9786207460151 - A Novel Concept of Grid Power Control Using Artificial Intelligence di Daphale, Dhanraj; Moholkar, Shreya; Sawant, Vijay (6 risultati)

Taschenbuch. Condizione: Neu. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch.

Taschenbuch. Condizione: Neu. A Novel Concept of Grid Power Control Using Artificial Intelligence | Dhanraj Daphale (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207460151 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 52 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.