DPGS: data-driven photovoltaic grid-connected system exploiting deep learning and two-stage single-phase inverter
The increasing demand for clean energy to address the looming energy crisis has led to the widespread use of photovoltaic grid-connected technology, particularly in microgrids. To fully harness solar energy, this study proposes a data-driven strategy for photovoltaic maximum power point tracking wit...
Main Authors: | Tian, Luyu, Dong, Chaoyu, Mu, Yunfei, Jia, Hongjie |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175604 |
Similar Items
-
Maximum power point controller for large-scale photovoltaic power plants using central inverters under partial shading conditions
by: Karanayil, Baburaj, et al.
Published: (2020) -
Improved ADALINE harmonics extraction algorithm for boosting performance of photovoltaic shunt active power filter under dynamic operations
by: Mohd Zainuri, Muhammad Ammirrul Atiqi, et al.
Published: (2016) -
Active/Reactive Power Control of Photovoltaic Grid-Tied Inverters with Peak Current Limitation and Zero Active Power Oscillation during Unbalanced Voltage Sags
by: Dehghani Tafti, Hossein, et al.
Published: (2018) -
A simplified model of flexible power point tracking algorithms in double-stage photovoltaic systems
by: Utrilla, Candelaria, et al.
Published: (2023) -
A general algorithm for flexible active power control of photovoltaic systems
by: Dehghani Tafti, Hossein, et al.
Published: (2018)