Energy最新文献 - Book学术

A compensation strategy to improve gas-solid heat transfer without sacrificing kinetic energy in a cyclone pyrolyzer

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-04-02 DOI: 10.1016/j.energy.2025.135952

Nan Zhang , Xueer Pan , Jingxuan Yang , Wenhao Lian , Tiancheng Fang , Zhonglin Zhang , Xiaogang Hao , Abuliti Abudula , Guoqing Guan , Huiling Fan

The enhancement of the gas-solid heat transfer process is usually accompanied by an increase in kinetic energy consumption in a cyclone pyrolyzer. Unfortunately, in the current literature, there are few reports on how to improve the gas-solid heat transfer process without increasing the kinetic energy consumption. In response to these challenges, a compensation strategy was proposed to globally optimize the flow properties in cyclone pyrolyzer. Concretely, increasing the thermal resistance of the localized low thermal resistance region to compensate for the high thermal resistance region, achieving a more uniform thermal resistance distribution, thereby optimizing the overall flow and heat transfer properties. In this work, the exhaust pipe insert depth (S = 30, 45, 60, and 90 mm) was used to regulate gas-solid flow behaviors in a cyclone pyrolyzer. The heat transfer process and its control mechanism are systematically studied using the Computational fluid dynamics-Discrete element method (CFD-DEM). Results show that the extension of S increases the final temperature of the coal particles by 21.6 %, while reducing the pressure drop and kinetic energy consumption. Furthermore, by analyzing the gas-solid flow behavior, it was found that the extension of S can improve the gas flow field and synergy characteristics. These results are expected to provide theoretical guidance for improving the heat transfer efficiency in the cyclone pyrolyzer.

{"title":"A compensation strategy to improve gas-solid heat transfer without sacrificing kinetic energy in a cyclone pyrolyzer","authors":"Nan Zhang , Xueer Pan , Jingxuan Yang , Wenhao Lian , Tiancheng Fang , Zhonglin Zhang , Xiaogang Hao , Abuliti Abudula , Guoqing Guan , Huiling Fan","doi":"10.1016/j.energy.2025.135952","DOIUrl":"10.1016/j.energy.2025.135952","url":null,"abstract":"<div><div>The enhancement of the gas-solid heat transfer process is usually accompanied by an increase in kinetic energy consumption in a cyclone pyrolyzer. Unfortunately, in the current literature, there are few reports on how to improve the gas-solid heat transfer process without increasing the kinetic energy consumption. In response to these challenges, a compensation strategy was proposed to globally optimize the flow properties in cyclone pyrolyzer. Concretely, increasing the thermal resistance of the localized low thermal resistance region to compensate for the high thermal resistance region, achieving a more uniform thermal resistance distribution, thereby optimizing the overall flow and heat transfer properties. In this work, the exhaust pipe insert depth (<em>S</em> = 30, 45, 60, and 90 mm) was used to regulate gas-solid flow behaviors in a cyclone pyrolyzer. The heat transfer process and its control mechanism are systematically studied using the Computational fluid dynamics-Discrete element method (CFD-DEM). Results show that the extension of <em>S</em> increases the final temperature of the coal particles by 21.6 %, while reducing the pressure drop and kinetic energy consumption. Furthermore, by analyzing the gas-solid flow behavior, it was found that the extension of <em>S</em> can improve the gas flow field and synergy characteristics. These results are expected to provide theoretical guidance for improving the heat transfer efficiency in the cyclone pyrolyzer.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135952"},"PeriodicalIF":9.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760823","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}

引用次数: 0

Research on fuel injection quantity fluctuation characteristics and optimization improvement of dual-fuel engines

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-04-02 DOI: 10.1016/j.energy.2025.135953

Longguo He, Wanru Gong, Jianhui Zhao

The fluctuation of fuel injection quantity directly affects the power and economy of dual-fuel engines. Identifying key factors causing these fluctuations and improving injection stability are essential for better economy and emissions performance. This paper constructs and validates a high-pressure fuel injection system simulation model using a test platform. It examines the relationship between injection quantity fluctuations and needle action, finding that low injection pressure and narrow pulse width prevent rapid and full needle opening, leading to higher injection quantity fluctuation rate (IQFR). Specifically, low injection pressure reduces needle acceleration, while narrow pulse width limits needle ascent time. A data-driven model of IQFR is established using generalized regression neural network (GRNN) in combination with grey wolf optimizer (GWO). An optimization and improvement study is then carried out with the objective of reducing the fluctuation rate of the injection quantity. The results demonstrate that the maximum lift of the needle is diminished from 0.25 mm to 0.16 mm without a concomitant reduction in the maximum injection rate. The IQFR is diminished by a maximum of 13.3 % across the full range of operating conditions, achieving an enhancement in injection stability under conditions of low injection pressure and narrow injection pulse width.

{"title":"Research on fuel injection quantity fluctuation characteristics and optimization improvement of dual-fuel engines","authors":"Longguo He, Wanru Gong, Jianhui Zhao","doi":"10.1016/j.energy.2025.135953","DOIUrl":"10.1016/j.energy.2025.135953","url":null,"abstract":"<div><div>The fluctuation of fuel injection quantity directly affects the power and economy of dual-fuel engines. Identifying key factors causing these fluctuations and improving injection stability are essential for better economy and emissions performance. This paper constructs and validates a high-pressure fuel injection system simulation model using a test platform. It examines the relationship between injection quantity fluctuations and needle action, finding that low injection pressure and narrow pulse width prevent rapid and full needle opening, leading to higher injection quantity fluctuation rate (<em>IQFR</em>). Specifically, low injection pressure reduces needle acceleration, while narrow pulse width limits needle ascent time. A data-driven model of <em>IQFR</em> is established using generalized regression neural network (GRNN) in combination with grey wolf optimizer (GWO). An optimization and improvement study is then carried out with the objective of reducing the fluctuation rate of the injection quantity. The results demonstrate that the maximum lift of the needle is diminished from 0.25 mm to 0.16 mm without a concomitant reduction in the maximum injection rate. The <em>IQFR</em> is diminished by a maximum of 13.3 % across the full range of operating conditions, achieving an enhancement in injection stability under conditions of low injection pressure and narrow injection pulse width.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135953"},"PeriodicalIF":9.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760856","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}

引用次数: 0

Firm power generation with photovoltaic overbuilding and pumped hydro storage

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-04-02 DOI: 10.1016/j.energy.2025.135800

Qi Gao , Yun Chen , Dazhi Yang , Hao Zhang , Guoming Yang , Yanbo Shen , Xiang’ao Xia , Bai Liu

The term “firm power generation” is synonymous with “effectively dispatchable solar power.” Indeed, solar power is variable by nature but can be firmed up through various technologies, such as storage, generation blending, or demand response, which can modify the generation and/or load profiles such that they eventually coincide with each other. In this work, two major innovations are presented. First, by virtue of its long-term storage capacity, pumped hydro storage (PHS) is proposed as a viable alternative to conventional battery storage. Second, contrary to traditional practices that minimize curtailment, photovoltaic (PV) systems are deliberately overbuilt and proactively curtailed. Both strategies are demonstrated to reduce the overall cost of firm energy systems. From a modeling perspective, it is argued that the simplified PV and PHS modeling could lead to an overconfident configuration. To that end, a refined configuration model, which integrates the model-chain-based solar power curve for PV and nonlinear hydraulic losses for PHS, is presented. A case study in northern China demonstrates that the simplified PV and PHS models tend to underestimate the equivalent annual cost of the system by 5.79%. Notably, the optimal system configuration suggests an overbuilding ratio of 1.33, validating the effectiveness of overbuilding and proactive curtailment. Additionally, when 5% of peak load is shifted to periods of low demand, the system cost remains nearly unchanged, highlighting the role of PHS in providing long-term storage capacity.

{"title":"Firm power generation with photovoltaic overbuilding and pumped hydro storage","authors":"Qi Gao , Yun Chen , Dazhi Yang , Hao Zhang , Guoming Yang , Yanbo Shen , Xiang’ao Xia , Bai Liu","doi":"10.1016/j.energy.2025.135800","DOIUrl":"10.1016/j.energy.2025.135800","url":null,"abstract":"<div><div>The term “firm power generation” is synonymous with “effectively dispatchable solar power.” Indeed, solar power is variable by nature but can be firmed up through various technologies, such as storage, generation blending, or demand response, which can modify the generation and/or load profiles such that they eventually coincide with each other. In this work, two major innovations are presented. First, by virtue of its long-term storage capacity, pumped hydro storage (PHS) is proposed as a viable alternative to conventional battery storage. Second, contrary to traditional practices that minimize curtailment, photovoltaic (PV) systems are deliberately overbuilt and proactively curtailed. Both strategies are demonstrated to reduce the overall cost of firm energy systems. From a modeling perspective, it is argued that the simplified PV and PHS modeling could lead to an overconfident configuration. To that end, a refined configuration model, which integrates the model-chain-based solar power curve for PV and nonlinear hydraulic losses for PHS, is presented. A case study in northern China demonstrates that the simplified PV and PHS models tend to underestimate the equivalent annual cost of the system by 5.79%. Notably, the optimal system configuration suggests an overbuilding ratio of 1.33, validating the effectiveness of overbuilding and proactive curtailment. Additionally, when 5% of peak load is shifted to periods of low demand, the system cost remains nearly unchanged, highlighting the role of PHS in providing long-term storage capacity.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135800"},"PeriodicalIF":9.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760913","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}

引用次数: 0

Multi-objective optimization analysis of on-demand design in multi-source heating system for low carbon development

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-04-02 DOI: 10.1016/j.energy.2025.135917

Weichen Wang , Jingchao Sun , Su Yan , Yuxing Yuan , Tianshun Xiao , Baoqi Chen , Tao Du , Hongming Na

A multi-energy complementary heating system (MEHS) is essential for the development of low-carbon building heating. However, limited research has been conducted on the optimal heat load allocation. In light of heat balancing, heat source operation, and energy resource limits, this study proposes a MEHS model based on life cycle assessment, with costs, CO₂ emissions, and energy efficiency serving as the objective functions. By optimizing, the Pareto frontier solution is obtained, and the relationships between the objective and the heat load allocation ratios of heating subsystems are analyzed. Finally, the impact of the power industry's low-carbon transition and increasing carbon trading prices on the MEHS is investigated. The results show that the optimal heat load allocation ratios for the air source heat pump, natural gas-fired, biomass-fired, coal-fired, thermal storage electric boiler, and ground source heat pump heating subsystems are 44.42 %, 13.41 %, 0.71 %, 32.18 %, 0.56 %, and 8.72 %, respectively. Costs and CO₂ emissions during operation account for more than 80 % of the total life cycle impact. CO₂ emissions can be reduced by 16 % when the power grid CO₂ emission factor is reduced to 0.2530 kg CO₂/kWh, and by 4.5 % when the carbon price increases to 200 CNY/t.

多能源互补供热系统（MEHS）对于低碳建筑供热的发展至关重要。然而，关于热负荷优化分配的研究还很有限。针对热平衡、热源运行和能源资源限制等问题，本研究提出了基于生命周期评估的多能源互补供热系统模型，以成本、二氧化碳排放和能效为目标函数。通过优化，得到帕累托前沿解，并分析了目标与供热子系统热负荷分配比例之间的关系。最后，研究了电力行业低碳转型和碳交易价格不断上涨对 MEHS 的影响。结果表明，空气源热泵、天然气、生物质、燃煤、蓄热式电锅炉和地源热泵供暖子系统的最佳热负荷分配比例分别为 44.42 %、13.41 %、0.71 %、32.18 %、0.56 % 和 8.72 %。运行期间的成本和二氧化碳排放量占整个生命周期影响的 80% 以上。当电网二氧化碳排放系数降低到 0.2530 千克二氧化碳/千瓦时时，二氧化碳排放量可减少 16%；当碳价格提高到 200 元人民币/吨时，二氧化碳排放量可减少 4.5%。

{"title":"Multi-objective optimization analysis of on-demand design in multi-source heating system for low carbon development","authors":"Weichen Wang , Jingchao Sun , Su Yan , Yuxing Yuan , Tianshun Xiao , Baoqi Chen , Tao Du , Hongming Na","doi":"10.1016/j.energy.2025.135917","DOIUrl":"10.1016/j.energy.2025.135917","url":null,"abstract":"<div><div>A multi-energy complementary heating system (MEHS) is essential for the development of low-carbon building heating. However, limited research has been conducted on the optimal heat load allocation. In light of heat balancing, heat source operation, and energy resource limits, this study proposes a MEHS model based on life cycle assessment, with costs, CO<sub>2</sub> emissions, and energy efficiency serving as the objective functions. By optimizing, the Pareto frontier solution is obtained, and the relationships between the objective and the heat load allocation ratios of heating subsystems are analyzed. Finally, the impact of the power industry's low-carbon transition and increasing carbon trading prices on the MEHS is investigated. The results show that the optimal heat load allocation ratios for the air source heat pump, natural gas-fired, biomass-fired, coal-fired, thermal storage electric boiler, and ground source heat pump heating subsystems are 44.42 %, 13.41 %, 0.71 %, 32.18 %, 0.56 %, and 8.72 %, respectively. Costs and CO<sub>2</sub> emissions during operation account for more than 80 % of the total life cycle impact. CO<sub>2</sub> emissions can be reduced by 16 % when the power grid CO<sub>2</sub> emission factor is reduced to 0.2530 kg CO<sub>2</sub>/kWh, and by 4.5 % when the carbon price increases to 200 CNY/t.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135917"},"PeriodicalIF":9.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760911","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}

引用次数: 0

Design and multi-objective optimization of co-production system of hydrogen and electricity via integration of methanol steam reforming, fuel cell and electrochemical hydrogen pump

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-04-02 DOI: 10.1016/j.energy.2025.135924

Andi Cheng , Huijun Yi , Wu Xiao , Xuehua Ruan , Xiaobin Jiang , Gaohong He

In this work, a distributed co-production system of electricity and hydrogen based on electrochemical hydrogen pump (EHP) enhancement was proposed to simultaneously meet user electricity and hydrogen demands. Methanol reformate gas was used to generate power through fuel cells firstly, and then entered EHP to produce pressurized hydrogen, which improving the utilization value of hydrogen, and realizing cascade utilization of hydrogen with different concentrations. Subsequently, a total of 46 datasets were designed based on the Box-Behnken Design, and a response surface surrogate model with 4 responses, 5 factors, and 3 levels was established for the analysis of multi-parameter interaction of the entire system. Furtherly, the multi-objective optimization of system net power, annual hydrogen production, levelized cost of electricity, and hydrogen was carried out using the NSGA-II, which appropriate solution under different application scenarios were selected by LINMAP and TOPSIS methods, which showed that the novel co-production system achieved an levelized cost of electricity and hydrogen are 0.1–0.19 $/kW∙h and 2.2–8.15 $/kgH₂, offering a reliable solution for processes enhancing in future distributed energy systems.

本研究提出了一种基于电化学氢泵（EHP）增强技术的分布式电氢联产系统，可同时满足用户的用电和用氢需求。甲醇重整气首先通过燃料电池发电，然后进入 EHP 产生加压氢气，提高了氢气的利用价值，实现了不同浓度氢气的梯级利用。随后，基于盒-贝肯设计（Box-Behnken Design）共设计了 46 个数据集，并建立了 4 个响应、5 个因子和 3 个水平的响应面代用模型，用于分析整个系统的多参数交互作用。此外，还利用 NSGA-II 对系统净功率、氢气年产量、电力和氢气的平准化成本进行了多目标优化，并通过 LINMAP 和 TOPSIS 方法选择了不同应用场景下的合适方案，结果表明新型联产系统的电力和氢气平准化成本分别为 0.1-0.19 美元/kW∙h 和 2.2-8.15 美元/kgH2，为未来分布式能源系统中的工艺提升提供了可靠的解决方案。

{"title":"Design and multi-objective optimization of co-production system of hydrogen and electricity via integration of methanol steam reforming, fuel cell and electrochemical hydrogen pump","authors":"Andi Cheng , Huijun Yi , Wu Xiao , Xuehua Ruan , Xiaobin Jiang , Gaohong He","doi":"10.1016/j.energy.2025.135924","DOIUrl":"10.1016/j.energy.2025.135924","url":null,"abstract":"<div><div>In this work, a distributed co-production system of electricity and hydrogen based on electrochemical hydrogen pump (EHP) enhancement was proposed to simultaneously meet user electricity and hydrogen demands. Methanol reformate gas was used to generate power through fuel cells firstly, and then entered EHP to produce pressurized hydrogen, which improving the utilization value of hydrogen, and realizing cascade utilization of hydrogen with different concentrations. Subsequently, a total of 46 datasets were designed based on the Box-Behnken Design, and a response surface surrogate model with 4 responses, 5 factors, and 3 levels was established for the analysis of multi-parameter interaction of the entire system. Furtherly, the multi-objective optimization of system net power, annual hydrogen production, levelized cost of electricity, and hydrogen was carried out using the NSGA-II, which appropriate solution under different application scenarios were selected by LINMAP and TOPSIS methods, which showed that the novel co-production system achieved an levelized cost of electricity and hydrogen are 0.1–0.19 $/kW∙h and 2.2–8.15 $/kgH<sub>2</sub>, offering a reliable solution for processes enhancing in future distributed energy systems.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135924"},"PeriodicalIF":9.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760914","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}

引用次数: 0

Molecular scale crystallization dynamic characteristics and melting mechanism of carbon dioxide

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-04-01 DOI: 10.1016/j.energy.2025.135923

Zhaoxi Wang , Yue Wang , Hengguang Cao , Bingbing Wang , Qian Li , Jiang Bian , Yihuai Hua , Weihua Cai

Clarifying the microscopic phase transition characteristics of carbon dioxide (CO₂) crystallization and melting is of significant theoretical importance for regulating the solid-liquid phase transition behavior of CO₂ in natural gas liquefaction process. This study employs molecular dynamics simulations to investigate the microscopic processes of the crystallization growth of supercooled liquid CO₂ under different pressure conditions, as well as the dynamic characteristics of the melting phase transition in solid CO₂. The results indicate that during crystallization, the CO₂ molecules undergo a liquid-to-solid reconfiguration, with carbon atoms forming a lattice arrangement dominated by face-centered cubic (FCC), accompanied by the coexistence of metastable body-centered cubic (BCC) and hexagonal close-packed (HCP) configurations, suggesting a competitive mechanism among multiple crystal phases during crystallization. Additionally, the melting behavior of solid CO₂ is influenced by the volume of the amorphous atomic regions and the void region, with the melting temperature exhibiting pressure independence and an average value of 215 ± 7.46 K, deviating by only 0.73 % from the equilibrium melting temperature. During melting, the regions containing amorphous atoms gradually expand, and the outward expansion of these disordered regions disrupts the surrounding ordered crystal structure, thereby accelerating the melting process.

{"title":"Molecular scale crystallization dynamic characteristics and melting mechanism of carbon dioxide","authors":"Zhaoxi Wang , Yue Wang , Hengguang Cao , Bingbing Wang , Qian Li , Jiang Bian , Yihuai Hua , Weihua Cai","doi":"10.1016/j.energy.2025.135923","DOIUrl":"10.1016/j.energy.2025.135923","url":null,"abstract":"<div><div>Clarifying the microscopic phase transition characteristics of carbon dioxide (CO<sub>2</sub>) crystallization and melting is of significant theoretical importance for regulating the solid-liquid phase transition behavior of CO<sub>2</sub> in natural gas liquefaction process. This study employs molecular dynamics simulations to investigate the microscopic processes of the crystallization growth of supercooled liquid CO<sub>2</sub> under different pressure conditions, as well as the dynamic characteristics of the melting phase transition in solid CO<sub>2</sub>. The results indicate that during crystallization, the CO<sub>2</sub> molecules undergo a liquid-to-solid reconfiguration, with carbon atoms forming a lattice arrangement dominated by face-centered cubic (FCC), accompanied by the coexistence of metastable body-centered cubic (BCC) and hexagonal close-packed (HCP) configurations, suggesting a competitive mechanism among multiple crystal phases during crystallization. Additionally, the melting behavior of solid CO<sub>2</sub> is influenced by the volume of the amorphous atomic regions and the void region, with the melting temperature exhibiting pressure independence and an average value of 215 ± 7.46 K, deviating by only 0.73 % from the equilibrium melting temperature. During melting, the regions containing amorphous atoms gradually expand, and the outward expansion of these disordered regions disrupts the surrounding ordered crystal structure, thereby accelerating the melting process.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135923"},"PeriodicalIF":9.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760858","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}

引用次数: 0

Comprehensive tradeoff and utilization of airborne renewable energy and uncertain stratospheric wind potential based on reinforcement learning

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-04-01 DOI: 10.1016/j.energy.2025.135932

Yang Liu, Mingyun Lv, Kangwen Sun

Solar-powered airships are demonstrated overwhelming superiority in plentiful application scenario. Adaptation to the flight environment and efficient energy management are essential during the mission. To improve the operating efficiency of airborne energy system, the tradeoff and integration of airborne renewable energy and uncertain stratospheric wind potential is studied. To complete the station keeping mission utilizing external and internal energy which has complex decision support parameters in different scales and continuous control action spaces with different characteristics, a Noisy Heterogeneous Policy Network Proximal Policy Optimization method is proposed. The state standardization, piecewise reward function, output action with noise, and heterogeneous policy network are designed. The results show that the proposed method has better convergence speed under different degrees of uncertainty of wind field and at different starting points. When the prediction error of the wind velocity is less than 2 m/s, the effective time within the region of the airship starting at specific positions is more than 80 %. When the error reaches 5 m/s, the time percentage is reduced to 50 %. The research results of this paper can provide some valuable reference for improving the performance of renewable energy system on stratospheric airship during the long-time flight in uncertain wind fields.

{"title":"Comprehensive tradeoff and utilization of airborne renewable energy and uncertain stratospheric wind potential based on reinforcement learning","authors":"Yang Liu, Mingyun Lv, Kangwen Sun","doi":"10.1016/j.energy.2025.135932","DOIUrl":"10.1016/j.energy.2025.135932","url":null,"abstract":"<div><div>Solar-powered airships are demonstrated overwhelming superiority in plentiful application scenario. Adaptation to the flight environment and efficient energy management are essential during the mission. To improve the operating efficiency of airborne energy system, the tradeoff and integration of airborne renewable energy and uncertain stratospheric wind potential is studied. To complete the station keeping mission utilizing external and internal energy which has complex decision support parameters in different scales and continuous control action spaces with different characteristics, a Noisy Heterogeneous Policy Network Proximal Policy Optimization method is proposed. The state standardization, piecewise reward function, output action with noise, and heterogeneous policy network are designed. The results show that the proposed method has better convergence speed under different degrees of uncertainty of wind field and at different starting points. When the prediction error of the wind velocity is less than 2 m/s, the effective time within the region of the airship starting at specific positions is more than 80 %. When the error reaches 5 m/s, the time percentage is reduced to 50 %. The research results of this paper can provide some valuable reference for improving the performance of renewable energy system on stratospheric airship during the long-time flight in uncertain wind fields.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135932"},"PeriodicalIF":9.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748458","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}

引用次数: 0

Investigation of building load prediction models based on integration of mechanism methods and data-driven models

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-03-31 DOI: 10.1016/j.energy.2025.135933

Xiaojie Lin , Ning Zhang , Liuliu Du-Ikonen , Xiaolei Yuan , Wei Zhong

In the district energy systems, the quality of data often proves inferior, resulting in that the historical building data may be partially or entirely absent. The traditional data-driven models may generate poor fitting results in such scenarios, while mechanism models typically involve a time-consuming simulation process, especially for large-space building load calculation. This paper proposes building load prediction models based on the integration of mechanism methods and data-driven models to deal with the problem for different building types and in different degrees of data quantity. The mechanism methods are performed based on the specific building in the case, and the base structure of data-driven models is not limited by this method. Two cases with different building types and load types are selected for the experiment. This paper investigates the building load prediction capabilities of different models, including different base structures and whether mechanism methods are integrated, in different training data sampling scenarios. Based on the experiment results, the proposed models achieve generalization and robustness in different cases and scenarios.

在区域能源系统中，数据质量往往较差，导致历史建筑数据可能部分或完全缺失。在这种情况下，传统的数据驱动模型可能会产生较差的拟合结果，而机制模型通常涉及耗时的模拟过程，尤其是在大空间建筑负荷计算方面。本文提出了基于机理方法和数据驱动模型相结合的建筑荷载预测模型，以解决不同建筑类型和不同数据量情况下的问题。机制方法是根据案例中的具体建筑来执行的，而数据驱动模型的基础结构不受此方法的限制。本文选取了两个不同建筑类型和荷载类型的案例进行实验。本文研究了不同模型在不同训练数据采样情况下的建筑荷载预测能力，包括不同的基础结构和是否整合了机制方法。根据实验结果，所提出的模型在不同情况和场景下都实现了泛化和鲁棒性。

{"title":"Investigation of building load prediction models based on integration of mechanism methods and data-driven models","authors":"Xiaojie Lin , Ning Zhang , Liuliu Du-Ikonen , Xiaolei Yuan , Wei Zhong","doi":"10.1016/j.energy.2025.135933","DOIUrl":"10.1016/j.energy.2025.135933","url":null,"abstract":"<div><div>In the district energy systems, the quality of data often proves inferior, resulting in that the historical building data may be partially or entirely absent. The traditional data-driven models may generate poor fitting results in such scenarios, while mechanism models typically involve a time-consuming simulation process, especially for large-space building load calculation. This paper proposes building load prediction models based on the integration of mechanism methods and data-driven models to deal with the problem for different building types and in different degrees of data quantity. The mechanism methods are performed based on the specific building in the case, and the base structure of data-driven models is not limited by this method. Two cases with different building types and load types are selected for the experiment. This paper investigates the building load prediction capabilities of different models, including different base structures and whether mechanism methods are integrated, in different training data sampling scenarios. Based on the experiment results, the proposed models achieve generalization and robustness in different cases and scenarios.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135933"},"PeriodicalIF":9.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760912","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}

引用次数: 0

Energy and economic performance evaluation of solar thermal and photovoltaic hybrid systems for industrial process heating

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-03-31 DOI: 10.1016/j.energy.2025.135765

Josué F. Rosales-Pérez , Andrés Villarruel-Jaramillo , Manuel Pérez-García , José M. Cardemil , Rodrigo Escobar

Hybrid solar heating systems that combine solar thermal (ST) collectors with photovoltaic systems (ST–PV) have shown potential to improve the feasibility of integrating renewable heat in the industrial sector. However, the application scenarios where ST–PV systems achieve better performance relative to individual alternatives and other hybrid configurations have not been determined. This study evaluates the techno-economic performance of ST–PV systems considering the effect of radiation levels, process temperature, and technological proportion of the hybrid field. A sizing methodology for the ST–PV configuration was developed, and a parametric analysis was carried out to identify which implementation scenarios allow better system performance in terms of solar fraction (SF) and levelized cost of heat (LCOH). The results showed that the greatest potential of the ST–PV system is obtained for SFs above 0.3, low and medium process temperatures, and medium and high radiation levels, achieving reductions in the LCOH up to 54% compared to the individual alternatives and showing better economic potential than hybrid systems with two ST collector technologies. The methodology and results of this study provide an important tool for project developers and researchers to determine the implementation conditions where ST–PV systems could improve the viability of industrial solar heating.

{"title":"Energy and economic performance evaluation of solar thermal and photovoltaic hybrid systems for industrial process heating","authors":"Josué F. Rosales-Pérez , Andrés Villarruel-Jaramillo , Manuel Pérez-García , José M. Cardemil , Rodrigo Escobar","doi":"10.1016/j.energy.2025.135765","DOIUrl":"10.1016/j.energy.2025.135765","url":null,"abstract":"<div><div>Hybrid solar heating systems that combine solar thermal (ST) collectors with photovoltaic systems (ST–PV) have shown potential to improve the feasibility of integrating renewable heat in the industrial sector. However, the application scenarios where ST–PV systems achieve better performance relative to individual alternatives and other hybrid configurations have not been determined. This study evaluates the techno-economic performance of ST–PV systems considering the effect of radiation levels, process temperature, and technological proportion of the hybrid field. A sizing methodology for the ST–PV configuration was developed, and a parametric analysis was carried out to identify which implementation scenarios allow better system performance in terms of solar fraction (SF) and levelized cost of heat (LCOH). The results showed that the greatest potential of the ST–PV system is obtained for SFs above 0.3, low and medium process temperatures, and medium and high radiation levels, achieving reductions in the LCOH up to 54% compared to the individual alternatives and showing better economic potential than hybrid systems with two ST collector technologies. The methodology and results of this study provide an important tool for project developers and researchers to determine the implementation conditions where ST–PV systems could improve the viability of industrial solar heating.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135765"},"PeriodicalIF":9.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760822","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}

引用次数: 0

A novel fractional nonlinear discrete grey model with kernel-markov adaptation for clean energy forecasting

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-03-29 DOI: 10.1016/j.energy.2025.135888

Yong Wang , Zhongsen Yang , Neng Fan , Shixiong Wen , Wenyu Kuang , Mou Yang , Hong-Li Li , Govindasami Narayanan , Flavian Emmanuel Sapnken

In response to the escalating global environmental pollution crisis and the growing demand for clean energy, accurate prediction and assessment of clean energy production and consumption have become crucial for strategic energy development. This study presents an innovative data-driven adaptive fractional nonlinear discrete grey prediction model, which incorporates the kernel method from support vector machines and integrates enhanced concepts from Markov chains. The proposed model achieves dual advancements: it addresses nonlinear factors at the structural level while effectively capturing temporal dependencies in historical data patterns. Furthermore, we introduce a fractional-order integration generator that extends the grey sequence operator's order to the real domain, thereby significantly enhancing the model's applicability and flexibility. To optimize model parameters, we conducted a comprehensive comparison of optimization algorithms, ultimately implementing the Grey Wolf Optimizer (GWO). The model's performance was rigorously evaluated through comparative analysis with existing high-performing models, employing three case studies: quarterly net photovoltaic electricity generation in U.S. small-scale solar energy systems, quarterly natural gas consumption in the U.S. residential sector, and other renewable energy generation in the United States. Additionally, we employed Monte-Carlo simulation and probability density analysis to assess the model's robustness. The results demonstrate superior stability and predictive accuracy compared to existing models, with the adaptive structure of our proposed model proving particularly effective in generating reliable forecasts. Based on these predictive outcomes, we provide strategic recommendations to decision-makers regarding clean energy production and consumption development.

{"title":"A novel fractional nonlinear discrete grey model with kernel-markov adaptation for clean energy forecasting","authors":"Yong Wang , Zhongsen Yang , Neng Fan , Shixiong Wen , Wenyu Kuang , Mou Yang , Hong-Li Li , Govindasami Narayanan , Flavian Emmanuel Sapnken","doi":"10.1016/j.energy.2025.135888","DOIUrl":"10.1016/j.energy.2025.135888","url":null,"abstract":"<div><div>In response to the escalating global environmental pollution crisis and the growing demand for clean energy, accurate prediction and assessment of clean energy production and consumption have become crucial for strategic energy development. This study presents an innovative data-driven adaptive fractional nonlinear discrete grey prediction model, which incorporates the kernel method from support vector machines and integrates enhanced concepts from Markov chains. The proposed model achieves dual advancements: it addresses nonlinear factors at the structural level while effectively capturing temporal dependencies in historical data patterns. Furthermore, we introduce a fractional-order integration generator that extends the grey sequence operator's order to the real domain, thereby significantly enhancing the model's applicability and flexibility. To optimize model parameters, we conducted a comprehensive comparison of optimization algorithms, ultimately implementing the Grey Wolf Optimizer (GWO). The model's performance was rigorously evaluated through comparative analysis with existing high-performing models, employing three case studies: quarterly net photovoltaic electricity generation in U.S. small-scale solar energy systems, quarterly natural gas consumption in the U.S. residential sector, and other renewable energy generation in the United States. Additionally, we employed Monte-Carlo simulation and probability density analysis to assess the model's robustness. The results demonstrate superior stability and predictive accuracy compared to existing models, with the adaptive structure of our proposed model proving particularly effective in generating reliable forecasts. Based on these predictive outcomes, we provide strategic recommendations to decision-makers regarding clean energy production and consumption development.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"323 ","pages":"Article 135888"},"PeriodicalIF":9.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739732","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}

引用次数: 0