dc.contributor.author |
Shanthi, T. |
|
dc.contributor.author |
Prabha, S. U. |
|
dc.date.accessioned |
2024-09-13T08:06:32Z |
|
dc.date.available |
2024-09-13T08:06:32Z |
|
dc.date.issued |
2020 |
|
dc.identifier.citation |
Shanthi, T.; Prabha, S.U.: Simulation of MPPT controller with fuzzy logic and neural network for solar PV system with SEPIC converter. Timişoara: Editura Politehnica, 2020. |
en_US |
dc.identifier.issn |
1582-4594 |
|
dc.identifier.uri |
https://dspace.upt.ro/xmlui/handle/123456789/6553 |
|
dc.description.abstract |
Design of maximum power point tracking (MPPT) controller to extract power from the solar panel and to supply a single phase Induction motor is presented in this paper. In the proposed scheme the incremental conductance algorithm is employed to track the maximum power from the solar panel. The DC-DC SEPIC converter and a full bridge inverter are employed as power electronic interface. The speed of the motor with proportional integral (PI) controller, fuzzy logic controller and neural network controller has been measured and the comparison results were presented. The entire system has been modeled and simulated using MATLAB/Simulink software. |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.ispartofseries |
Journal of Electrical Engineering;Vol 20 No 4 |
|
dc.subject |
Maximum Power Point Tracking(MPPT) |
en_US |
dc.subject |
Incremental Conductance |
en_US |
dc.subject |
Photovoltaic (PV) |
en_US |
dc.subject |
PI controller |
en_US |
dc.subject |
Fuzzy logic |
en_US |
dc.subject |
Neural network |
en_US |
dc.subject |
SEPIC converter |
en_US |
dc.subject |
1ɸ induction motor |
en_US |
dc.title |
Simulation of MPPT controller with fuzzy logic and neural network for solar PV system with SEPIC converter [articol] |
en_US |
dc.type |
Article |
en_US |