文件名称:R1
介绍说明－－下载内容均来自于网络，请自行研究使用
A grid-connected wind-photovoltaic (PV) hybrid power system is proposed, and the steady-state model
analysis and the control strategy of the system are presented in this paper. The system consists of the PV
power, wind power, and an intelligent power controller. The General Regression Neural Network (GRNN)
algorithm applied to PV generation system which has non-linear characteristic and analyzed performance.
A high-performance on-line training radial basis function network-sliding mode (RBFNSM) algorithm
is designed to derive the turbine speed to extract maximum power the wind.-A grid-connected wind-photovoltaic (PV) hybrid power system is proposed, and the steady-state model
analysis and the control strategy of the system are presented in this paper. The system consists of the PV
power, wind power, and an intelligent power controller. The General Regression Neural Network (GRNN)
algorithm applied to PV generation system which has non-linear characteristic and analyzed performance.
A high-performance on-line training radial basis function network-sliding mode (RBFNSM) algorithm
is designed to derive the turbine speed to extract maximum power the wind.
analysis and the control strategy of the system are presented in this paper. The system consists of the PV
power, wind power, and an intelligent power controller. The General Regression Neural Network (GRNN)
algorithm applied to PV generation system which has non-linear characteristic and analyzed performance.
A high-performance on-line training radial basis function network-sliding mode (RBFNSM) algorithm
is designed to derive the turbine speed to extract maximum power the wind.-A grid-connected wind-photovoltaic (PV) hybrid power system is proposed, and the steady-state model
analysis and the control strategy of the system are presented in this paper. The system consists of the PV
power, wind power, and an intelligent power controller. The General Regression Neural Network (GRNN)
algorithm applied to PV generation system which has non-linear characteristic and analyzed performance.
A high-performance on-line training radial basis function network-sliding mode (RBFNSM) algorithm
is designed to derive the turbine speed to extract maximum power the wind.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
R1.pdf