Energy Conversion and Management最新文献

{"title":"Chance constrained optimal sizing of a hybrid PV/battery/hydrogen isolated microgrid: A life-cycle analysis","authors":"Ahmed R. El Shamy,&nbsp;Prince Aduama,&nbsp;Ameena S. Al-Sumaiti","doi":"10.1016/j.enconman.2025.119707","DOIUrl":"10.1016/j.enconman.2025.119707","url":null,"abstract":"<div><div>Isolated microgrids offer a great potential for capturing advancements in renewable energy sources (RES) and storage technologies. Prospects for such systems include industrial, commercial, and residential areas, where grid connection is not possible or not economical. Planning isolated microgrids must be accurate, such that it preserves system security and avoids resource oversizing. This paper introduces a microgrid, composed of multiple storage components and a solar PV system, with the goal to optimally size the PV plant, battery capacity, fuel cell rating, electrolyzer rating and hydrogen tank size to match the load demand and reduce the life cycle cost of the entire system. A PV plant is used as the main energy source, while battery and hydrogen storage systems provide the maneuvering needed for covering the periods of sun absence. To accommodate PV and load uncertainties due to weather conditions, a chance constrained (CC) optimal sizing mixed integer linear programming (MILP) problem is formulated. CC optimization provides a great window for stochasticity inclusion and sizing based on criticality level of application. To prove the fidelity of the results, the system is required to achieve at least 80 % success of 100 different scenarios generated for the modeled system. The results show the capacities of the various components needed to meet the load requirements of a microgrid with a PV source, hydrogen storage system and a battery energy storage system. The total life cycle cost of the system for a period of 25 years is found to be US$1.221 m.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119707"},"PeriodicalIF":9.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of equilibrium-based and kinetics-based models for evaluating the impact of hydrogen carrier reforming on SOFC system","authors":"Clyde-Theodore N. Batista ,&nbsp;Kazeem Ayodeji Mohammed ,&nbsp;Amirpiran Amiri ,&nbsp;Neda Azimi ,&nbsp;Robert Steinberger-Wilckens","doi":"10.1016/j.enconman.2025.119733","DOIUrl":"10.1016/j.enconman.2025.119733","url":null,"abstract":"<div><div>This paper evaluates the computational risks of using Equilibrium-Based Models (EBMs) and Kinetics-Based Models (KBMs) interchangeably for simulating the external reformer in Solid Oxide Fuel Cell (SOFC) Balance of Plant (BoP). Various reforming processes, including steam reforming, partial oxidation, and autothermal reforming of hydrocarbons are assessed. The study systematically investigates the effect of reformers operating parameters, such as temperature, pressure, steam-to-carbon ratio, and oxygen-to-carbon ratio, on SOFC performance captured by EBM and KBM. In contrast to EBM, the KBM consistently provided a more detailed and accurate measures of system behaviour. This is more evident, especially under conditions where reaction kinetics play a crucial role, such as in high-pressure scenarios or significant variations in the steam-to-carbon ratio. The KBM captured the details of reaction kinetics and mass transfer limitations that the EBM, with its inherent assumption of near-instantaneous equilibrium, could not fully replicate. While EBM is computationally effective for minimising modelling complexity/time at the system level, it has limitations in scenarios that require detailed reaction kinetics due to the nature of reaction or fuel mixture. EBM and KBM results deviations are quantified to identify regions where these risks are either significant or tolerable.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119733"},"PeriodicalIF":9.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Quantum machine learning based wind turbine condition monitoring: State of the art and future prospects","authors":"Zhefeng Zhang,&nbsp;Yueqi Wu,&nbsp;Xiandong Ma","doi":"10.1016/j.enconman.2025.119694","DOIUrl":"10.1016/j.enconman.2025.119694","url":null,"abstract":"<div><div>Wind energy, as a popular renewable resource, has gained extensive development and application in recent decades. Effective condition monitoring and fault diagnosis are crucial for ensuring the reliable operation of wind turbines. While conventional machine learning methods have been widely used in wind turbine condition monitoring, these approaches often face challenges such as complex feature extraction, limited model generalization, and high computational costs when dealing with large-scale, high-dimensional, and complex datasets. The emergence of quantum computing has opened up a new paradigm of machine learning algorithms. Quantum machine learning combines the advantages of quantum computing and machine learning, with the potential to surpass classical computational capabilities. This paper firstly reviews applications and limitations of the state-of-the-art machine learning-based condition monitoring techniques for wind turbines. It then reviews the fundamentals of quantum computing, quantum machine learning algorithms and their applications, covering quantum-based feature extraction, classification and regression for fault detection and the use of quantum neural networks for predictive maintenance. Through comparison, it is observed that quantum machine learning methods, even without extensive optimization, can achieve accuracy levels comparable to those of optimized conventional machine learning approaches. The challenges of applying quantum machine learning are also addressed, along with the future research and development prospects. The objective of this review is to fill a gap in the published literature by providing a new paradigm approach for wind turbine condition monitoring. By promoting quantum machine learning in this field, the reliability and efficiency of wind power systems are ultimately sought to be enhanced.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119694"},"PeriodicalIF":9.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Proposal and analysis of an energy storage system integrated hydrogen energy storage and Carnot battery","authors":"Ju Guan ,&nbsp;Wei Han ,&nbsp;Qibin Liu ,&nbsp;Fan Jiao ,&nbsp;Wenjing Ma","doi":"10.1016/j.enconman.2025.119734","DOIUrl":"10.1016/j.enconman.2025.119734","url":null,"abstract":"<div><div>As renewable energy capacity continues to surge, the volatility and intermittency of its generation poses a mismatch between supply and demand when aligned with the fluctuating user load. Consequently, there’s a pressing need for the development of large-scale, high-efficiency, rapid-response, long-duration energy storage system. This study presents a novel integrated energy storage system combining hydrogen energy storage and Carnot battery. Carnot battery serves as the base load for stable, large-scale energy storage, while hydrogen energy storage (PEMEC and SOFC) serves as the regulated load to flexibly absorbs excess renewable electricity and responds promptly to user demand. The integrated system also effectively leverages high-temperature waste from the SOFC to boost Carnot battery’s round-trip efficiency (RTE), enhancing overall system RTE. Energy and exergy analyses are conducted for both the proposed system and a reference system. Results indicate that the proposed system achieves an overall RTE of 57.48% and an RTE of 71.98% for the Carnot Battery, improvements of 5.71% and 11.32%, respectively, compared to the reference system. The mechanisms underlying the efficiency improvements are analyzed, and the impact of capacity allocation between hydrogen storage and the Carnot battery on overall system performance is explored.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119734"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Boosting electrical efficiency in hybrid energy harvesters by scavenging ambient thermal and mechanical energy","authors":"Arun Mondal,&nbsp;Amish Kumar Gautam,&nbsp;Neeraj Khare","doi":"10.1016/j.enconman.2025.119739","DOIUrl":"10.1016/j.enconman.2025.119739","url":null,"abstract":"<div><div>The generation of electricity by hybrid energy harvesting devices would be a desirable approach to improve power efficiencies due to their ability to utilize multiple energy sources simultaneously. However, to achieve the improved efficiency from the hybrid device, the power outputs of two individual devices need to be comparable. Here, a single hybrid device has been fabricated, which combines triboelectric nanogenerator (TENG) and thermoelectric generator (TEG) and is capable of harvesting both thermal and mechanical energy, simultaneously. The TEG part of the hybrid device generates a maximum power density of ∼ 35 μW/cm² at a ΔT of ∼ 12.5 K, whereas the TENG part of the hybrid device also separately generated a maximum power density of ∼ 32 μW/cm². The comparable power density of the thermoelectric and triboelectric devices makes the hybrid device more efficient. The output power density of the individual TENG and TEG devices shows significantly higher performances as compared to the outputs reported in previous works. The individual performances of the TENG and TEGs further simulated using COMSOL MULTIPHYSICS 5.5 and compared with the experimental results. The hybrid device charged the capacitor (1 μF, 63 V) up to a voltage of 13 V at a rate of 163 mV/sec in 80 sec, which is about 37 % and 2067 % higher as compared to the individual performance of the TENG and TEG, respectively. The practical application of the hybrid device is demonstrated by powering a digital calculator. Thus, the use of a present hybrid device having a comparable individual power density can be used to harness the ambient energy.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119739"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A molten salt-mediated biomass gasification process for high-yield hydrogen production with in situ carbon capture: experiments, simulation and ANN prediction","authors":"Aoyang Zhang ,&nbsp;Dongfang Li ,&nbsp;Xing Zhu ,&nbsp;Gyeong-min Kim ,&nbsp;Yijie Zeng ,&nbsp;Chung-hwan Jeon ,&nbsp;Hua Wang ,&nbsp;Tao Zhu ,&nbsp;Guirong Bao","doi":"10.1016/j.enconman.2025.119735","DOIUrl":"10.1016/j.enconman.2025.119735","url":null,"abstract":"<div><div>Biomass gasification is a promising technology for green hydrogen production. In this study, a molten salt-mediated biomass gasification process with in situ carbon capture for hydrogen-rich syngas production is proposed and analyzed via experiments, process simulation and ANN modeling. The process utilizes molten salts as a solar energy carrier, with the entire system’s heat requirements fulfilled through solar energy, thereby increasing the gas yield per unit biomass. CaO is added to the process to facilitate in situ CO₂ capture and enhance the WGS reaction, enabling simultaneous CO₂ sequestration and increased hydrogen production in the syngas. Key operational parameters such as temperature, calcium-to-carbon (Ca/C) molar ratio, and steam-to-carbon (S/C) molar ratio are experimentally investigated. Results indicate a hydrogen composition of 68.67 vol% at 600 °C, with optimal Ca/C and S/C ratios of 1:1.5 and 1:1, respectively. A quasi-steady-state model developed in Aspen Plus is verified with experimental data, and a full loop model identifies an optimal molten salt-to-biomass (M/B) mass ratio of 2.40. Additionally, an artificial neural network was employed to predict the relationship between key operational parameters and hydrogen yield. The best-performing model, ANN12, achieved a high coefficient of determination (R² = 0.99587). This process allows for simultaneous hydrogen production and carbon capture, offering an efficient method for green hydrogen generation with negative carbon emissions.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119735"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring microalgae species for integrated bioenergy Production: A Multi-Fuel cascade valorisation approach","authors":"Joana Oliveira ,&nbsp;Sara Pardilhó ,&nbsp;Emanuel Costa ,&nbsp;José C. Pires ,&nbsp;Joana Maia Dias","doi":"10.1016/j.enconman.2025.119736","DOIUrl":"10.1016/j.enconman.2025.119736","url":null,"abstract":"<div><div>The present study aims to evaluate the cascade valorisation of microalgae for bioenergy production after defining the most promising species between <em>Aurantiochytrium</em> sp., <em>Scenedesmus obliquus</em>, <em>Nannochloropsis oceanica</em>, and <em>Nannochloropsis</em> sp.. For selection, biodiesel (after hexane lipid extraction coupled with cell-disruption methods) and bioethanol (after acid hydrolysis) were produced from raw biomass. <em>Aurantiochytrium</em> sp. achieved the highest oil and FAME contents (21 ± 1 wt% and 58.9 ± 0.6 wt%, respectively), as well as the highest bioethanol concentration (5.4 ± 0.3 g/L). The integrated production of biodiesel, bioethanol and biogas led to a decrease in bioethanol and biogas production efficiency compared to raw biomass (around 30 % and 60 %, respectively). However, it allows multiple product outputs, potentially improving economic and environmental outcomes. The current study highlights the potential of using microalgae species such as <em>Aurantiochytrium</em> sp. for bioenergy production, in a zero-waste approach.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119736"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of co-generative and synergistic desalination & refrigeration systems for sustainable development applications","authors":"Gayatri Sundar Rajan ,&nbsp;Seda Zeynep Keleş ,&nbsp;Christian D. Peters ,&nbsp;Binjian Nie ,&nbsp;Hiba Bensalah ,&nbsp;Nicholas P. Hankins","doi":"10.1016/j.enconman.2025.119717","DOIUrl":"10.1016/j.enconman.2025.119717","url":null,"abstract":"<div><div>Within the water-energy-food nexus, desalination and refrigeration cogeneration systems are able to address pressing sustainable development goals. Such systems exploit the synergy between the two processes to yield mutual benefits. This review evaluates existing cogeneration studies to recommend promising research directions for sustainable development applications such as simultaneous freshwater production and cold storage refrigeration. Compared to recent reviews of combined desalination and cooling systems, the novelty of this review is in its focus on refrigeration temperatures suitable for fresh food storage (between 0–15 °C), differentiating hybrid systems as Integrated or Coupled, and highlighting the potential technical and economic synergies between refrigeration and desalination systems for sustainable development applications. The key aspects examined included (1) capacity of desalination and refrigeration, (2) source of water and potential contaminants, (3) system design and synergies, (4) efficiency of energy and material resources, and (5) integration with renewable energy sources. The primary synergy in integrated systems was the simultaneous low-temperature evaporation of water and chilling of a cooling fluid. In coupled systems, the synergy comes from the usage of waste heat from refrigeration systems to drive thermal desalination processes. Regarding performance, the systems with the highest water recovery rates and thermal desalination efficiencies are hybrid multiple effect distillation systems. Promising directions for future research include experimentally validating numerically derived inferences, achieving deeper heat integration to improve system efficiency, and developing passive measures such as indirect evaporative cooling for simultaneous dehumidification, cooling, and water production.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119717"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Benchmarking reinforcement learning and prototyping development of floating solar power system: Experimental study and LSTM modeling combined with brown-bear optimization algorithm","authors":"Mohamed E. Zayed ,&nbsp;Shafiqur Rehman ,&nbsp;Ibrahim A. Elgendy ,&nbsp;Ali Al-Shaikhi ,&nbsp;Mohamed A. Mohandes ,&nbsp;Kashif Irshad ,&nbsp;A.S. Abdelrazik ,&nbsp;Mohamed Azad Alam","doi":"10.1016/j.enconman.2025.119696","DOIUrl":"10.1016/j.enconman.2025.119696","url":null,"abstract":"<div><div>This study conducts comprehensive comparative experimental investigation, performance assessment analysis, and enhanced artificial intelligence (AI) modeling of solar floating photovoltaic (SFPV) and ground-mounted solar PV (GSPV) systems. Both systems—SFPV and GSPV—are installed, tested, and compared under identical harsh environmental conditions in Bahrain’s Gulf, in Al-Khobar, Saudi Arabia, with a detailed assessment of electric power output, PV panel surface temperature, PV DC voltage, and current, as well as energy yield and efficiency. More so, a hybrid artificial intelligence framework integrating Light Gradient-Boosting Machine (LightGBM), Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) models, fine-tuned through the utilization of an innovative Brown Bear Optimization Algorithm (BBOA) are also developed to forecast electrical power generation and PV panel surface temperature for both SFPV and GSPV systems. The experiments indicate that the SFPV system improved the average PV electrical power and accumulated net daily electrical energy by 59.25% and 69.70%, as well as reduced the PV panel surface temperature by 32.36% compared to that of the SGPV system, respectively. Moreover, statistical evaluations highlighted the LSTM-BBOA model achieved superior robustness over the investigated AI models (LGBM-BBOA, GRU, LSTM, LGBM) in performance prediction, evidenced by the maximal determination coefficient (R²) of 0.9998 and 0.9999, and the minimal RMSE values of 0.5031 and 0.0007 for predicting the SFPV’s electric power and module surface panel temperature, respectively. Conclusively, the study provides valuable insights into the benchmarking of AI techniques for improving smart-grid integration and operational efficiency of floating solar installations, aligning with the innovation objectives of sustainable energy development.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119696"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Built-in metallic partitions in solar chimney: Structural design and thermo-hydraulic performance analysis","authors":"Jing Nie,&nbsp;Jinchen Xu,&nbsp;Tongzheng Guo,&nbsp;Jiawei Wang,&nbsp;Jing Jia,&nbsp;Hong Gao","doi":"10.1016/j.enconman.2025.119718","DOIUrl":"10.1016/j.enconman.2025.119718","url":null,"abstract":"<div><div>This study introduces a solar chimney design incorporating built-in metallic partitions to enhance convective heat transfer between fluids and solids. Based on the Manzanares prototype, numerical simulations were conducted to analyze the effects of solar radiation intensity, turbine pressure drop, and ambient temperature on flow fields and thermo-hydraulic performance. A response surface methodology was employed to develop an output power prediction model. Results indicate that metallic partitions significantly improve thermal efficiency, with relative increase rates of 9.28 % in power output and 21.61 % in collector efficiency compared to the prototype at specific operating conditions, and achieving a maximum output power of 89.607 kW under specific conditions (SR = 1000 W/m², ΔP = 140 Pa, ambient temperature = 308 K). The system demonstrates robust operation under low radiation and high ΔP conditions. Cost-effective strategies, such as aluminum-steel composite structures and honeycomb perforated designs integrated with modular manufacturing, are proposed to reduce material costs while maintaining high heat transfer efficiency. This approach eliminates the need for large-scale ground modifications, preserves structural simplicity, and offers a novel solution for efficient, low-cost deployment in large-scale solar chimney power plants.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119718"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}