Genetically Optimization of an Asymmetrical Fuzzy Logic Based Photovoltaic Maximum Power Point Tracking Controller
This paper introduces a new fuzzy logic controller (FLC) based photovoltaic (PV) maximum power point tracking (MPPT) optimized with the genetic algorithm (GA). Four FLCs with five and seven numbers of triangular (tri) and generalized bell (g-bell) membership functions (MFs) are analyzed. The perfo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Stefan cel Mare University of Suceava
2017-11-01
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| Series: | Advances in Electrical and Computer Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.4316/AECE.2017.04009 |
| Summary: | This paper introduces a new fuzzy logic controller (FLC) based photovoltaic (PV) maximum power point tracking
(MPPT) optimized with the genetic algorithm (GA). Four FLCs with five and seven numbers of triangular (tri)
and generalized bell (g-bell) membership functions (MFs) are analyzed. The performances of the analyzed
algorithms have been compared with the appropriate performances of the classical perturb and observe (P&O)
algorithm by using the following criteria: the rise time (tr), the tracking accuracy of the output power,
and the energy yield. The results showed that the FL-based PV MPPT controller with seven triangular (7-tri)
MFs provides the best steady-state performances. |
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| ISSN: | 1582-7445 1844-7600 |