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- W2970483797 abstract "This paper presents a control scheme for the optimization of the efficiency of a grid-connected hybrid generation system consisting of a photovoltaic generator and a wind turbine. The design of the control system is made using a Xilinx System Generator tool that allows the future implementation of the code in a Field-Programmable Gate Array board. An online-trained Artificial Neural Network-based control scheme has been used in order to improve the performance of the classical control algorithms. A recurrent Elman Neural Network and a Feed Forward Neural Network have been chosen in order to maximize the power produced by the two renewable energy-based sources. Furthermore, the supervision of the grid-connected inverter is ensured by means of a traditional Voltage Oriented Control scheme. The simulation results, that have been obtained in a Matlab/Simulink environment, prove the effectiveness and the accuracy of the developed control system." @default.
- W2970483797 created "2019-09-05" @default.
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- W2970483797 date "2019-06-01" @default.
- W2970483797 modified "2023-10-15" @default.
- W2970483797 title "XSG-based control scheme for a grid-connected hybrid generation system" @default.
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- W2970483797 doi "https://doi.org/10.1109/ptc.2019.8810731" @default.
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