Enhancing PV power generation via an adaptive neuro-fuzzy and fast terminal synergetic MPPT approach
The distinct characteristics of photovoltaic (PV) generators related to power and current present a complex problem in terms of optimizing their power output. To tackle this, a Maximum Power Point Tracking (MPPT) interface is required to extract the full power and increase the efficiency. The purpos...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-04-01
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| Series: | Measurement + Control |
| Online Access: | https://doi.org/10.1177/00202940241270647 |
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| Summary: | The distinct characteristics of photovoltaic (PV) generators related to power and current present a complex problem in terms of optimizing their power output. To tackle this, a Maximum Power Point Tracking (MPPT) interface is required to extract the full power and increase the efficiency. The purpose of this research is to propose an innovative method that merges the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Fast Terminal Synergetic Controller (FTSC) to refine the tracking of the optimal power point and to bolster the PV system’s stability in the face of unpredictable scenarios. Simulations conducted using MATLAB/Simulink demonstrate that the ANFIS-FTSC achieves an impressive efficiency of 99.89%, and exhibits fast, robust, and accurate responses compared to other algorithms like FTSC and conventional P&O. |
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| ISSN: | 0020-2940 |