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
Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple stake...Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.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
Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH(Noise,Vibration,and Harshness).When analyzing the NVH performance of the vehicle body,the traditional SEA(Statistical Energy Anal...Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH(Noise,Vibration,and Harshness).When analyzing the NVH performance of the vehicle body,the traditional SEA(Statistical Energy Analysis)simulation technology is usually limited by the accuracy of the material parameters obtained during the acoustic package modeling and the limitations of the application conditions.In order to effectively solve these shortcomings,based on the analysis of the vehicle noise transmission path,a multi-level objective decomposition architecture of the interior noise at the driver’s right ear is established.Combined with the data-driven method,the ResNet neural network model is introduced.The stacked residual blocks avoid the problem of gradient dis-appearance caused by the increasing network level of the traditional CNN network,thus establishing a higher-precision prediction model.This method alleviates the inherent limitations of traditional SEA simulation design,and enhances the prediction performance of the ResNet model by dynamically adjusting the learning rate.Finally,the proposed method is applied to a specific vehicle model and verified.The results show that the proposed meth-od has significant advantages in prediction accuracy and robustness.展开更多
Bisphenol A (BPA), an important endocrine disruptor, is used in the manufacturing of various materials, including food packaging. Ingestion of contaminated foodstuffs is, in fact, the most relevant form of exposure to...Bisphenol A (BPA), an important endocrine disruptor, is used in the manufacturing of various materials, including food packaging. Ingestion of contaminated foodstuffs is, in fact, the most relevant form of exposure to this substance. However, scarce data on the presence of this contaminant in milk, or whether different types of food packaging influence food contamination are available in Brazil. This study, therefore, aimed to evaluate the BPA contamination of whole milk (fluid and powder) samples packaged in different types of packaging (Tetra Pak?;PET: Poly (ethylene terephthalate;Metallic can (epoxy resin);Polyethylene (PE) and poly (vinylidene chloride) (PVDC);Laminated Film - Metallized Polyester-Polyethylene and glass) and marketed metropolitan region of Rio de Janeiro, Brazil. An analytical method for the BPA determination in milk was optimized for both fluid (pasteurized and ultra-high temperature) and powdered milk samples. A modified QuEChERS method was applied, and BPA determinations were conducted by ultra-performance liquid chromatography coupled with sequential mass spectrometry (HPLC-MS/MS). The validated method was then applied to 51 milk samples, where BPA was detected in five samples (9.8%) and quantified in two (3.8%).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 in part by National Key R&D Program of China (2021YFB2500600)CAS Youth multi-discipline project (JCTD-2021-09)Strategic Piority Research Program of Chinese Academy of Sciences (XDA28040100)。
文摘Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.
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This research was funded by the SWJTU Science and Technology Innovation Project,Grant Number 2682022CX008the Natural Science Foundation of Sichuan Province,Grant Numbers 2022NSFSC1892,2023NSFSC0395.
文摘Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH(Noise,Vibration,and Harshness).When analyzing the NVH performance of the vehicle body,the traditional SEA(Statistical Energy Analysis)simulation technology is usually limited by the accuracy of the material parameters obtained during the acoustic package modeling and the limitations of the application conditions.In order to effectively solve these shortcomings,based on the analysis of the vehicle noise transmission path,a multi-level objective decomposition architecture of the interior noise at the driver’s right ear is established.Combined with the data-driven method,the ResNet neural network model is introduced.The stacked residual blocks avoid the problem of gradient dis-appearance caused by the increasing network level of the traditional CNN network,thus establishing a higher-precision prediction model.This method alleviates the inherent limitations of traditional SEA simulation design,and enhances the prediction performance of the ResNet model by dynamically adjusting the learning rate.Finally,the proposed method is applied to a specific vehicle model and verified.The results show that the proposed meth-od has significant advantages in prediction accuracy and robustness.
文摘Bisphenol A (BPA), an important endocrine disruptor, is used in the manufacturing of various materials, including food packaging. Ingestion of contaminated foodstuffs is, in fact, the most relevant form of exposure to this substance. However, scarce data on the presence of this contaminant in milk, or whether different types of food packaging influence food contamination are available in Brazil. This study, therefore, aimed to evaluate the BPA contamination of whole milk (fluid and powder) samples packaged in different types of packaging (Tetra Pak?;PET: Poly (ethylene terephthalate;Metallic can (epoxy resin);Polyethylene (PE) and poly (vinylidene chloride) (PVDC);Laminated Film - Metallized Polyester-Polyethylene and glass) and marketed metropolitan region of Rio de Janeiro, Brazil. An analytical method for the BPA determination in milk was optimized for both fluid (pasteurized and ultra-high temperature) and powdered milk samples. A modified QuEChERS method was applied, and BPA determinations were conducted by ultra-performance liquid chromatography coupled with sequential mass spectrometry (HPLC-MS/MS). The validated method was then applied to 51 milk samples, where BPA was detected in five samples (9.8%) and quantified in two (3.8%).
