为分析智能软开关(soft open point,SOP)连续调节能力对柔性配电网(flexible distribution network,FDN)风险的影响。首先,实现基于三点估计的FDN风险评估方法;采用三点估计法结合交直流交替迭代法和Gram-Charlier级数展开法进行FDN概...为分析智能软开关(soft open point,SOP)连续调节能力对柔性配电网(flexible distribution network,FDN)风险的影响。首先,实现基于三点估计的FDN风险评估方法;采用三点估计法结合交直流交替迭代法和Gram-Charlier级数展开法进行FDN概率潮流计算,获得节点电压与支路有功功率的概率密度函数,使用越限偏移量结合风险偏好型效用函数构建严重度函数,根据风险评估理论建立并计算风险评估指标。其次,在此基础上,提出一种计及SOP参数优化的FDN风险评估方法;以系统总风险最低为目标,建立计及SOP参数优化的FDN风险评估模型,采用粒子群优化算法结合基于三点估计的FDN风险评估方法对其进行求解,用得到的结果去配置SOP,并对此FDN进行风险评估。以3个IEEE 33节点网络通过三端口SOP互联形成的FDN为例,验证了所提风险评估方法的有效性,分析了SOP连续调节能力以及不同接入位置对FDN风险的影响。展开更多
The integration of distributed generation brings in new challenges for the operation of distribution networks,including out-of-limit voltage and power flow control.Soft open points(SOP)are new power electronic devices...The integration of distributed generation brings in new challenges for the operation of distribution networks,including out-of-limit voltage and power flow control.Soft open points(SOP)are new power electronic devices that can flexibly control active and reactive power flows.With the exception of active power output,photovoltaic(PV)devices can provide reactive power compensation through an inverter.Thus,a synergetic optimization operation method for SOP and PV in a distribution network is proposed.A synergetic optimization model was developed.The voltage deviation,network loss,and ratio of photovoltaic abandonment were selected as the objective functions.The PV model was improved by considering the three reactive power output modes of the PV inverter.Both the load fluctuation and loss of the SOP were considered.Three multi-objective optimization algorithms were used,and a compromise optimal solution was calculated.Case studies were conducted using an IEEE 33-node system.The simulation results indicated that the SOP and PVs complemented each other in terms of active power transmission and reactive power compensation.Synergetic optimization improves power control capability and flexibility,providing better power quality and PV consumption rate.展开更多
Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and ...Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.展开更多
This study systematically examines the energy dissipation mechanisms and ballistic characteristics of foam sandwich panels(FSP)under high-velocity impact using the explicit non-linear finite element method.Based on th...This study systematically examines the energy dissipation mechanisms and ballistic characteristics of foam sandwich panels(FSP)under high-velocity impact using the explicit non-linear finite element method.Based on the geometric topology of the FSP system,three FSP configurations with the same areal density are derived,namely multi-layer,gradient core and asymmetric face sheet,and three key structural parameters are identified:core thickness(t_(c)),face sheet thickness(t_(f))and overlap face/core number(n_(o)).The ballistic performance of the FSP system is comprehensively evaluated in terms of the ballistic limit velocity(BLV),deformation modes,energy dissipation mechanism,and specific penetration energy(SPE).The results show that the FSP system exhibits a significant configuration dependence,whose ballistic performance ranking is:asymmetric face sheet>gradient core>multi-layer.The mass distribution of the top and bottom face sheets plays a critical role in the ballistic resistance of the FSP system.Both BLV and SPE increase with tf,while the raising tcor noleads to an increase in BLV but a decrease in SPE.Further,a face-core synchronous enhancement mechanism is discovered by the energy dissipation analysis,based on which the ballistic optimization procedure is also conducted and a design chart is established.This study shed light on the anti-penetration mechanism of the FSP system and might provide a theoretical basis for its engineering application.展开更多
Photovoltaic(PV)panels are essential to the global transition towards sustainable energy,offering a clean,renewable source that reduces reliance on fossil fuels and mitigates climate change.High temperatures can signi...Photovoltaic(PV)panels are essential to the global transition towards sustainable energy,offering a clean,renewable source that reduces reliance on fossil fuels and mitigates climate change.High temperatures can significantly affect the performance of photovoltaic(PV)panels by reducing their efficiency and power output.This paper explores the consequential effect of various rooftop coverings on the thermal performance of photovoltaic(PV)panels.It investigates the relationship between the type of rooftop covering materials and the efficiency of PV panels,considering the thermal performance and its implications for enhancing their overall performance and sustainability.The study compares four rooftop covering materials:wooden flakes packs(both dry and wet),polystyrene,and woolen insulation.The measurements were implemented under Iraqi weather conditions.The comparison was based on the PV panels’thermal behavior and its impact on conversion efficiency.The results revealed that covering the roof beneath the installed PV panels reduces their temperature and increases efficiency.The best performance was observedwhen placingwetwooden flakes beneath the panels,with an efficiency increase of 5%.Moreover,thewoolen insulation offered an efficiency rise of 12%near sunset.Themain outcome of thiswork is that the wet–wooden–flakes showed the best performance improvement of the PV panels.展开更多
Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincia...Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.展开更多
This paper examines the progression and advancements in fault detection techniques for photovoltaic (PV) panels, a target for optimizing the efficiency and longevity of solar energy systems. As the adoption of PV tech...This paper examines the progression and advancements in fault detection techniques for photovoltaic (PV) panels, a target for optimizing the efficiency and longevity of solar energy systems. As the adoption of PV technology grows, the need for effective fault detection strategies becomes increasingly paramount to maximize energy output and minimize operational downtimes of solar power systems. These approaches include the use of machine learning and deep learning methodologies to be able to detect the identified faults in PV technology. Here, we delve into how machine learning models, specifically kernel-based extreme learning machines and support vector machines, trained on current-voltage characteristic (I-V curve) data, provide information on fault identification. We explore deep learning approaches by taking models like EfficientNet-B0, which looks at infrared images of solar panels to detect subtle defects not visible to the human eye. We highlight the utilization of advanced image processing techniques and algorithms to exploit aerial imagery data, from Unmanned Aerial Vehicles (UAVs), for inspecting large solar installations. Some other techniques like DeepLabV3 , Feature Pyramid Networks (FPN), and U-Net will be detailed as such tools enable effective segmentation and anomaly detection in aerial panel images. Finally, we discuss implications of these technologies on labor costs, fault detection precision, and sustainability of PV installations.展开更多
文摘为分析智能软开关(soft open point,SOP)连续调节能力对柔性配电网(flexible distribution network,FDN)风险的影响。首先,实现基于三点估计的FDN风险评估方法;采用三点估计法结合交直流交替迭代法和Gram-Charlier级数展开法进行FDN概率潮流计算,获得节点电压与支路有功功率的概率密度函数,使用越限偏移量结合风险偏好型效用函数构建严重度函数,根据风险评估理论建立并计算风险评估指标。其次,在此基础上,提出一种计及SOP参数优化的FDN风险评估方法;以系统总风险最低为目标,建立计及SOP参数优化的FDN风险评估模型,采用粒子群优化算法结合基于三点估计的FDN风险评估方法对其进行求解,用得到的结果去配置SOP,并对此FDN进行风险评估。以3个IEEE 33节点网络通过三端口SOP互联形成的FDN为例,验证了所提风险评估方法的有效性,分析了SOP连续调节能力以及不同接入位置对FDN风险的影响。
基金supported by the Science and Technology Project of SGCC(kj2022-075).
文摘The integration of distributed generation brings in new challenges for the operation of distribution networks,including out-of-limit voltage and power flow control.Soft open points(SOP)are new power electronic devices that can flexibly control active and reactive power flows.With the exception of active power output,photovoltaic(PV)devices can provide reactive power compensation through an inverter.Thus,a synergetic optimization operation method for SOP and PV in a distribution network is proposed.A synergetic optimization model was developed.The voltage deviation,network loss,and ratio of photovoltaic abandonment were selected as the objective functions.The PV model was improved by considering the three reactive power output modes of the PV inverter.Both the load fluctuation and loss of the SOP were considered.Three multi-objective optimization algorithms were used,and a compromise optimal solution was calculated.Case studies were conducted using an IEEE 33-node system.The simulation results indicated that the SOP and PVs complemented each other in terms of active power transmission and reactive power compensation.Synergetic optimization improves power control capability and flexibility,providing better power quality and PV consumption rate.
基金supported by the National Natural Science Foundation of China(Grant No.52079046).
文摘Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.
基金the National Natural Science Foundation of China(Grant Nos.11972096,12372127 and 12202085)the Fundamental Research Funds for the Central Universities(Grant No.2022CDJQY004)+4 种基金Chongqing Natural Science Foundation(Grant No.cstc2021ycjh-bgzxm0117)China Postdoctoral Science Foundation(Grant No.2022M720562)Chongqing Postdoctoral Science Foundation(Grant No.2021XM3022)supported by the opening project of State Key Laboratory of Explosion Science and Technology(Beijing Institute of Technology)The opening project number is KFJJ23-18 M。
文摘This study systematically examines the energy dissipation mechanisms and ballistic characteristics of foam sandwich panels(FSP)under high-velocity impact using the explicit non-linear finite element method.Based on the geometric topology of the FSP system,three FSP configurations with the same areal density are derived,namely multi-layer,gradient core and asymmetric face sheet,and three key structural parameters are identified:core thickness(t_(c)),face sheet thickness(t_(f))and overlap face/core number(n_(o)).The ballistic performance of the FSP system is comprehensively evaluated in terms of the ballistic limit velocity(BLV),deformation modes,energy dissipation mechanism,and specific penetration energy(SPE).The results show that the FSP system exhibits a significant configuration dependence,whose ballistic performance ranking is:asymmetric face sheet>gradient core>multi-layer.The mass distribution of the top and bottom face sheets plays a critical role in the ballistic resistance of the FSP system.Both BLV and SPE increase with tf,while the raising tcor noleads to an increase in BLV but a decrease in SPE.Further,a face-core synchronous enhancement mechanism is discovered by the energy dissipation analysis,based on which the ballistic optimization procedure is also conducted and a design chart is established.This study shed light on the anti-penetration mechanism of the FSP system and might provide a theoretical basis for its engineering application.
文摘Photovoltaic(PV)panels are essential to the global transition towards sustainable energy,offering a clean,renewable source that reduces reliance on fossil fuels and mitigates climate change.High temperatures can significantly affect the performance of photovoltaic(PV)panels by reducing their efficiency and power output.This paper explores the consequential effect of various rooftop coverings on the thermal performance of photovoltaic(PV)panels.It investigates the relationship between the type of rooftop covering materials and the efficiency of PV panels,considering the thermal performance and its implications for enhancing their overall performance and sustainability.The study compares four rooftop covering materials:wooden flakes packs(both dry and wet),polystyrene,and woolen insulation.The measurements were implemented under Iraqi weather conditions.The comparison was based on the PV panels’thermal behavior and its impact on conversion efficiency.The results revealed that covering the roof beneath the installed PV panels reduces their temperature and increases efficiency.The best performance was observedwhen placingwetwooden flakes beneath the panels,with an efficiency increase of 5%.Moreover,thewoolen insulation offered an efficiency rise of 12%near sunset.Themain outcome of thiswork is that the wet–wooden–flakes showed the best performance improvement of the PV panels.
文摘Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.
文摘This paper examines the progression and advancements in fault detection techniques for photovoltaic (PV) panels, a target for optimizing the efficiency and longevity of solar energy systems. As the adoption of PV technology grows, the need for effective fault detection strategies becomes increasingly paramount to maximize energy output and minimize operational downtimes of solar power systems. These approaches include the use of machine learning and deep learning methodologies to be able to detect the identified faults in PV technology. Here, we delve into how machine learning models, specifically kernel-based extreme learning machines and support vector machines, trained on current-voltage characteristic (I-V curve) data, provide information on fault identification. We explore deep learning approaches by taking models like EfficientNet-B0, which looks at infrared images of solar panels to detect subtle defects not visible to the human eye. We highlight the utilization of advanced image processing techniques and algorithms to exploit aerial imagery data, from Unmanned Aerial Vehicles (UAVs), for inspecting large solar installations. Some other techniques like DeepLabV3 , Feature Pyramid Networks (FPN), and U-Net will be detailed as such tools enable effective segmentation and anomaly detection in aerial panel images. Finally, we discuss implications of these technologies on labor costs, fault detection precision, and sustainability of PV installations.
