基于模块化多电平换流器的静止同步补偿器(stationary synchronous compensator based on modular multilevel converters,MMC-STATCOM)是高压电力系统中无功补偿的关键设备,其传统线性控制器性能会因运行点的大范围变化而恶化。针对该...基于模块化多电平换流器的静止同步补偿器(stationary synchronous compensator based on modular multilevel converters,MMC-STATCOM)是高压电力系统中无功补偿的关键设备,其传统线性控制器性能会因运行点的大范围变化而恶化。针对该问题,该文提出了一种基于滑模状态反馈精确线性化的非线性智能控制策略,首先通过选择合适的输出函数、坐标变换,将不做任何简化的3阶MMC-STATCOM非线性模型转化为一个可控的Brunovsky标准型线性系统,并通过数学理论证明了该模型满足精确线性化条件。然后采用改进的粒子群算法配置其反馈增益矩阵,利用积分滑模控制计算其平衡点。最后通过状态反馈使各个状态变量快速收敛至平衡点。将该控制策略与传统PI控制、LQR状态反馈控制通过硬件在环实时仿真平台进行对比实验,结果表明该控制策略具有更好的动态特性、暂态稳定性、鲁棒性,尤其适用于运行环境发生大扰动时。此外,该控制策略的设计过程可以拓展应用于其他类型的柔性交流输电装置。展开更多
With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered wide...With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered widespread attention.To address the challenges of fault feature extraction,this article proposes an end-to-end diagnostic approach based on a wavelet kernel convolutional neural network (WKCNN),capable of extracting multi-scale features from current signals to significantly enhance diagnostic accuracy.This method directly uses raw three-phase current signals as input,applying wavelet kernel convolution to automatically capture frequency-domain fault features,combined with a Softmax classifier optimized by the Adam algorithm to achieve fault diagnosis for NPC threelevel inverters.Experimental results under various operating conditions demonstrate that this approach maintains robust diagnostic accuracy across multiple fault scenarios,with comparative analysis further confirming its advantages in diagnostic efficiency and performance over traditional machine learning and other deep learning methods.展开更多
With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as...With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as promising technologies for mitigating grid oscillations and enhancing system flexibility.However,the excitation converters in DFVS-PSUs are prone to significant issues such as elevated common-mode voltage(CMV)and neutral-point voltage(NPV)fluctuations,which can lead to electromagnetic interference and degrade transient performance.To address these challenges,an optimized virtual space vector pulse width modulation(OVSVPWM)strategy is proposed,aiming to suppress CMV and NPV simultaneously through coordinated multi-objective control.Specifically,a dynamic feedback mechanism is introduced to adjust the balancing factor of basic vectors in the synthesized virtual small vector in real-time,achieving autonomous balancing of the NPV.To address the excessive switching actions introduced by the OVSVPWM strategy,a phase duty ratio-based sequence reconstruction method is adopted,which reduces the total number of switching actions to half of the original.A zero-level buffering scheme is employed to reconstruct the single-phase voltage-level output sequence,achieving peak CMV suppression down to udc/6.Simulation results demonstrate that the proposed strategy significantly improves electromagnetic compatibility and operational stability while maintaining high power quality.展开更多
This paper presents a method for estimating the parameters of DC-link capacitors in three-level NPC voltage source inverters(3L-NPC-VSI)used in grid-tied systems.The technique uses the signals generated by the intermo...This paper presents a method for estimating the parameters of DC-link capacitors in three-level NPC voltage source inverters(3L-NPC-VSI)used in grid-tied systems.The technique uses the signals generated by the intermodulation caused by the PWM strategy and converter topology interaction to estimate the capacitor parameters of the converter DC-link.It utilizes an observer-based structure consisting of a recursive noninteger sliding discrete Fourier transform(rnSDFT)and an RLS filter improved with a forgetting factor(oSDFT-RLS)to accurately estimate the capacitance and equivalent series resistance(ESR).Importantly,this method does not require additional sensors beyond those already installed in off-the-shelf 3L-NPC-VSI systems,ensuring its noninvasiveness.Furthermore,the oSDFTRLS estimates capacitor parameters in the time-frequency domain,enabling the tracking of capacitor degradation and predicting potential faults.Experimental results from the laboratory setup demonstrate the effectiveness of the proposed condition monitoring method.展开更多
文摘基于模块化多电平换流器的静止同步补偿器(stationary synchronous compensator based on modular multilevel converters,MMC-STATCOM)是高压电力系统中无功补偿的关键设备,其传统线性控制器性能会因运行点的大范围变化而恶化。针对该问题,该文提出了一种基于滑模状态反馈精确线性化的非线性智能控制策略,首先通过选择合适的输出函数、坐标变换,将不做任何简化的3阶MMC-STATCOM非线性模型转化为一个可控的Brunovsky标准型线性系统,并通过数学理论证明了该模型满足精确线性化条件。然后采用改进的粒子群算法配置其反馈增益矩阵,利用积分滑模控制计算其平衡点。最后通过状态反馈使各个状态变量快速收敛至平衡点。将该控制策略与传统PI控制、LQR状态反馈控制通过硬件在环实时仿真平台进行对比实验,结果表明该控制策略具有更好的动态特性、暂态稳定性、鲁棒性,尤其适用于运行环境发生大扰动时。此外,该控制策略的设计过程可以拓展应用于其他类型的柔性交流输电装置。
基金supported in part by Zhejiang Provincial“Pioneer”and“Leading Goose”R&D Program of China under Grant 2024C01014the National Natural Science Foundation of China under Grant52177055。
文摘With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered widespread attention.To address the challenges of fault feature extraction,this article proposes an end-to-end diagnostic approach based on a wavelet kernel convolutional neural network (WKCNN),capable of extracting multi-scale features from current signals to significantly enhance diagnostic accuracy.This method directly uses raw three-phase current signals as input,applying wavelet kernel convolution to automatically capture frequency-domain fault features,combined with a Softmax classifier optimized by the Adam algorithm to achieve fault diagnosis for NPC threelevel inverters.Experimental results under various operating conditions demonstrate that this approach maintains robust diagnostic accuracy across multiple fault scenarios,with comparative analysis further confirming its advantages in diagnostic efficiency and performance over traditional machine learning and other deep learning methods.
文摘With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as promising technologies for mitigating grid oscillations and enhancing system flexibility.However,the excitation converters in DFVS-PSUs are prone to significant issues such as elevated common-mode voltage(CMV)and neutral-point voltage(NPV)fluctuations,which can lead to electromagnetic interference and degrade transient performance.To address these challenges,an optimized virtual space vector pulse width modulation(OVSVPWM)strategy is proposed,aiming to suppress CMV and NPV simultaneously through coordinated multi-objective control.Specifically,a dynamic feedback mechanism is introduced to adjust the balancing factor of basic vectors in the synthesized virtual small vector in real-time,achieving autonomous balancing of the NPV.To address the excessive switching actions introduced by the OVSVPWM strategy,a phase duty ratio-based sequence reconstruction method is adopted,which reduces the total number of switching actions to half of the original.A zero-level buffering scheme is employed to reconstruct the single-phase voltage-level output sequence,achieving peak CMV suppression down to udc/6.Simulation results demonstrate that the proposed strategy significantly improves electromagnetic compatibility and operational stability while maintaining high power quality.
基金funded by the Brazilian National Council for Scientific and Technological Development—CNPq(CNPq grant number 405997/2022-1)supported by the EMBRAPII VIRTUS Competence Center in Intelligent Hardware for Industry—VIRTUS-CC(MCTI grant number 055/2023).
文摘This paper presents a method for estimating the parameters of DC-link capacitors in three-level NPC voltage source inverters(3L-NPC-VSI)used in grid-tied systems.The technique uses the signals generated by the intermodulation caused by the PWM strategy and converter topology interaction to estimate the capacitor parameters of the converter DC-link.It utilizes an observer-based structure consisting of a recursive noninteger sliding discrete Fourier transform(rnSDFT)and an RLS filter improved with a forgetting factor(oSDFT-RLS)to accurately estimate the capacitance and equivalent series resistance(ESR).Importantly,this method does not require additional sensors beyond those already installed in off-the-shelf 3L-NPC-VSI systems,ensuring its noninvasiveness.Furthermore,the oSDFTRLS estimates capacitor parameters in the time-frequency domain,enabling the tracking of capacitor degradation and predicting potential faults.Experimental results from the laboratory setup demonstrate the effectiveness of the proposed condition monitoring method.
