In order to utilize solar energy effectively and to achieve a higher electrical efficiency by limiting the operating temperature of the photovoltaic （PV） panel, a novel photovoltaic/thermal solar-assisted heat pump ...In order to utilize solar energy effectively and to achieve a higher electrical efficiency by limiting the operating temperature of the photovoltaic （PV） panel, a novel photovoltaic/thermal solar-assisted heat pump （PV/T-SAHP） system was proposed and constructed. The hybrid solar system generates electricity and thermal energy simultaneously. A distributed parameters model of the PWT-SAHP system was developed and applied to analyze the system dynamic performance in terms of PV action, photothermal action and Rankine cycle processes. The simulation results indicated that the coefficient of performance （COP） of the proposed PV/T-SAHP can be much better than that of the conventional heat pump. Both PV-efficiency and photothermic efficiency have been improved considerably. The results also showed that the performance of this PV/T-SAHP system was strongly influenced by the evaporator area, tube pitch and tilt angle of the PV/T evaporator, which are the key factors in PV/T-SAHP system optimization and PV/T evaporator design.展开更多
This study presents a systematic numerical analysis of wind loads on offshore photovoltaic(PV)panels.A computational fluid dynamics(CFD)model,incorporating a free-surface wave boundary condition,is developed and valid...This study presents a systematic numerical analysis of wind loads on offshore photovoltaic(PV)panels.A computational fluid dynamics(CFD)model,incorporating a free-surface wave boundary condition,is developed and validated against experimental data.Parametric investigations quantify the effects of wind speed,panel tilt angle,clearance,and wave characteristics on the aerodynamic coefficients(drag,lift,and moment).Results indicate that all force coefficients increase with wind speed,with the lift coefficient being most sensitive to wave action.While a larger tilt angle intensifies airflow disturbance and amplifies the coefficients,this effect is more pronounced over flat ground than above a wavy surface.As clearance increases,the drag coefficient fluctuates before rising,the lift coefficient exhibits a trough-shaped response,and the moment coefficient increases monotonically,with values consistently higher over waves.Furthermore,the aerodynamic coefficients generally decrease with greater wave height.The maximum wind load occurs directly above the wave trough,and the aerodynamic force coefficient varies non-monotonically with wave position,first decreasing and then increasing.These findings offer practical guidance for the structural design and safety assurance of offshore PV systems.展开更多
Clouds are one of the leading causes of sun shading,which reduces the direct horizontal irradiance and curtails the photovoltaic(PV)power.It is critical to estimate cloud cover to accurately predict PV generation with...Clouds are one of the leading causes of sun shading,which reduces the direct horizontal irradiance and curtails the photovoltaic(PV)power.It is critical to estimate cloud cover to accurately predict PV generation within a very short horizon(second/minute).To achieve the precise forecasting of cloud cover,an image preprocessing method based on total-sky images is proposed to remove the interference and address the image edge distortion issue.An optimal threshold estimation method is further designed to achieve higher cloud identification precision.Considering the cloud's meteorological properties,a random hypersurface model(RHM)based on the Gaussian mixture probability hypothesis density(GM-PHD)filter is applied to track the cloud.The GM-PHD can track the rotation and diffusion of clouds,which helps to estimate sun-cloud collision.Furthermore,a hybrid autoregressive integrated moving average(ARIMA)and backpropagation(BP)neural network-based model is applied for intra-hour PV power forecasting.The experiment results demonstrate that the proposed cloud-tracking-based PV power forecasting model can capture the ramp behavior of PV power,improving forecasting precision.展开更多
The dense integration of residential distributed photovoltaic(PV)systems into three-phase,four-wire low-voltage(LV)distribution networks results in reverse power flow and three-phase imbalance,leading to voltage viola...The dense integration of residential distributed photovoltaic(PV)systems into three-phase,four-wire low-voltage(LV)distribution networks results in reverse power flow and three-phase imbalance,leading to voltage violations that hinder the growth of rural distributed PV systems.Traditional voltage droop-based control methods regulate PV power output solely based on local voltage measurements at the point of PV connection.Due to a lack of global coordination and optimization,their efficiency is often subpar.This paper presents a centralized coordinated active/reactive power control strategy for PV inverters in rural LV distribution feeders with high PV penetration.The strategy optimizes residential PV inverter reactive and active power control to enhance voltage quality.It uses sensitivity coefficients derived from the inverse Jacobian matrix to assign adjustment weights to individual PV units and iteratively optimize their power outputs.The control sequence prioritizes reactive power increases;if the coefficients are below average or the inverters reach capacity,active power is curtailed until voltage issues are resolved.A simulation based on a real 37-node rural distribution network shows that the proposed method significantly reduces PV curtailment.Typical daily results indicate a curtailment rate of 1.47%,which is significantly lower than the 15.4%observed with the voltage droop-based control method.The total daily PV power output(measured every 15 min)increases from 5.55 to 6.41 MW,improving PV hosting capacity.展开更多
In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this pape...In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection.展开更多
通过系统在不同运行模式下的实验研究,分析太阳辐照度、温度等参数对系统光伏光热性能的影响,结果表明光伏热泵组件发电效率比传统光伏组件提高16.4%;在获得同样热水情况下,混联运行比串联运行每天多输出1.7 k Wh的净发电量,热泵平均COP...通过系统在不同运行模式下的实验研究,分析太阳辐照度、温度等参数对系统光伏光热性能的影响,结果表明光伏热泵组件发电效率比传统光伏组件提高16.4%;在获得同样热水情况下,混联运行比串联运行每天多输出1.7 k Wh的净发电量,热泵平均COP从1.9升高到3.4。间接式光伏热泵系统将集热器的热量在蒸发器与冷凝器间进行合理分配后,比直膨式光伏热泵系统具有更好的综合性能。展开更多
基金the National Natural Science Foundation ofChina (No. 50708105)partly supported by the Natural ScienceFoundation of Anhui Province (No. 070414161), China
文摘In order to utilize solar energy effectively and to achieve a higher electrical efficiency by limiting the operating temperature of the photovoltaic （PV） panel, a novel photovoltaic/thermal solar-assisted heat pump （PV/T-SAHP） system was proposed and constructed. The hybrid solar system generates electricity and thermal energy simultaneously. A distributed parameters model of the PWT-SAHP system was developed and applied to analyze the system dynamic performance in terms of PV action, photothermal action and Rankine cycle processes. The simulation results indicated that the coefficient of performance （COP） of the proposed PV/T-SAHP can be much better than that of the conventional heat pump. Both PV-efficiency and photothermic efficiency have been improved considerably. The results also showed that the performance of this PV/T-SAHP system was strongly influenced by the evaporator area, tube pitch and tilt angle of the PV/T evaporator, which are the key factors in PV/T-SAHP system optimization and PV/T evaporator design.
基金supported by China Postdoctoral Science Foundation(Grant No.2024M752865)Postdoctoral Fellowship Program of CPSF(Grant No.GZC20241531)+2 种基金Shandong Provincial Higher Education Institutions Youth Plan Team(2022KJ081)the Double First-Class Discipline Construction Fund Project of Harbin Institute of Technology at Weihai(2023SYLCB04)the Open Funding of the Research Center of Civil,Hydraulic and Power Engineering of Xizang(XZA202405CHP2002B).
文摘This study presents a systematic numerical analysis of wind loads on offshore photovoltaic(PV)panels.A computational fluid dynamics(CFD)model,incorporating a free-surface wave boundary condition,is developed and validated against experimental data.Parametric investigations quantify the effects of wind speed,panel tilt angle,clearance,and wave characteristics on the aerodynamic coefficients(drag,lift,and moment).Results indicate that all force coefficients increase with wind speed,with the lift coefficient being most sensitive to wave action.While a larger tilt angle intensifies airflow disturbance and amplifies the coefficients,this effect is more pronounced over flat ground than above a wavy surface.As clearance increases,the drag coefficient fluctuates before rising,the lift coefficient exhibits a trough-shaped response,and the moment coefficient increases monotonically,with values consistently higher over waves.Furthermore,the aerodynamic coefficients generally decrease with greater wave height.The maximum wind load occurs directly above the wave trough,and the aerodynamic force coefficient varies non-monotonically with wave position,first decreasing and then increasing.These findings offer practical guidance for the structural design and safety assurance of offshore PV systems.
基金supported by National Natural Science Foundation of China(U1909201,62206062).
文摘Clouds are one of the leading causes of sun shading,which reduces the direct horizontal irradiance and curtails the photovoltaic(PV)power.It is critical to estimate cloud cover to accurately predict PV generation within a very short horizon(second/minute).To achieve the precise forecasting of cloud cover,an image preprocessing method based on total-sky images is proposed to remove the interference and address the image edge distortion issue.An optimal threshold estimation method is further designed to achieve higher cloud identification precision.Considering the cloud's meteorological properties,a random hypersurface model(RHM)based on the Gaussian mixture probability hypothesis density(GM-PHD)filter is applied to track the cloud.The GM-PHD can track the rotation and diffusion of clouds,which helps to estimate sun-cloud collision.Furthermore,a hybrid autoregressive integrated moving average(ARIMA)and backpropagation(BP)neural network-based model is applied for intra-hour PV power forecasting.The experiment results demonstrate that the proposed cloud-tracking-based PV power forecasting model can capture the ramp behavior of PV power,improving forecasting precision.
基金supported by the Provincial Industrial Science and Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.of China,grant number JC2024118.
文摘The dense integration of residential distributed photovoltaic(PV)systems into three-phase,four-wire low-voltage(LV)distribution networks results in reverse power flow and three-phase imbalance,leading to voltage violations that hinder the growth of rural distributed PV systems.Traditional voltage droop-based control methods regulate PV power output solely based on local voltage measurements at the point of PV connection.Due to a lack of global coordination and optimization,their efficiency is often subpar.This paper presents a centralized coordinated active/reactive power control strategy for PV inverters in rural LV distribution feeders with high PV penetration.The strategy optimizes residential PV inverter reactive and active power control to enhance voltage quality.It uses sensitivity coefficients derived from the inverse Jacobian matrix to assign adjustment weights to individual PV units and iteratively optimize their power outputs.The control sequence prioritizes reactive power increases;if the coefficients are below average or the inverters reach capacity,active power is curtailed until voltage issues are resolved.A simulation based on a real 37-node rural distribution network shows that the proposed method significantly reduces PV curtailment.Typical daily results indicate a curtailment rate of 1.47%,which is significantly lower than the 15.4%observed with the voltage droop-based control method.The total daily PV power output(measured every 15 min)increases from 5.55 to 6.41 MW,improving PV hosting capacity.
基金supported by the Gansu Provincial Department of Education Industry Support Plan Project(2025CYZC-018).
文摘In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection.
文摘通过系统在不同运行模式下的实验研究,分析太阳辐照度、温度等参数对系统光伏光热性能的影响,结果表明光伏热泵组件发电效率比传统光伏组件提高16.4%;在获得同样热水情况下,混联运行比串联运行每天多输出1.7 k Wh的净发电量,热泵平均COP从1.9升高到3.4。间接式光伏热泵系统将集热器的热量在蒸发器与冷凝器间进行合理分配后,比直膨式光伏热泵系统具有更好的综合性能。
