. Characterization of the used LiB performance is necessary to ensure its suitability for second-life battery (SLB) applications. This study aims to obtain the optimum C-rate for used online motorcycle taxi batteries. The analysis of the impact of C-rate on battery capacity and surface temperature was conducted over 50 cycles at C-rates of 1C, 0.5C, and 0.3C. The study results show that a high C-rate has a significant impact on the capacity and efficiency of used batteries in the charging-discharging process. The obtained data suggest that used batteries are more stable at a lower C-rate (0.3C). A high C-rate also affects the temperature increase of used batteries during charging and discharging. At a C-rate of 1C, the temperature increase can reach approximately 6 – 10 ℃, whereas at a low C-rate of 0.3C, the temperature increase is only around 2 – 3.5 ℃. To reduce safety risks in the second-life application of used batteries, it is recommended to operate at low C-rates.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101640"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Topology-variable-based reliability modeling for optimal smart switch deployment in flexible distribution networks with Scenario-Based parallel progressive hedging algorithm","authors":"Ziyao Wang ,&nbsp;Tao Yu ,&nbsp;Pengyi Fan ,&nbsp;Minghao Wang","doi":"10.1016/j.ecmx.2026.101596","DOIUrl":"10.1016/j.ecmx.2026.101596","url":null,"abstract":"<div><div>In flexible distribution networks (FDNs), the placement of smart switches, including circuit breakers (CBs), remote-controlled switches (RCSs), and soft open points (SOPs), substantially impacts fault propagation, isolation, and service restoration, thus influencing system reliability indices. Existing research, however, does not explicitly model the relationship between smart switch placement in FDNs as topological decision variables and these reliability indices. As a result, switch placement and reliability assessment remain an “open-loop” process requiring multiple iterations, which cannot guarantee optimality under reliability constraints or objectives. To address this issue, this paper proposes a topology-variable-based reliability modeling framework for optimizing smart switch placement, which integrates CB, RCS, and SOP, and explicitly links system reliability indices (ASAI, SAIDI, SAIFI, EENS) with smart switch placement decisions. The proposed optimization-based reliability model is developed to capture the synergistic effects of these switches across fault detection (FD), fault isolation (FI), and service restoration (SR) phases, embedding dynamic topology changes and power flow control into a two-stage stochastic mixed-integer programming formulation considering multiple fault scenarios. To solve this complex model efficiently, a scenario-aware element-wise progressive hedging (SEW-PH) algorithm is introduced, leveraging adaptive parameter strategies to decouple multi-scenario computations and accelerate convergence. Case studies reveal that joint deployment of CBs, RCSs, and SOPs in FDNs further enhances reliability indices beyond traditional switch deployment strategy, attributed to SOP’s rapid fault isolation and power flow control—delivering superior cost-effectiveness and comprehensive performance in high-reliability scenarios. Compared to heuristic optimization that fall under open-loop reliability-aware planning frameworks, the proposed close-loop reliability-aware smart switch deployment framework ensures high solving efficiency while improving solution optimality, with the SEW-PH algorithm further accelerating model solving.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101596"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CO2 utilization for H2-rich syngas production in a combined system: Bi-objective optimization and machine learning analysis","authors":"Parisa Mojaver","doi":"10.1016/j.ecmx.2026.101588","DOIUrl":"10.1016/j.ecmx.2026.101588","url":null,"abstract":"<div><div>This study aimed to mitigate environmental risks in energy production through the design of a system that generates high-quality syngas from a blend of poplar wood and polyethylene terephthalate waste. CO₂ was employed as the gasifying agent, an approach that both eliminates nitrogen dilution in the syngas stream and offers a practical pathway for CO₂ utilization from industrial emissions, thereby linking clean energy production with greenhouse gas reduction. To assess the validity and robustness of the developed models, a residual analysis was performed. Subsequently, a bi-objective optimization was conducted to simultaneously maximize cold gas efficiency and the H₂/CO ratio. The reliability of the machine learning model was evaluated by comparing its predictions with the outcomes derived from thermodynamic simulations. The results demonstrated that the optimal operating range was within a gasifier agent to fuel of 1.95–2.15 and a water gas shift reactor agent to fuel of 1.75–1.90. In this range, the system achieved cold gas efficiencies between 97% and 98%, along with H₂/CO ratio percentage ranging from 80% to 90%. The comparative analysis indicated that the results predicted by machine learning models showed strong agreement with those obtained from the engineering equation solver simulation software.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101588"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Industry-adaptable explainable AI based methodology for forecasting electricity prices","authors":"Bence Biró ,&nbsp;Csaba Kiss ,&nbsp;Roland Molontay ,&nbsp;Attila Aszódi","doi":"10.1016/j.ecmx.2026.101583","DOIUrl":"10.1016/j.ecmx.2026.101583","url":null,"abstract":"<div><div>The COVID-19 pandemic and the volatility of the energy market triggered by Russia’s invasion of Ukraine have highlighted the critical importance of the reliability and transparency of electricity price forecasting. The use of artificial intelligence models based on explainable AI has become essential for market participants to develop more efficient and informed strategies by making predictions more meaningful. Within the framework of this study, we developed artificial intelligence models based on open-source data and models for forecasting the day-ahead electricity prices in 19 European countries and analyzed the importance of different features in the models for the forecasting using SHAP values. Our results showed that for both 2015–2020 and 2020–2024 periods, the tree-based machine learning models performed best in price forecasting. By analyzing our models using SHAP, we show how much feature importance has changed from 2020 to 2024, demonstrating the increased complexity of electricity price forecasting due to the energy crisis and structural changes in the electricity system. Using Germany and France as case studies, we present detailed results for the two distinct electricity markets across both modelled periods.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101583"},"PeriodicalIF":7.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}