Energy Conversion and Management最新文献

{"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":"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":"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":"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}

{"title":"Research on virtual calibration technology for multi objective operating parameters of thermal management system based on thermodynamic indicators","authors":"Haoyuan Chen ,&nbsp;Kunfeng Liang ,&nbsp;Chunyan Gao ,&nbsp;Yunpeng Zhang ,&nbsp;Xun Zhou ,&nbsp;Bin Chen ,&nbsp;Chenguang Zhang ,&nbsp;Haolei Duan ,&nbsp;Shuopeng Li","doi":"10.1016/j.enconman.2025.119712","DOIUrl":"10.1016/j.enconman.2025.119712","url":null,"abstract":"<div><div>With the rapid development of battery electric vehicle, technical problems still exist, and an efficient and reliable thermal management system is a core challenge to improve vehicle performance.This study proposes a multi-mode directly-cooling thermal management system to meet temperature control requirements while optimizing energy efficiency, cost, and environmental impact. An experimental and simulation platform for the system was established as the data source, and a thermodynamic analysis architecture including three indicators was developed to evaluate the impact of different operating parameters on system performance using experimental data. The results show that a 5 °C increase in the system evaporation temperature reduced total energy loss by approximately 12.6 % and environmental impact by 4.65 %, while increasing costs by about 12 % in both modes, system has a set of optimal operating parameters under different operating modes. Under the guidance of thermodynamic analysis, three thermodynamic indicators and key operating parameters were optimized as objective functions and decision variables. The Non-dominated sorting genetic algorithm was applied to develop a multi-objective virtual calibration technology for system parameters, leading to an 18.2 % increase in exergy efficiency across both modes, along with reductions of 11.1 % in total cost rate and 30.9 % in environmental impact rate. Based on the AMESim platform, virtual calibration of optimized parameters demonstrates that the proposed scheme ensures temperature control performance while significantly improves energy efficiency, and reduces economic and environmental impacts, showing strong application potential.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119712"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619982","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":"Aerodynamics prediction of vertical-axis wind turbines based on meta learning under regional interactions","authors":"Rui Zhang ,&nbsp;Lingyu Zhan ,&nbsp;Redili Yushan ,&nbsp;Yaoran Chen ,&nbsp;Limin Kuang ,&nbsp;Yu Tu ,&nbsp;Zhaolong Han ,&nbsp;Dai Zhou","doi":"10.1016/j.enconman.2025.119727","DOIUrl":"10.1016/j.enconman.2025.119727","url":null,"abstract":"<div><div>Due to the difficulty in balancing efficiency and accuracy using traditional methods, an increasing number of deep learning models are being used to study the aerodynamic parameters of vertical-axis wind turbines. Nevertheless, interactions between the upwind and downwind regions of vertical-axis wind turbines were often ignored in this process, resulting in inaccurate outcomes. In a meta learning framework, this study proposes a novel deep learning model, called Meta-Double Long Short-Term Memory, to accurately predict aerodynamics of vertical-axis wind turbines. In this model, Double Long Short-Term Memory module utilizes the upwind region and downwind region models to characterize the interactions among regions, while model-agnostic meta-learning is used to capture knowledge across different datasets in a two-stage strategy. Experimental results indicate that this model outperforms other baselines with the lowest errors of 2.21 % and 1.85 % for the peak torque coefficient and the corresponding azimuthal angle, respectively. Global sensitivity analysis reveals that turbine rotational speed (<em>ω</em>) has the greatest impact on prediction results, while upwind aerodynamics and geometrical parameters also significantly affect downwind predictions. Additionally, the proposed model can effectively optimize turbine parameters and provides detailed time series of aerodynamic parameters for in-depth analysis. By using a meta-learning approach and considering regional interactions, the proposed model improves the accuracy of aerodynamic predictions for vertical-axis wind turbines, and its training methodology can be applied to other renewable energy systems.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601250","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":"Techno-economic and environmental impacts of hybridization and low-carbon fuels on heavy-duty trucks","authors":"Kangjie Liu ,&nbsp;Zhiyu Han ,&nbsp;Junbo Zhang ,&nbsp;Ziwei Tang ,&nbsp;Haifeng Tang","doi":"10.1016/j.enconman.2025.119634","DOIUrl":"10.1016/j.enconman.2025.119634","url":null,"abstract":"<div><div>Heavy-duty trucks account for a significant share of petroleum consumption and CO₂ emissions in the automotive sector. However, their transition to low-carbon renewable energy has lagged behind that of passenger vehicles. This study systematically evaluates the performance, energy consumption, total cost of ownership (TCO), and well-to-wheel (WTW) CO₂ emissions of various low-carbon fuel powertrains and fuel-electric hybrid systems for heavy-duty long-haul trucks. The fuels considered include liquefied natural gas (LNG), methanol, hydrogen, and electricity, while the hybrid systems evaluated are series, parallel, and series–parallel configurations. Design parameters of these diesel-electric hybrid systems were first optimized to achieve improved performance and cost-efficiency. The series–parallel design emerged as the most effective configuration and was subsequently applied to other fuel hybrid systems. The analysis revealed that hybrid trucks consistently outperformed conventional engine trucks in energy consumption, TCO, and CO₂ emissions across all fuel types. Diesel-, LNG- and methanol-electric hybrid trucks were more cost-effective than battery-electric trucks, underscoring hybridization as a pivotal technology for energy savings and emissions reduction in logistics. Hydrogen engine and hydrogen hybrid trucks exhibited higher TCOs compared to diesel-based systems, while LNG and methanol hybrid trucks offered the lowest TCOs, highlighting the economic barriers to widespread hydrogen adoption. The WTW CO₂ emissions were highly dependent on the production pathways of methanol and hydrogen. For instance, trucks fueled by coal gasification-derived hydrogen emitted 2.64 times the CO₂ of diesel trucks, whereas hydrogen produced from renewable electricity reduced CO₂ to just 29.3% of diesel levels. Similarly, coal-derived methanol increased CO₂ emissions by 3.95 times compared to diesel, while methanol synthesized from industrial CO₂ exhausts and hydrogen from coke oven gases achieved a 22.8% reduction. These findings highlight that transitioning heavy-duty trucks to methanol and hydrogen fuels requires a parallel shift toward sustainable, low-carbon fuel production methods to maximize environmental benefits.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119634"},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610882","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":"Efficiency enhancement of liquid air energy storage systems through ultra-high-temperature heat pump integration","authors":"Jiamin Du ,&nbsp;Xindong Wang ,&nbsp;Jiyun Liu ,&nbsp;Junxian Li ,&nbsp;Zhikang Wang ,&nbsp;Xiaoyu Fan ,&nbsp;Yihong Li ,&nbsp;Zhaozhao Gao ,&nbsp;Wei Ji ,&nbsp;Liubiao Chen ,&nbsp;Junjie Wang","doi":"10.1016/j.enconman.2025.119714","DOIUrl":"10.1016/j.enconman.2025.119714","url":null,"abstract":"<div><div>Liquid air energy storage is emerging as a promising technology for large-scale energy storage. It offers high energy density and geographical flexibility, making it an effective solution for grid peak shaving. However, the round-trip efficiency of standalone systems typically ranges from 50 % to 60 %, with insufficient utilization of compression heat being a key factor contributing to low efficiency. Enhancing the use of compression heat and increasing the reheat temperature during expansion are effective strategies for improving the performance of the system. This study proposes an innovative system that integrates an ultra-high-temperature heat pump unit with an organic Rankine cycle to address these challenges. The system leverages the ultra-high-temperature heat pump to upgrade compression heat, thereby raising the reheat temperature during the energy release phase and resolving the low reheat temperature issue common in traditional designs. Additionally, the organic Rankine cycle recovers and harnesses the waste heat from the compression process, generating additional power and improving the round-trip efficiency. A thermodynamic model was developed to design and optimize the system, achieving a round-trip efficiency of 63.14 %. Economic analysis further reveals that the dynamic payback period of the system is 6.82 years, with a net present value of 12.85 million USD over its operational lifespan, 2.13 times higher than that of standalone liquid air energy storage systems. These results demonstrate that the integrated system improves profitability and market competitiveness. By efficiently utilizing compression heat, the proposed system ensures safety, flexibility, and high efficiency, offering valuable insights for the development of large-scale standalone liquid air energy storage systems.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119714"},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610886","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":"Advances and future perspectives in thermoelectric cooling technology","authors":"Lei Wang ,&nbsp;Tianshu Chu ,&nbsp;Shuaishuai Yuan ,&nbsp;Peng Zou ,&nbsp;Wenchao Zhai ,&nbsp;Xiaobing Zheng ,&nbsp;Maopeng Xia","doi":"10.1016/j.enconman.2025.119621","DOIUrl":"10.1016/j.enconman.2025.119621","url":null,"abstract":"<div><div>Thermoelectric cooling technology has become a research hotspot due to its alignment with the growing demand for environmentally friendly solutions. Compared to traditional cooling methods, thermoelectric coolers (TECs) offer advantages such as compact size, lightweight, simple structure, and lack of vibration. These benefits allow for easy integration with various power devices and enable precise temperature control. However, TECs face challenges including limited temperature control range and low thermoelectric conversion efficiency. This review explores the latest advancements in TECs across material design, structural design, heat dissipation, and application areas to identify potential solutions. The exploration of room-temperature thermoelectric materials with extremely low lattice thermal conductivity, high Seebeck coefficients, and high electrical conductivity is crucial for enhancing TEC performance. Investigating novel TEC structures and reducing thermal resistance between the TEC’s hot side and the heat sink will improve cooling efficiency. Additionally, optimizing system integration designs for TECs can support low-cost, large-scale commercialization. This review outlines the challenges TECs will face in the future and provides possible solutions. Addressing these issues will significantly boost TECs’ competitiveness within the broader cooling technology landscape.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119621"},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620087","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}