Pub Date : 2024-11-07DOI: 10.1016/j.renene.2024.121801
Meena E. Girgis , Nasr A. Elkhateeb
To maximize power transfer from the PV panel, a Perturb and Observe (P&O) algorithm and a feedback controller are used to create the Maximum Power Point Tracking (MPPT) algorithm. The dynamic performance of the MPPT algorithm depends on the feedback controller’s ability to track the PV panel voltage to the reference voltage from the algorithm. This research introduces an adaptive Proportional-Integral-Derivative (PID) controller that improves the dynamic characteristics of the MPPT algorithm. The proposed adaptive control technique utilizes a PID controller and the exponential forgetting recursive least squares (EFRLS) algorithm to update the PID gains online. The verification process involves simulations under three scenarios: slow and fast variations in temperature, solar insolation, resistive load, and partial shading situations. The proposed adaptive PID controller performs robustly during tracking PV panel voltage under different atmospheric conditions.
{"title":"Enhancing photovoltaic MPPT with P&O algorithm performance based on adaptive PID control using exponential forgetting recursive least squares method","authors":"Meena E. Girgis , Nasr A. Elkhateeb","doi":"10.1016/j.renene.2024.121801","DOIUrl":"10.1016/j.renene.2024.121801","url":null,"abstract":"<div><div>To maximize power transfer from the PV panel, a Perturb and Observe (P&O) algorithm and a feedback controller are used to create the Maximum Power Point Tracking (MPPT) algorithm. The dynamic performance of the MPPT algorithm depends on the feedback controller’s ability to track the PV panel voltage to the reference voltage from the <span><math><mtext>P&O</mtext></math></span> algorithm. This research introduces an adaptive Proportional-Integral-Derivative (PID) controller that improves the dynamic characteristics of the MPPT algorithm. The proposed adaptive control technique utilizes a PID controller and the exponential forgetting recursive least squares (EFRLS) algorithm to update the PID gains online. The verification process involves simulations under three scenarios: slow and fast variations in temperature, solar insolation, resistive load, and partial shading situations. The proposed adaptive PID controller performs robustly during tracking PV panel voltage under different atmospheric conditions.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121801"},"PeriodicalIF":9.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658671","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}
Pub Date : 2024-11-07DOI: 10.1016/j.renene.2024.121828
Yuchen Pu , Qi Li , Shasha Huo , Elena Breaz , Weirong Chen , Fei Gao
The flexible operation and storage of hydrogen and electric energy provide an effective path for the development of low-carbon energy and transportation systems. This paper introduces a configuration method for electric-hydrogen shared energy storage supporting the multiple energy and capacity demands of integrated energy systems (IESs). A Stackelberg game-based shared energy framework with gaseous hydrogen transportation by transportation network for shared energy storage operators (SESO) and IESs is established. In this framework, the electric power and electric storage sharing are accomplished by power lines, while the shared hydrogen is achieved by the transportation of mobile trucks. The target of the energy storage operator is to maximize its trading benefits with IESs and lower the life-cycle cost of the whole system, while the IESs aim to meet their energy demand and lower the operation cost via energy storage sharing. To solve this planning model, a two-level sine cosine based grey wolf optimizer (GWO-SCA)-bisectional method is provided to realize the system configuration, mobile hydrogen planning, and economic trading of the shared energy operator. A case study with 3 IESs, real-world geographic roads, and environmental conditions is carried out to verify the effectiveness of the method and the life-cycle configuration and operation economy of the shared energy storage. The comparisons show that the proposed energy storage sharing frame can achieve a higher energy utilization ratio of 92 % and the proposed method can solve the two-level problem more efficiently, the calculation time is reduced by 80.2 %.
{"title":"Optimal configuration for shared electric-hydrogen energy storage for multiple integrated energy systems with mobile hydrogen transportation","authors":"Yuchen Pu , Qi Li , Shasha Huo , Elena Breaz , Weirong Chen , Fei Gao","doi":"10.1016/j.renene.2024.121828","DOIUrl":"10.1016/j.renene.2024.121828","url":null,"abstract":"<div><div>The flexible operation and storage of hydrogen and electric energy provide an effective path for the development of low-carbon energy and transportation systems. This paper introduces a configuration method for electric-hydrogen shared energy storage supporting the multiple energy and capacity demands of integrated energy systems (IESs). A Stackelberg game-based shared energy framework with gaseous hydrogen transportation by transportation network for shared energy storage operators (SESO) and IESs is established. In this framework, the electric power and electric storage sharing are accomplished by power lines, while the shared hydrogen is achieved by the transportation of mobile trucks. The target of the energy storage operator is to maximize its trading benefits with IESs and lower the life-cycle cost of the whole system, while the IESs aim to meet their energy demand and lower the operation cost via energy storage sharing. To solve this planning model, a two-level sine cosine based grey wolf optimizer (GWO-SCA)-bisectional method is provided to realize the system configuration, mobile hydrogen planning, and economic trading of the shared energy operator. A case study with 3 IESs, real-world geographic roads, and environmental conditions is carried out to verify the effectiveness of the method and the life-cycle configuration and operation economy of the shared energy storage. The comparisons show that the proposed energy storage sharing frame can achieve a higher energy utilization ratio of 92 % and the proposed method can solve the two-level problem more efficiently, the calculation time is reduced by 80.2 %.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121828"},"PeriodicalIF":9.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658670","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}
Pub Date : 2024-11-07DOI: 10.1016/j.renene.2024.121811
Yanchao Liu , Weijiong Dai , Lichen Zhang , Jiajun Zheng , Yanze Du , Xiwen Zhang , Tong Zhang , Bo Qin , Ruifeng Li
The conversion of waste cooking oil into biodiesel can bring about dual benefits: alleviating environmental pollution and realizing waste recycle. Embryonic zeolite has highly accessible acid sites because of the partially formed or more open zeolitic structure, which can solve problems such as diffusion limitation and inaccessible acid sites that the traditional zeolite catalysts face in the process of macromolecular reactants. In this work, a series of embryonic Beta zeolites were prepared by using mesoporous SBA-15 as a self-sacrificial silica source via a solid-state transformation strategy. NH3-TPD and FT-IR pyridine adsorption confirm that Brønsted acid sites have been created in these amorphous form embryonic catalysts. The diffusion property of toluene obtained by a zero-length column method proved that the higher the zeolization degree, the greater the diffusion activation energy. The synergistic effects resulted from the combination of the ordered mesoporous structures (ranging from 2 to 10 nm) stemming from the SBA-15 substrate and the moderate acid sites (∼88 μmol g−1) offered the embryonic SBEA-3 catalyst with remarkable catalytic performance for ≥95 % conversion during 20 times cycling tests and more than 90 % methyloleate yield.
{"title":"A high-efficient beta-zeolitic catalyst for conversion of waste cooking oil towards biodiesel","authors":"Yanchao Liu , Weijiong Dai , Lichen Zhang , Jiajun Zheng , Yanze Du , Xiwen Zhang , Tong Zhang , Bo Qin , Ruifeng Li","doi":"10.1016/j.renene.2024.121811","DOIUrl":"10.1016/j.renene.2024.121811","url":null,"abstract":"<div><div>The conversion of waste cooking oil into biodiesel can bring about dual benefits: alleviating environmental pollution and realizing waste recycle. Embryonic zeolite has highly accessible acid sites because of the partially formed or more open zeolitic structure, which can solve problems such as diffusion limitation and inaccessible acid sites that the traditional zeolite catalysts face in the process of macromolecular reactants. In this work, a series of embryonic Beta zeolites were prepared by using mesoporous SBA-15 as a self-sacrificial silica source <em>via</em> a solid-state transformation strategy. NH<sub>3</sub>-TPD and FT-IR pyridine adsorption confirm that Brønsted acid sites have been created in these amorphous form embryonic catalysts. The diffusion property of toluene obtained by a zero-length column method proved that the higher the zeolization degree, the greater the diffusion activation energy. The synergistic effects resulted from the combination of the ordered mesoporous structures (ranging from 2 to 10 nm) stemming from the SBA-15 substrate and the moderate acid sites (∼88 μmol g<sup>−1</sup>) offered the embryonic SBEA-3 catalyst with remarkable catalytic performance for ≥95 % conversion during 20 times cycling tests and more than 90 % methyloleate yield.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121811"},"PeriodicalIF":9.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658912","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}
Pub Date : 2024-11-07DOI: 10.1016/j.renene.2024.121794
Mohammad Bakhtiari , Mojtaba Binazadeh , Mohammad Farsi , Seyyed Mojtaba Mousavi , Raed H. Althomali , Mohammed M. Rahman
Integration of Tri-reforming and Fischer-Tropsch processes is a novel approach for conversion of CO2 into C5+ liquid hydrocarbon. Tri-reforming converts CO2 into syngas and does not require external heat source due to methane oxidation reaction that occurs at the beginning of reactor. Fischer-Tropsch synthesis converts produced syngas in the reformer to hydrocarbon fuels. In this research, plug reactors have been modeled in a heterogeneous and one-dimensional form, and the mass and energy equations governing them in steady state have been developed. The accuracy of models is validated with literature data. Then an optimization problem aiming at maximal C5+ production is compiled with specific limitations imposed on operating conditions. Based on the modeling results, 95 % of CO2 produced at Fischer-Tropsch and 92 % CO2 produced at Tri-reforming process is captured and injected into Tri-reforming reactor for conversion into hydrocarbon fuels. Modeling results revealed that the mole fractions of C2-C4 and C5+ at outlet of Fischer-Tropsch are 0.117 and 0.023 which could be purified in separators and used as clean energy carriers. The suggested integrated route for CO2 capture and conversion into green fuels offers both environmental and technical advantages.
{"title":"Optimization of C5+ production by CO2 recycle at an integrated Tri-reforming and Fischer-Tropsch process","authors":"Mohammad Bakhtiari , Mojtaba Binazadeh , Mohammad Farsi , Seyyed Mojtaba Mousavi , Raed H. Althomali , Mohammed M. Rahman","doi":"10.1016/j.renene.2024.121794","DOIUrl":"10.1016/j.renene.2024.121794","url":null,"abstract":"<div><div>Integration of Tri-reforming and Fischer-Tropsch processes is a novel approach for conversion of CO<sub>2</sub> into C<sub>5</sub><sup>+</sup> liquid hydrocarbon. Tri-reforming converts CO<sub>2</sub> into syngas and does not require external heat source due to methane oxidation reaction that occurs at the beginning of reactor. Fischer-Tropsch synthesis converts produced syngas in the reformer to hydrocarbon fuels. In this research, plug reactors have been modeled in a heterogeneous and one-dimensional form, and the mass and energy equations governing them in steady state have been developed. The accuracy of models is validated with literature data. Then an optimization problem aiming at maximal C<sub>5</sub><sup>+</sup> production is compiled with specific limitations imposed on operating conditions. Based on the modeling results, 95 % of CO<sub>2</sub> produced at Fischer-Tropsch and 92 % CO<sub>2</sub> produced at Tri-reforming process is captured and injected into Tri-reforming reactor for conversion into hydrocarbon fuels. Modeling results revealed that the mole fractions of C<sub>2</sub>-C<sub>4</sub> and C<sub>5</sub><sup>+</sup> at outlet of Fischer-Tropsch are 0.117 and 0.023 which could be purified in separators and used as clean energy carriers. The suggested integrated route for CO<sub>2</sub> capture and conversion into green fuels offers both environmental and technical advantages.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121794"},"PeriodicalIF":9.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658913","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}
Pub Date : 2024-11-06DOI: 10.1016/j.renene.2024.121821
Wei Li, Ravi Kumar Pandit
Wind energy is a significant renewable resource, but its efficient harnessing requires advanced control systems. This study presents a Data-Centric Predictive Control (DPC) system, enhanced by a Tuna Swarm Optimization-Backpropagation Neural Network (TSO-BPNN) for predictive wind turbine control. It's like a smart tool that uses innovative fusion of deep learning, predictive Control, and reinforcement learning. Unlike traditional control methods, the proposed approach uses real-time data to optimize turbine performance in response to fluctuating wind conditions.
The system is validated using simulations on the FAST platform, which demonstrate its superior performance in two critical operational regions. Specifically, in Region II, where the objective is to maximize power extraction from the wind, the DPC achieves a 1.07 % reduction in overshoot and an improvement of 36.14 units in steady-state error compared to traditional methods. The response time remains comparable to existing Model Predictive Control (MPC) strategies, ensuring real-time applicability without sacrificing efficiency. In Region III, where maintaining constant power output is crucial, the DPC outperforms both the baseline and MPC methods, reducing overshoot by 0.58 % and improving accuracy by 17.27 units compared to the baseline method. These results highlight the effectiveness of the proposed DPC system in optimizing turbine performance under variable wind conditions, offering a significant improvement over traditional methods in both accuracy and control precision.
风能是一种重要的可再生资源，但有效利用风能需要先进的控制系统。本研究提出了一种以数据为中心的预测控制（DPC）系统，并通过金枪鱼群优化-反向传播神经网络（TSO-BPNN）对风力涡轮机的预测控制进行了增强。它就像一个智能工具，将深度学习、预测控制和强化学习创新性地融合在一起。与传统的控制方法不同，所提出的方法利用实时数据来优化风机性能，以应对波动的风力条件。该系统在 FAST 平台上进行了模拟验证，证明了它在两个关键运行区域的卓越性能。具体来说，在目标是最大限度地从风中提取电能的区域 II 中，与传统方法相比，DPC 的过冲减少了 1.07%，稳态误差提高了 36.14 个单位。响应时间与现有的模型预测控制 (MPC) 策略相当，确保了在不降低效率的情况下的实时适用性。在对保持恒定功率输出至关重要的区域 III 中，DPC 的性能优于基准方法和 MPC 方法，与基准方法相比，过冲减少了 0.58 %，精度提高了 17.27 个单位。这些结果凸显了所提出的 DPC 系统在多变风力条件下优化涡轮机性能的有效性，与传统方法相比，在精确度和控制精度方面都有显著提高。
{"title":"Data-centric predictive control with tuna swarm optimization-backpropagation neural networks for enhanced wind turbine performance","authors":"Wei Li, Ravi Kumar Pandit","doi":"10.1016/j.renene.2024.121821","DOIUrl":"10.1016/j.renene.2024.121821","url":null,"abstract":"<div><div>Wind energy is a significant renewable resource, but its efficient harnessing requires advanced control systems. This study presents a Data-Centric Predictive Control (DPC) system, enhanced by a Tuna Swarm Optimization-Backpropagation Neural Network (TSO-BPNN) for predictive wind turbine control. It's like a smart tool that uses innovative fusion of deep learning, predictive Control, and reinforcement learning. Unlike traditional control methods, the proposed approach uses real-time data to optimize turbine performance in response to fluctuating wind conditions.</div><div>The system is validated using simulations on the FAST platform, which demonstrate its superior performance in two critical operational regions. Specifically, in Region II, where the objective is to maximize power extraction from the wind, the DPC achieves a 1.07 % reduction in overshoot and an improvement of 36.14 units in steady-state error compared to traditional methods. The response time remains comparable to existing Model Predictive Control (MPC) strategies, ensuring real-time applicability without sacrificing efficiency. In Region III, where maintaining constant power output is crucial, the DPC outperforms both the baseline and MPC methods, reducing overshoot by 0.58 % and improving accuracy by 17.27 units compared to the baseline method. These results highlight the effectiveness of the proposed DPC system in optimizing turbine performance under variable wind conditions, offering a significant improvement over traditional methods in both accuracy and control precision.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121821"},"PeriodicalIF":9.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658558","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}
Pub Date : 2024-11-06DOI: 10.1016/j.renene.2024.121833
Cong Han, Arindam Banerjee
Tidal stream turbines deployed at highly energetic open water sites are subjected to sheared inflow in the rotor plane. The inflow shear is expected to cause asymmetric loading on the rotor blades and affect the downstream wake. In the current study, two different turbulent inflow conditions, static-high shear and dynamic shear, were generated via an active-grid turbulence generator. A 1:20 scaled three-bladed horizontal axis tidal turbine model was tested in those conditions. The results were compared to a quasi-laminar case with no imposed turbulence or shear. The results show that the high shear reduces the average performance, with a drop of up to 16% in the optimal power coefficient. Besides, the shear profiles increase torque fluctuations and induce significant differences in wake hydrodynamics between the high-speed (upper) and low-speed (lower) regions. The large integral length scales further enhance the load fluctuations perceived by the rotor but have a negligible effect on the mean wake field quantities and the wake recovery. The lower half region featured a faster breakdown of tip vortex structure and a rapid drop of swirl number, a phenomenon conjectured to be a consequence of the strong turbulence intensities and Reynolds stresses in the lower half region. The sheared turbulent inflow also results in a very intensive energy redistribution process towards large-scale, low-frequency motions, which is important to the downstream turbines.
{"title":"Near wake evolution of a tidal stream turbine due to asymmetric sheared turbulent inflow with different integral length scales","authors":"Cong Han, Arindam Banerjee","doi":"10.1016/j.renene.2024.121833","DOIUrl":"10.1016/j.renene.2024.121833","url":null,"abstract":"<div><div>Tidal stream turbines deployed at highly energetic open water sites are subjected to sheared inflow in the rotor plane. The inflow shear is expected to cause asymmetric loading on the rotor blades and affect the downstream wake. In the current study, two different turbulent inflow conditions, static-high shear and dynamic shear, were generated via an active-grid turbulence generator. A 1:20 scaled three-bladed horizontal axis tidal turbine model was tested in those conditions. The results were compared to a quasi-laminar case with no imposed turbulence or shear. The results show that the high shear reduces the average performance, with a drop of up to 16% in the optimal power coefficient. Besides, the shear profiles increase torque fluctuations and induce significant differences in wake hydrodynamics between the high-speed (upper) and low-speed (lower) regions. The large integral length scales further enhance the load fluctuations perceived by the rotor but have a negligible effect on the mean wake field quantities and the wake recovery. The lower half region featured a faster breakdown of tip vortex structure and a rapid drop of swirl number, a phenomenon conjectured to be a consequence of the strong turbulence intensities and Reynolds stresses in the lower half region. The sheared turbulent inflow also results in a very intensive energy redistribution process towards large-scale, low-frequency motions, which is important to the downstream turbines.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121833"},"PeriodicalIF":9.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663238","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}
Pub Date : 2024-11-06DOI: 10.1016/j.renene.2024.121810
Jinhao Yang , Jinghua Wu , Junjie Lu , Xiangang Peng , Haoliang Yuan , Loi Lei Lai
The assessment of rooftop photovoltaic (PV) potential is highly significant for energy policy formulation. With the rapid development of computer vision (CV) and remote sensing imagery, utilizing CV to extract rooftop information is an ideal approach. However, deep learning requires a large amount of accurately annotated data, and annotating remote sensing images is a labor-intensive task. This limitation hinders the application of deep learning in rooftop PV potential assessment. To address this issue, this paper proposes a semi-supervised learning (SSL)-based segmentation model to extract rooftop information from remote sensing images. Subsequently, a rooftop classification method is proposed to categorize rooftops into several classes and estimate their rooftop PV available area ratios. Finally, the total available rooftop PV area in urban areas is evaluated, and the potential rooftop PV installed capacity and power generation are calculated. This method is applied in the Longhu District of Shantou City, Guangdong Province. The evaluation results show that the total rooftop area in Longhu District is 17.2 km2, with a rooftop PV available area of 12.7 km2. It is estimated that the rooftop PV installed capacity in Longhu District is 1849.4 MW, with an annual power generation of 2219.3 GWh.
{"title":"A novel method for assessment rooftop PV potential based on remote sensing images","authors":"Jinhao Yang , Jinghua Wu , Junjie Lu , Xiangang Peng , Haoliang Yuan , Loi Lei Lai","doi":"10.1016/j.renene.2024.121810","DOIUrl":"10.1016/j.renene.2024.121810","url":null,"abstract":"<div><div>The assessment of rooftop photovoltaic (PV) potential is highly significant for energy policy formulation. With the rapid development of computer vision (CV) and remote sensing imagery, utilizing CV to extract rooftop information is an ideal approach. However, deep learning requires a large amount of accurately annotated data, and annotating remote sensing images is a labor-intensive task. This limitation hinders the application of deep learning in rooftop PV potential assessment. To address this issue, this paper proposes a semi-supervised learning (SSL)-based segmentation model to extract rooftop information from remote sensing images. Subsequently, a rooftop classification method is proposed to categorize rooftops into several classes and estimate their rooftop PV available area ratios. Finally, the total available rooftop PV area in urban areas is evaluated, and the potential rooftop PV installed capacity and power generation are calculated. This method is applied in the Longhu District of Shantou City, Guangdong Province. The evaluation results show that the total rooftop area in Longhu District is 17.2 km<sup>2</sup>, with a rooftop PV available area of 12.7 km<sup>2</sup>. It is estimated that the rooftop PV installed capacity in Longhu District is 1849.4 MW, with an annual power generation of 2219.3 GWh.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121810"},"PeriodicalIF":9.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658726","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}
Pub Date : 2024-11-06DOI: 10.1016/j.renene.2024.121770
Ruike Huang , Xuexia Zhang , Sidi Dong , Lei Huang , Hongbo Liao , Yuan Li
Accurate prognostication of degradation plays an essential role in effectively enhancing the operational lifespan of proton exchange membrane fuel cells (PEMFCs). This paper proposes a novel enhanced correctional grey Verhulst model (IHS-CRGVM-RE), designed to prognosticate the degradation process of PEMFCs using the voltage of PEMFCs stack as a health indicator. First, the inverse hyperbolic sine function transformation is employed to attain optimal smoothness in data treatment. Then, the background value within the grey Verhulst model framework is modified based on cellular automata with rectangle techniques. Finally, a residual correction mechanism is applied to delineate the influences of error outcomes concerning PEMFCs degradation. Rigorous validation is provided via a comprehensive analysis based on two distinct PEMFCs datasets. The results demonstrate that the proposed model outperforms other data-driven models in prognostication accuracy, highlighting its significant importance for prognosticating the lifespan of PEMFCs.
{"title":"A refined grey Verhulst model for accurate degradation prognostication of PEM fuel cells based on inverse hyperbolic sine function transformation","authors":"Ruike Huang , Xuexia Zhang , Sidi Dong , Lei Huang , Hongbo Liao , Yuan Li","doi":"10.1016/j.renene.2024.121770","DOIUrl":"10.1016/j.renene.2024.121770","url":null,"abstract":"<div><div>Accurate prognostication of degradation plays an essential role in effectively enhancing the operational lifespan of proton exchange membrane fuel cells (PEMFCs). This paper proposes a novel enhanced correctional grey Verhulst model (IHS-CRGVM-RE), designed to prognosticate the degradation process of PEMFCs using the voltage of PEMFCs stack as a health indicator. First, the inverse hyperbolic sine function transformation is employed to attain optimal smoothness in data treatment. Then, the background value within the grey Verhulst model framework is modified based on cellular automata with rectangle techniques. Finally, a residual correction mechanism is applied to delineate the influences of error outcomes concerning PEMFCs degradation. Rigorous validation is provided via a comprehensive analysis based on two distinct PEMFCs datasets. The results demonstrate that the proposed model outperforms other data-driven models in prognostication accuracy, highlighting its significant importance for prognosticating the lifespan of PEMFCs.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121770"},"PeriodicalIF":9.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658562","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}
Pub Date : 2024-11-06DOI: 10.1016/j.renene.2024.121825
Sirine Dhaoui , Abdallah Bouabidi , Moataz M. Abdel-Aziz , Mohammed El Hadi Attia
This study explores the enhancement of a double slope solar still (DSSS) by integrating cylindrical fins on the absorber plate to improve heat transfer efficiency and water productivity. The experimental setup, made from galvanized iron sheets and insulated with a wooden box, features a glass cover angled at 34° for optimal solar radiation absorption. Testing was conducted in Gabes, Tunisia, evaluating solar radiation, wind speed, ambient temperature, and water productivity. Measurements were taken from 9:00 a.m. to 6:00 p.m., focusing on distillate yield, temperatures, and heat transfer coefficients. Both experimental and numerical analyses examined the effect of fin diameter on temperature distribution, heat transfer coefficients, and energy efficiency. Results demonstrate that the addition of fins significantly enhances both absorber and water temperatures, with the largest fin diameter (80 mm) achieving a 14.07 % increase. A validated Computational Fluid Dynamics (CFD) model showed a maximum temperature deviation of less than 3.5 °C from experimental data. The study recorded a peak energy efficiency of 71.03 % and a cumulative water productivity of 3252.55 mL/m2.
{"title":"Performance enhancement of double slope solar still using cylindrical fins: Experimental and numerical analysis","authors":"Sirine Dhaoui , Abdallah Bouabidi , Moataz M. Abdel-Aziz , Mohammed El Hadi Attia","doi":"10.1016/j.renene.2024.121825","DOIUrl":"10.1016/j.renene.2024.121825","url":null,"abstract":"<div><div>This study explores the enhancement of a double slope solar still (DSSS) by integrating cylindrical fins on the absorber plate to improve heat transfer efficiency and water productivity. The experimental setup, made from galvanized iron sheets and insulated with a wooden box, features a glass cover angled at 34° for optimal solar radiation absorption. Testing was conducted in Gabes, Tunisia, evaluating solar radiation, wind speed, ambient temperature, and water productivity. Measurements were taken from 9:00 a.m. to 6:00 p.m., focusing on distillate yield, temperatures, and heat transfer coefficients. Both experimental and numerical analyses examined the effect of fin diameter on temperature distribution, heat transfer coefficients, and energy efficiency. Results demonstrate that the addition of fins significantly enhances both absorber and water temperatures, with the largest fin diameter (80 mm) achieving a 14.07 % increase. A validated Computational Fluid Dynamics (CFD) model showed a maximum temperature deviation of less than 3.5 °C from experimental data. The study recorded a peak energy efficiency of 71.03 % and a cumulative water productivity of 3252.55 mL/m<sup>2</sup>.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121825"},"PeriodicalIF":9.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658748","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}
Pub Date : 2024-11-06DOI: 10.1016/j.renene.2024.121826
Chu Wang , Hangchen Qu , Lin Mu , Dengyu Chen , Ming Dong , Liang Wang
The present investigation proposed an experimental method combining bio-oil segmental recovery, vapor composition inversion, and function fitting, to describe the vapor evolution curves and heat maps of water, acetic acid, furfural, phenol, MCP, guaiacol and its derivatives in the indirect condensing field regulated by continuous water bath temperatures within 280–364 K. Under 280 K water bath, the recovery proportion of water exceeded 50 % after pyrolysis vapors moved 8 cm from inlet, and soon surpassed 90 % after 12.5 cm. At 337 K, 50 % recovery proportion of water required the vapors to move 20 cm, while guaiacol required only 10 cm for the same proportion. Half of the evolution description data were sampled and utilized to fit the prediction curves of vapor evolution with increasing bath temperature, and another half were used to verify these prediction curves. The overall prediction accuracy of the representative components remained at 70 %, despite the local accuracies less than 50 % within 280–300 K and 355–364 K. These findings provided a visual description and prediction method for the selective condensation of pyrolysis vapors. The cycle from research to application of selective condensation was effectively shortened by the prediction of vapor evolution under water bath based on sampling experiments.
本研究提出了一种结合生物油分段回收、蒸汽成分反演和函数拟合的实验方法，以描述水、乙酸、糠醛、苯酚、MCP、愈创木酚及其衍生物在280-364 K连续水浴温度调节的间接冷凝场中的蒸汽演化曲线和热图。在280 K水浴条件下，热解蒸汽离入口8 cm后，水的回收率超过50%，12.5 cm后很快超过90%。在 337 K 水浴条件下，水的回收率达到 50%需要蒸汽移动 20 厘米，而愈创木酚只需要移动 10 厘米就能达到同样的回收率。对一半的进化描述数据进行了采样，并利用这些数据拟合了随浴槽温度升高的蒸汽进化预测曲线，另一半数据则用于验证这些预测曲线。尽管在 280-300 K 和 355-364 K 温度范围内的局部准确率低于 50%，但代表性成分的整体预测准确率仍保持在 70%。这些发现为热解蒸汽的选择性冷凝提供了一种直观的描述和预测方法。通过基于取样实验的水浴蒸汽演变预测，有效缩短了选择性冷凝从研究到应用的周期。
{"title":"Visual liquefaction process of biomass pyrolysis vapors during indirect heat exchange: Experimental description, prediction, and verification","authors":"Chu Wang , Hangchen Qu , Lin Mu , Dengyu Chen , Ming Dong , Liang Wang","doi":"10.1016/j.renene.2024.121826","DOIUrl":"10.1016/j.renene.2024.121826","url":null,"abstract":"<div><div>The present investigation proposed an experimental method combining bio-oil segmental recovery, vapor composition inversion, and function fitting, to describe the vapor evolution curves and heat maps of water, acetic acid, furfural, phenol, MCP, guaiacol and its derivatives in the indirect condensing field regulated by continuous water bath temperatures within 280–364 K. Under 280 K water bath, the recovery proportion of water exceeded 50 % after pyrolysis vapors moved 8 cm from inlet, and soon surpassed 90 % after 12.5 cm. At 337 K, 50 % recovery proportion of water required the vapors to move 20 cm, while guaiacol required only 10 cm for the same proportion. Half of the evolution description data were sampled and utilized to fit the prediction curves of vapor evolution with increasing bath temperature, and another half were used to verify these prediction curves. The overall prediction accuracy of the representative components remained at 70 %, despite the local accuracies less than 50 % within 280–300 K and 355–364 K. These findings provided a visual description and prediction method for the selective condensation of pyrolysis vapors. The cycle from research to application of selective condensation was effectively shortened by the prediction of vapor evolution under water bath based on sampling experiments.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121826"},"PeriodicalIF":9.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658747","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}
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