A Novel Concept of Grid Power Control Using Artificial Intelligence
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This book presents the control strategy and steady-state model analysis of a grid-connected wind-photovoltaic (PV) hybrid power system that is proposed. PV power, wind power, and an intelligent power controller make up the system. PV generation systems with non-linear characteristics were subjected to an analysis of their performance using the General Regression Neural Network (GRNN) method. A radial basis function network-sliding mode (RBFNSM) method with good performance for online training is developed to determine the turbine speed in order to maximize wind power extraction.The intelligent...
This book presents the control strategy and steady-state model analysis of a grid-connected wind-photovoltaic (PV) hybrid power system that is proposed. PV power, wind power, and an intelligent power controller make up the system. PV generation systems with non-linear characteristics were subjected to an analysis of their performance using the General Regression Neural Network (GRNN) method. A radial basis function network-sliding mode (RBFNSM) method with good performance for online training is developed to determine the turbine speed in order to maximize wind power extraction.The intelligent controller is made up of a GRNN for maximum power point tracking (MPPT) control and an RBFNSM for rapid and steady power control response. The PV system uses GRNN, and the wind turbine's pitch angle is regulated by RBFNSM. The output signal is used to drive the boost converters in order to achieve the MPPT. The findings of the simulation verify that the suggested hybrid generation system can produce high efficiency when MPPT is used.
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