Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation,photovoltaic grid-connected systems are usually equipped with energy storage...Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation,photovoltaic grid-connected systems are usually equipped with energy storage units.Most of the structures combined with energy storage are used as the DC side.At the same time,virtual synchronous generators have been widely used in distributed power generation due to their inertial damping and frequency and voltage regulation.For the PV-storage grid-connected system based on virtual synchronous generators,the existing control strategy has unclear function allocation,fluctuations in photovoltaic inverter output power,and high requirements for coordinated control of PV arrays,energy storage units,and photovoltaic inverters,which make the control strategy more complicated.In order to solve the above problems,a control strategy for PV-storage grid-connected system based on a virtual synchronous generator is proposed.In this strategy,the energy storage unit implements maximum power point tracking,and the photovoltaic inverter implements a virtual synchronous generator algorithm,so that the functions implemented by each part of the system are clear,which reduces the requirements for coordinated control.At the same time,the smooth power command is used to suppress the fluctuation of the output power of the photovoltaic inverter.The simulation validates the effectiveness of the proposed method from three aspects:grid-connected operating conditions,frequency-modulated operating conditions,and illumination sudden-drop operating condition.Compared with the existing control strategies,the proposed method simplifies the control strategies and stabilizes the photovoltaic inverter fluctuation in the output power of the inverter.展开更多
The sense of being within a three-dimensional （3D） space and interacting with virtual 3D objects in a computer-generated virtual environment （VE） often requires essential image, vision and sensor signal processing...The sense of being within a three-dimensional （3D） space and interacting with virtual 3D objects in a computer-generated virtual environment （VE） often requires essential image, vision and sensor signal processing techniques such as differentiating and denoising. This paper describes novel implementations of the Gaussian filtering for characteristic signal extraction and waveletbased image denoising algorithms that run on the graphics processing unit （GPU）. While significant acceleration over standard CPU implementations is obtained through exploiting data parallelism provided by the modern programmable graphics hardware, the CPU can be freed up to run other computations more efficiently such as artificial intelligence （AI） and physics. The proposed GPU-based Gaussian filtering can extract surface information from a real object and provide its material features for rendering and illumination. The wavelet-based signal denoising for large size digital images realized in this project provided better realism for VE visualization without sacrificing real-time and interactive performances of an application.展开更多
基金supported by National Natural Science Foundation of China Key program(51937003)。
文摘Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation,photovoltaic grid-connected systems are usually equipped with energy storage units.Most of the structures combined with energy storage are used as the DC side.At the same time,virtual synchronous generators have been widely used in distributed power generation due to their inertial damping and frequency and voltage regulation.For the PV-storage grid-connected system based on virtual synchronous generators,the existing control strategy has unclear function allocation,fluctuations in photovoltaic inverter output power,and high requirements for coordinated control of PV arrays,energy storage units,and photovoltaic inverters,which make the control strategy more complicated.In order to solve the above problems,a control strategy for PV-storage grid-connected system based on a virtual synchronous generator is proposed.In this strategy,the energy storage unit implements maximum power point tracking,and the photovoltaic inverter implements a virtual synchronous generator algorithm,so that the functions implemented by each part of the system are clear,which reduces the requirements for coordinated control.At the same time,the smooth power command is used to suppress the fluctuation of the output power of the photovoltaic inverter.The simulation validates the effectiveness of the proposed method from three aspects:grid-connected operating conditions,frequency-modulated operating conditions,and illumination sudden-drop operating condition.Compared with the existing control strategies,the proposed method simplifies the control strategies and stabilizes the photovoltaic inverter fluctuation in the output power of the inverter.
基金supported by Research Funding of Huddersfield University:GPU-based High Performance Computing for Signal Processing (No. 1008/REU117)
文摘The sense of being within a three-dimensional （3D） space and interacting with virtual 3D objects in a computer-generated virtual environment （VE） often requires essential image, vision and sensor signal processing techniques such as differentiating and denoising. This paper describes novel implementations of the Gaussian filtering for characteristic signal extraction and waveletbased image denoising algorithms that run on the graphics processing unit （GPU）. While significant acceleration over standard CPU implementations is obtained through exploiting data parallelism provided by the modern programmable graphics hardware, the CPU can be freed up to run other computations more efficiently such as artificial intelligence （AI） and physics. The proposed GPU-based Gaussian filtering can extract surface information from a real object and provide its material features for rendering and illumination. The wavelet-based signal denoising for large size digital images realized in this project provided better realism for VE visualization without sacrificing real-time and interactive performances of an application.
