A Novel Control Approach Utilizing Neural Network for Efficient Microgrid Operation with Solar PV and Energy Storage Systems
This article introduces a novel approach for controlling a single-phase grid-connected inverter using neural network technology. While previous studies have primarily focused on voltage control techniques to facilitate power transfer in such systems, this paper advocates for the application of art...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Stefan cel Mare University of Suceava
2024-08-01
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| Series: | Advances in Electrical and Computer Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.4316/AECE.2024.03002 |
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| Summary: | This article introduces a novel approach for controlling a single-phase grid-connected inverter using neural
network technology. While previous studies have primarily focused on voltage control techniques to facilitate
power transfer in such systems, this paper advocates for the application of artificial intelligence for
enhanced efficiency. Specifically, the proposed control method employs a neural network trained for
function approximation to optimize power exchange between the microgrid and the main power grid.
To manage battery operations, a bidirectional converter is utilized, ensuring efficient charging
and discharging. During grid integration mode, voltage regulation within the microgrid is overseen
by the single-phase inverter, whereas boost converters take charge during isolation mode. Results
demonstrate a considerable enhancement in power management between the microgrid and the grid,
alongside effective voltage regulation of the DC bus. |
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| ISSN: | 1582-7445 1844-7600 |