Pub Date : 2026-01-17DOI: 10.1016/j.ecmx.2026.101583
Bence Biró , Csaba Kiss , Roland Molontay , Attila Aszódi
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.
{"title":"Industry-adaptable explainable AI based methodology for forecasting electricity prices","authors":"Bence Biró , Csaba Kiss , Roland Molontay , 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":"2026-01-17","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}
Pub Date : 2026-01-17DOI: 10.1016/j.ecmx.2026.101564
Amir Nourmohammadi , Majid Siavashi , Hossein Pourrahmani , Mohammad Mehdi Hesampour
Proton exchange membrane fuel cells (PEMFCs) are considered an advanced technology for clean energy usage due to their high efficiency and zero emissions. However, effective water management in the gas diffusion layer (GDL), particularly the formation and removal of liquid water droplets, remains a major challenge. In this study, a three-dimensional two-phase flow model based on the lattice Boltzmann method combined with the volume of fluid (LBM-VOF) approach is developed using the Palabos platform to simulate droplet dynamics at the pore scale of the GDL. The model is validated against existing numerical and experimental data. The main novelty of this study is to show the impacts of key geometric parameters, including porosity, fiber diameter, contact angle, and inlet velocity for conventional fiber-based structures, followed by the report of the best-performing values. Results reveal that mesh-based geometries, especially the hexagonal arrangement, significantly enhance water removal. In particular, the MultiOctagon 70% and Hexagon 70% configurations reduce water saturation and removal time by 42.16% and 44.99%, and by 47.61% and 43.99%, respectively, compared to the random fiber-based structure with 70% porosity and 8 µm fiber diameter. These findings highlight the potential of GDL designs to improve water management and overall PEMFC performance.
{"title":"Geometric design of gas diffusion layer of PEMFCs to improve water management using multiphase lattice Boltzmann method","authors":"Amir Nourmohammadi , Majid Siavashi , Hossein Pourrahmani , Mohammad Mehdi Hesampour","doi":"10.1016/j.ecmx.2026.101564","DOIUrl":"10.1016/j.ecmx.2026.101564","url":null,"abstract":"<div><div>Proton exchange membrane fuel cells (PEMFCs) are considered an advanced technology for clean energy usage due to their high efficiency and zero emissions. However, effective water management in the gas diffusion layer (GDL), particularly the formation and removal of liquid water droplets, remains a major challenge. In this study, a three-dimensional two-phase flow model based on the lattice Boltzmann method combined with the volume of fluid (LBM-VOF) approach is developed using the Palabos platform to simulate droplet dynamics at the pore scale of the GDL. The model is validated against existing numerical and experimental data. The main novelty of this study is to show the impacts of key geometric parameters, including porosity, fiber diameter, contact angle, and inlet velocity for conventional fiber-based structures, followed by the report of the best-performing values. Results reveal that mesh-based geometries, especially the hexagonal arrangement, significantly enhance water removal. In particular, the MultiOctagon 70% and Hexagon 70% configurations reduce water saturation and removal time by 42.16% and 44.99%, and by 47.61% and 43.99%, respectively, compared to the random fiber-based structure with 70% porosity and 8 µm fiber diameter. These findings highlight the potential of GDL designs to improve water management and overall PEMFC performance.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101564"},"PeriodicalIF":7.6,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039762","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}
Pub Date : 2026-01-17DOI: 10.1016/j.ecmx.2026.101558
Md. Asaduz-Zaman , Makbul A.M. Ramli , Sultan Alghamdi
The renewable-driven seawater reverse osmosis desalination (SWROD) plant has emerged as a sustainable solution to address the growing freshwater demand worldwide. In such systems, energy storage plays a critical role in coordinating water-energy balance. This study proposes a hybrid battery-tank storage operational strategy for techno-economic optimization of PV/Wind-based microgrids applied to SWROD. The methodology applies genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC) techniques for design comparison and validation. Five decision variables include SWROD capacity, PV panels, wind turbines, battery, and tank storage. The optimization minimizes the levelized cost of water (LCOW) while satisfying the loss of water supply probability (LWSP). Three microgrid configurations are simulated for Yanbu City using MATLAB software. Results indicate that PV/Wind hybrid system yields the lowest LCOW of 1.06657 $/m3 consisting of 2530 kW PV, 5240 kW wind turbine, 8700 kWh battery storage, 7500 m3 tank, and SWROD capacity of 9600 m3/day. Configurations relying solely on PV or Wind exhibit higher costs. ABC algorithm also outperforms the GA and PSO. Sensitivity analysis further reveals that water demand variability imposes greater risks than solar irradiance or wind fluctuations. This storage model offers a promising pathway toward resilient and cost-effective renewable desalination systems.
{"title":"A hybrid energy storage approach for techno-economic optimization of renewable microgrids in SWROD applications","authors":"Md. Asaduz-Zaman , Makbul A.M. Ramli , Sultan Alghamdi","doi":"10.1016/j.ecmx.2026.101558","DOIUrl":"10.1016/j.ecmx.2026.101558","url":null,"abstract":"<div><div>The renewable-driven seawater reverse osmosis desalination (SWROD) plant has emerged as a sustainable solution to address the growing freshwater demand worldwide. In such systems, energy storage plays a critical role in coordinating water-energy balance. This study proposes a hybrid battery-tank storage operational strategy for techno-economic optimization of PV/Wind-based microgrids applied to SWROD. The methodology applies genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC) techniques for design comparison and validation. Five decision variables include SWROD capacity, PV panels, wind turbines, battery, and tank storage. The optimization minimizes the levelized cost of water (LCOW) while satisfying the loss of water supply probability (LWSP). Three microgrid configurations are simulated for Yanbu City using MATLAB software. Results indicate that PV/Wind hybrid system yields the lowest LCOW of 1.06657 $/m<sup>3</sup> consisting of 2530 kW PV, 5240 kW wind turbine, 8700 kWh battery storage, 7500 m<sup>3</sup> tank, and SWROD capacity of 9600 m<sup>3</sup>/day. Configurations relying solely on PV or Wind exhibit higher costs. ABC algorithm also outperforms the GA and PSO. Sensitivity analysis further reveals that water demand variability imposes greater risks than solar irradiance or wind fluctuations. This storage model offers a promising pathway toward resilient and cost-effective renewable desalination systems.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101558"},"PeriodicalIF":7.6,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039769","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}
Pub Date : 2026-01-17DOI: 10.1016/j.ecmx.2026.101582
Claudio Zuffi, Daniele Fiaschi
The objective of the paper is a comprehensive energy and material rarity analysis of a representative example of household shifted to fully electric utilities, supported by uncommon combination of photovoltaic and wind renewables, complemented by battery storage. The manuscript provides figures of optimal battery storage sizing, complementarity of PV and wind resource and material rarity impact assessment, in a combined manner unavailable in literature. The approach and the considered example are generalizable to the wide category of single households and/or accommodation facilities in suburban areas, the countryside, the mountains and holiday resorts.
The manuscript analyses the dynamic behaviour of a moderately refurbished single-family household located in a country/suburban area of central Italy, grid-connected and fully electrified through a heat pump combined with Photovoltaics, Wind Turbine (PV/WT), and a Battery Energy Storage System (BESS). A dynamic model based on 12 representative monthly days was developed to evaluate the seasonal thermal and electrical behaviour of the building. It was validated against measured PV/BESS data from an existing case study, characterized by its overall pre-/post-refurbishment transmittance U. To avoid costly and invasive masonry interventions, the existing high-temperature heaters were preserved, and a high-temperature Heat Pump (HP) was adopted. The seasonal simulations enabled the optimization of the Battery Ratio (BR), defined as the BESS-to-(PV+WT) size ratio, to maximize the renewable fraction (Fr). Depending on the configuration, Fr ranged between 58.5 % and 65.6 % without WT, and increased up to 76.4–87.9 % with WT. The daily deficit associated with a PV string anomaly was quantified at 1–4 kWh under clear-sky summer conditions.
Finally, an element rarity (TR) assessment was carried out for HP, PV, WT, and BESS as a complement to standard sustainability metrics. The analysis highlighted a TR impact of 68.2 GJ for WT, 36 GJ for PV, and 21.3 MJ for HP, while a 7 kWh BESS reached 36.6 GJ, largely driven by cobalt (79.2 %).
This study provides a comprehensive example of household energy transition, combining moderate and cost-effective refurbishment strategies with an uncommon PV/WT integration, relying on data from a real case study. It also introduces material rarity as an additional sustainability indicator, with the aim of supporting more balanced design choices in the residential energy sector.
{"title":"Energy transition buildings: A representative case study of refurbished single household shifted to full electric utilities combined with PV, wind and battery storage","authors":"Claudio Zuffi, Daniele Fiaschi","doi":"10.1016/j.ecmx.2026.101582","DOIUrl":"10.1016/j.ecmx.2026.101582","url":null,"abstract":"<div><div>The objective of the paper is a comprehensive energy and material rarity analysis of a representative example of household shifted to fully electric utilities, supported by uncommon combination of photovoltaic and wind renewables, complemented by battery storage. The manuscript provides figures of optimal battery storage sizing, complementarity of PV and wind resource and material rarity impact assessment, in a combined manner unavailable in literature. The approach and the considered example are generalizable to the wide category of single households and/or accommodation facilities in suburban areas, the countryside, the mountains and holiday resorts.</div><div>The manuscript analyses the dynamic behaviour of a moderately refurbished single-family household located in a country/suburban area of central Italy, grid-connected and fully electrified through a heat pump combined with Photovoltaics, Wind Turbine (PV/WT), and a Battery Energy Storage System (BESS). A dynamic model based on 12 representative monthly days was developed to evaluate the seasonal thermal and electrical behaviour of the building. It was validated against measured PV/BESS data from an existing case study, characterized by its overall pre-/post-refurbishment transmittance U. To avoid costly and invasive masonry interventions, the existing high-temperature heaters were preserved, and a high-temperature Heat Pump (HP) was adopted. The seasonal simulations enabled the optimization of the Battery Ratio (BR), defined as the BESS-to-(PV+WT) size ratio, to maximize the renewable fraction (Fr). Depending on the configuration, Fr ranged between 58.5 % and 65.6 % without WT, and increased up to 76.4–87.9 % with WT. The daily deficit associated with a PV string anomaly was quantified at 1–4 kWh under clear-sky summer conditions.</div><div>Finally, an element rarity (TR) assessment was carried out for HP, PV, WT, and BESS as a complement to standard sustainability metrics. The analysis highlighted a TR impact of 68.2 GJ for WT, 36 GJ for PV, and 21.3 MJ for HP, while a 7 kWh BESS reached 36.6 GJ, largely driven by cobalt (79.2 %).</div><div>This study provides a comprehensive example of household energy transition, combining moderate and cost-effective refurbishment strategies with an uncommon PV/WT integration, relying on data from a real case study. It also introduces material rarity as an additional sustainability indicator, with the aim of supporting more balanced design choices in the residential energy sector.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101582"},"PeriodicalIF":7.6,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080132","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}
Pub Date : 2026-01-17DOI: 10.1016/j.ecmx.2026.101592
Eric Augusto Melchor Cruz, Mohamed Badaoui, David Sebastián-Baltazar
This paper addresses the issue of optimizing short-term hydro-power generation under multiple sources of uncertainty by proposing a Chance-Constrained Mixed-Integer Nonlinear Programming (MINLP) model for the Valentín Gómez Farías Hydro-Power Plant in Mexico. The optimization problems incorporate realistic stochastic behaviors in electricity prices and demand requirements, utilizing derived probability distributions, where stochasticity increases as the modeling progresses. Initially, this paper analyzes the sensitivity of the revenue regarding a risk level under a normally distributed parameter approach. Further, two formulations are developed, one using deterministic forecasts and the other incorporating a stochastic objective function via Monte Carlo simulation. The study addresses the Sample Average Approximation (SAA) and the Bonferroni approach to manage joint chance constraints under an operational risk. Our work’s technical contribution proposes an integrated and validated use of a hydro-technical model within a stochastic market environment. Specifically, we embed realistic nonlinear hydro-generation equations with friction head losses directly into a chance-constrained optimization framework, a practice rarely seen in the hydro-power domain where linearized dispatch models are often used. Using actual system data from the Mexican electricity market introduces operational realism, which is often missing in theoretical formulations. Numerical results from Julia’s programming language demonstrate that the validated optimal solution achieves a maximum expected revenue under a risk tolerance of , while maintaining a feasible solution with a maximum violation probability of 0.06913, as confirmed through Monte Carlo-based validation. We demonstrate the impact of feasible water dispatch strategies by interacting with physical Hydro constraints, probabilistic demand constraints, and market price signals over short-term horizons, highlighting the immediate applicability of our work and bridging uncertainty and profitability with optimal solutions for the day-ahead Hydro-Power Plant operation policy.
{"title":"Bridging uncertainty and profitability: A chance-constrained optimization approach for day-ahead hydro-power operations","authors":"Eric Augusto Melchor Cruz, Mohamed Badaoui, David Sebastián-Baltazar","doi":"10.1016/j.ecmx.2026.101592","DOIUrl":"10.1016/j.ecmx.2026.101592","url":null,"abstract":"<div><div>This paper addresses the issue of optimizing short-term hydro-power generation under multiple sources of uncertainty by proposing a Chance-Constrained Mixed-Integer Nonlinear Programming (MINLP) model for the Valentín Gómez Farías Hydro-Power Plant in Mexico. The optimization problems incorporate realistic stochastic behaviors in electricity prices and demand requirements, utilizing derived probability distributions, where stochasticity increases as the modeling progresses. Initially, this paper analyzes the sensitivity of the revenue regarding a risk level under a normally distributed parameter approach. Further, two formulations are developed, one using deterministic forecasts and the other incorporating a stochastic objective function via Monte Carlo simulation. The study addresses the Sample Average Approximation (SAA) and the Bonferroni approach to manage joint chance constraints under an operational risk. Our work’s technical contribution proposes an integrated and validated use of a hydro-technical model within a stochastic market environment. Specifically, we embed realistic nonlinear hydro-generation equations with friction head losses directly into a chance-constrained optimization framework, a practice rarely seen in the hydro-power domain where linearized dispatch models are often used. Using actual system data from the Mexican electricity market introduces operational realism, which is often missing in theoretical formulations. Numerical results from Julia’s programming language demonstrate that the validated optimal solution achieves a maximum expected revenue under a risk tolerance of <span><math><mrow><mi>ɛ</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>08</mn></mrow></math></span>, while maintaining a feasible solution with a maximum violation probability of 0.06913, as confirmed through Monte Carlo-based validation. We demonstrate the impact of feasible water dispatch strategies by interacting with physical Hydro constraints, probabilistic demand constraints, and market price signals over short-term horizons, highlighting the immediate applicability of our work and bridging uncertainty and profitability with optimal solutions for the day-ahead Hydro-Power Plant operation policy.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101592"},"PeriodicalIF":7.6,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039629","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}
Pub Date : 2026-01-17DOI: 10.1016/j.ecmx.2026.101580
Tao Chen , Yu Zhang , Darius Mottaghy
Fracture geometry is critical for Enhanced Geothermal Systems (EGS) performance. This study uses 3D ensemble simulations to investigate how natural fracture characteristics affect long-term heat production. Discrete fracture models are built stochastically using Monte Carlo simulations with power-law length distributions, Fisher orientation distributions, and power-law aperture-length scaling relationships, based on data from the Soultz EGS site. Coupled thermo-hydraulic simulations are performed using the finite element method (FEM) to solve fluid flow and heat transport equations. An analytical solution for doublet heat extraction in idealized fracture-matrix systems verifies the numerical model accuracy. Results from fifty realizations show that fracture geometries significantly influence production temperature and hydraulic-head differences. Temperature and geothermal energy production increase slightly with fracture length and density but decrease with aperture-length correlation exponent. Increasing the aperture-length correlation exponent from 0 to 2 reduces mean temperature from 170 °C to 119 °C, decreases energy production by approximately 37 % (from 20.3 PJ to 12.8 PJ over 60.6 years), and conversely increases hydraulic-head differences, demonstrating that fracture heterogeneity significantly impacts EGS performance through promoting preferential flow channeling while reducing connectivity. An exponential function best fits both relationships. The uncertainty of heat extraction performance decreases with increasing fracture length and density. While parameters are based on Soultz site characterization, the exponential relationship between fracture heterogeneity and thermal performance is expected to hold qualitatively in other fractured geothermal reservoirs.
{"title":"Impacts of natural fracture geometries on heat production in enhanced geothermal systems: from 3D discrete fracture models to uncertainty analysis","authors":"Tao Chen , Yu Zhang , Darius Mottaghy","doi":"10.1016/j.ecmx.2026.101580","DOIUrl":"10.1016/j.ecmx.2026.101580","url":null,"abstract":"<div><div>Fracture geometry is critical for Enhanced Geothermal Systems (EGS) performance. This study uses 3D ensemble simulations to investigate how natural fracture characteristics affect long-term heat production. Discrete fracture models are built stochastically using Monte Carlo simulations with power-law length distributions, Fisher orientation distributions, and power-law aperture-length scaling relationships, based on data from the Soultz EGS site. Coupled thermo-hydraulic simulations are performed using the finite element method (FEM) to solve fluid flow and heat transport equations. An analytical solution for doublet heat extraction in idealized fracture-matrix systems verifies the numerical model accuracy. Results from fifty realizations show that fracture geometries significantly influence production temperature and hydraulic-head differences. Temperature and geothermal energy production increase slightly with fracture length and density but decrease with aperture-length correlation exponent. Increasing the aperture-length correlation exponent from 0 to 2 reduces mean temperature from 170 °C to 119 °C, decreases energy production by approximately 37 % (from 20.3 PJ to 12.8 PJ over 60.6 years), and conversely increases hydraulic-head differences, demonstrating that fracture heterogeneity significantly impacts EGS performance through promoting preferential flow channeling while reducing connectivity. An exponential function best fits both relationships. The uncertainty of heat extraction performance decreases with increasing fracture length and density. While parameters are based on Soultz site characterization, the exponential relationship between fracture heterogeneity and thermal performance is expected to hold qualitatively in other fractured geothermal reservoirs.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101580"},"PeriodicalIF":7.6,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039766","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}
Pub Date : 2026-01-16DOI: 10.1016/j.ecmx.2026.101578
Claudia Schön , Juho Louhisalmi , Kamil Krpec , Hans Hartmann , Isaline Fraboulet , Benjamin Cea , Jarkko Tissari
The use of log wood stoves is common in residential homes and are tested in a type test procedure following EN 16510-1:2022 at optimal combustion condition. Since this does not represent real-life operation, a novel test protocol was developed and validated using two different log wood stoves. The new test protocol includes the ignition phase (two batches) at natural draught, followed by three batches at nominal load, two batches at partial load and one final batch at overload. Typical emission parameters such as carbon monoxide (CO), nitrogen oxides (NOX), organic gaseous carbon (OGC) emissions were recorded as well as TPM emissions in the hot undiluted flue gas. This study shows that it is challenging to get similar emission results for the same stove in different laboratories even when using the same fuel and well-defined test protocol, differences in results are due to measurement uncertainty, differences in appliance operations and not following exactly the defined Real-LIFE test protocol. Coefficients of variation for TPM, CO, OGC and NOX were 17.8 %, 20.1 %, 30.6 % and 8.7 %, respectively for stove A and 32.7 %, 13.9 %, 19.6 % and 10.0 %, respectively for stove B based on two to three repetitions per lab. The novel test protocol showed that combustion appliances may behave differently in different combustion phases, and this emphasizes the importance of measuring different combustion conditions in official testing to ensure that the appliances work properly in the field and that the measured emissions cover the whole operating range.
{"title":"Validation of a novel Real-LIFE test protocol on two log wood stoves","authors":"Claudia Schön , Juho Louhisalmi , Kamil Krpec , Hans Hartmann , Isaline Fraboulet , Benjamin Cea , Jarkko Tissari","doi":"10.1016/j.ecmx.2026.101578","DOIUrl":"10.1016/j.ecmx.2026.101578","url":null,"abstract":"<div><div>The use of log wood stoves is common in residential homes and are tested in a type test procedure following EN 16510-1:2022 at optimal combustion condition. Since this does not represent real-life operation, a novel test protocol was developed and validated using two different log wood stoves. The new test protocol includes the ignition phase (two batches) at natural draught, followed by three batches at nominal load, two batches at partial load and one final batch at overload. Typical emission parameters such as carbon monoxide (CO), nitrogen oxides (NO<sub>X</sub>), organic gaseous carbon (OGC) emissions were recorded as well as TPM emissions in the hot undiluted flue gas. This study shows that it is challenging to get similar emission results for the same stove in different laboratories even when using the same fuel and well-defined test protocol, differences in results are due to measurement uncertainty, differences in appliance operations and not following exactly the defined Real-LIFE test protocol. Coefficients of variation for TPM, CO, OGC and NO<sub>X</sub> were 17.8<!--> <!-->%, 20.1<!--> <!-->%, 30.6<!--> <!-->% and 8.7<!--> <!-->%, respectively for stove<!--> <!-->A and 32.7<!--> <!-->%, 13.9<!--> <!-->%, 19.6<!--> <!-->% and 10.0<!--> <!-->%, respectively for stove<!--> <!-->B based on two to three repetitions per lab. The novel test protocol showed that combustion appliances may behave differently in different combustion phases, and this emphasizes the importance of measuring different combustion conditions in official testing to ensure that the appliances work properly in the field and that the measured emissions cover the whole operating range.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101578"},"PeriodicalIF":7.6,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145996501","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}
A mathematical model was proposed to predict pressure development in vented explosions of methane-air mixture, considering the effect of secondary explosion indoors and external explosion on pressure development in chamber. Validation against experimental data demonstrates strong predictive accuracy, with model predictions for peak overpressure falling within ±10 % of measured values under lean mixture conditions (φ = 0.6–1.5). The model shows that indoor secondary explosions occur only when the residual gas concentration remains within the explosive limits (5–15 % vol for methane), a condition influenced by the initial equivalence ratio, the chemical reaction process variables and the gas venting ratio. Higher venting pressures (0.3–25 kPa) amplify indoor secondary explosion peaks, whereas excessively rich mixtures (Φ > 1.5) or elevated initial temperatures (>140 °C) suppress indoor secondary explosion. The proposed model offers a robust tool for designing venting systems by accurately capturing multi-peak pressure profiles and coupling residual gas concentration with criteria for secondary explosions.
{"title":"A mathematical model for calculating pressure development in vented explosions of methane-air mixture","authors":"Xingxing Liang , Junjie Cheng , Zhongqi Wang , Yaling Liao , Huajiao Zeng","doi":"10.1016/j.ecmx.2026.101581","DOIUrl":"10.1016/j.ecmx.2026.101581","url":null,"abstract":"<div><div>A mathematical model was proposed to predict pressure development in vented explosions of methane-air mixture, considering the effect of secondary explosion indoors and external explosion on pressure development in chamber. Validation against experimental data demonstrates strong predictive accuracy, with model predictions for peak overpressure falling within ±10 % of measured values under lean mixture conditions (φ = 0.6–1.5). The model shows that indoor secondary explosions occur only when the residual gas concentration remains within the explosive limits (5–15 % vol for methane), a condition influenced by the initial equivalence ratio, the chemical reaction process variables and the gas venting ratio. Higher venting pressures (0.3–25 kPa) amplify indoor secondary explosion peaks, whereas excessively rich mixtures (Φ > 1.5) or elevated initial temperatures (>140 °C) suppress indoor secondary explosion. The proposed model offers a robust tool for designing venting systems by accurately capturing multi-peak pressure profiles and coupling residual gas concentration with criteria for secondary explosions.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101581"},"PeriodicalIF":7.6,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039786","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}
Pub Date : 2026-01-16DOI: 10.1016/j.ecmx.2026.101576
Sara Tamburello, Lindert van Biert, Andrea Coraddu
Low-Temperature Polymer Electrolyte Membrane Fuel Cells (LT-PEMFCs) have recently emerged as a promising solution for sustainable ship energy systems. However, enhancing durability is essential to enable their broader adoption in the maritime sector. Durability enhancement depends on a thorough understanding of degradation mechanisms and accurate prognostics, both of which are highly application-specific. The current literature lacks a comprehensive understanding of LT-PEMFC degradation under maritime operating conditions and its integration into reliable prognostic models. To address this gap, this review provides an overview of LT-PEMFC durability and prognostic models from the perspective of maritime applications. Through a comparative analysis of studies across various sectors, we identify and discuss maritime-specific degradation drivers, including ship load profiles, sodium chloride contamination, vibrations, and wave-induced inclinations. Building on this analysis, we critically evaluate existing prognostic models and their suitability for lifetime prediction in maritime applications. This review proposes durability enhancement strategies based on current knowledge and highlights key research gaps requiring further investigation. In addition, it outlines promising prognostic methodologies and identifies technical challenges for application to maritime LT-PEMFCs. In this way, this work lays the foundation for enhancing LT-PEMFC durability in maritime environments and supporting its broader adoption for zero-emission ships.
{"title":"Durability and prognostic modelling of low-temperature polymer electrolyte membrane fuel cells in maritime applications: A review","authors":"Sara Tamburello, Lindert van Biert, Andrea Coraddu","doi":"10.1016/j.ecmx.2026.101576","DOIUrl":"10.1016/j.ecmx.2026.101576","url":null,"abstract":"<div><div>Low-Temperature Polymer Electrolyte Membrane Fuel Cells (LT-PEMFCs) have recently emerged as a promising solution for sustainable ship energy systems. However, enhancing durability is essential to enable their broader adoption in the maritime sector. Durability enhancement depends on a thorough understanding of degradation mechanisms and accurate prognostics, both of which are highly application-specific. The current literature lacks a comprehensive understanding of LT-PEMFC degradation under maritime operating conditions and its integration into reliable prognostic models. To address this gap, this review provides an overview of LT-PEMFC durability and prognostic models from the perspective of maritime applications. Through a comparative analysis of studies across various sectors, we identify and discuss maritime-specific degradation drivers, including ship load profiles, sodium chloride contamination, vibrations, and wave-induced inclinations. Building on this analysis, we critically evaluate existing prognostic models and their suitability for lifetime prediction in maritime applications. This review proposes durability enhancement strategies based on current knowledge and highlights key research gaps requiring further investigation. In addition, it outlines promising prognostic methodologies and identifies technical challenges for application to maritime LT-PEMFCs. In this way, this work lays the foundation for enhancing LT-PEMFC durability in maritime environments and supporting its broader adoption for zero-emission ships.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101576"},"PeriodicalIF":7.6,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039764","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}
The urgent need to decarbonize high-emission sectors has driven the development of Power-to-X technologies, which convert renewable electricity into electrofuels (efuels). Despite their potential, efuel production faces challenges such as high energy demand and low conversion efficiency. Membrane reactors, which integrate reaction and separation, offer a promising solution by improving yields and reducing energy requirements. This review presents a scientometric analysis of membrane reactors for efuel production using the Scopus database from 2003 to 2024. Analyzing 30 publications, six thematic clusters were identified using VOSviewer and Bibliometrix. Keyword co-occurrence and factorial analyses highlight main research themes and emerging areas, revealing gaps in reactor configuration optimization. Influential studies show that membrane reactors can enhance CO2 conversion and methane yield compared to conventional systems, though challenges remain in membrane selectivity, economic viability, and long-term durability under real feedstock conditions. Additional issues include scalable module manufacturing and the lack of harmonized techno-economic, life cycle, and performance metrics. Sector-specific analysis identifies positive dynamics, such as compatibility with existing infrastructure, improved energy security, and supportive policies, as well as negative dynamics, including high production costs, resource competition, technological uncertainties, and new safety and regulatory requirements. By mapping research progress, this study provides insights to guide the advancement of membrane reactors and support sustainable efuel production and decarbonization goals.
{"title":"Navigating towards efuel: A scientometric insight into the application of membrane reactors","authors":"Rahbaar Yeassin , Prangon Chowdhury , Prithibi Das , Ephraim Bonah Agyekum , Omar Farrok , Pankaj Kumar","doi":"10.1016/j.ecmx.2026.101545","DOIUrl":"10.1016/j.ecmx.2026.101545","url":null,"abstract":"<div><div>The urgent need to decarbonize high-emission sectors has driven the development of Power-to-X technologies, which convert renewable electricity into electrofuels (efuels). Despite their potential, efuel production faces challenges such as high energy demand and low conversion efficiency. Membrane reactors, which integrate reaction and separation, offer a promising solution by improving yields and reducing energy requirements. This review presents a scientometric analysis of membrane reactors for efuel production using the Scopus database from 2003 to 2024. Analyzing 30 publications, six thematic clusters were identified using VOSviewer and Bibliometrix. Keyword co-occurrence and factorial analyses highlight main research themes and emerging areas, revealing gaps in reactor configuration optimization. Influential studies show that membrane reactors can enhance CO<sub>2</sub> conversion and methane yield compared to conventional systems, though challenges remain in membrane selectivity, economic viability, and long-term durability under real feedstock conditions. Additional issues include scalable module manufacturing and the lack of harmonized techno-economic, life cycle, and performance metrics. Sector-specific analysis identifies positive dynamics, such as compatibility with existing infrastructure, improved energy security, and supportive policies, as well as negative dynamics, including high production costs, resource competition, technological uncertainties, and new safety and regulatory requirements. By mapping research progress, this study provides insights to guide the advancement of membrane reactors and support sustainable efuel production and decarbonization goals.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"30 ","pages":"Article 101545"},"PeriodicalIF":7.6,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039760","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}
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