Smart Control for Renewable Energy Hybrid Systems
Author Information
Author(s): KECHIDA Abdelhak, GOZIM Djamal, TOUAL Belgacem, ALHARTHI Mosleh M., AGAJIE Takele Ferede, GHONEIM S. M., GHALY Ramy N. R.
Primary Institution: Ziane Achour University Djelfa, Algeria
Hypothesis
Can an Adaptive Neuro-Fuzzy Inference System (ANFIS) improve the efficiency of renewable energy hybrid systems?
Conclusion
The proposed ANFIS-based control system significantly enhances the efficiency and performance of renewable energy hybrid systems.
Supporting Evidence
- The ANFIS-based MPPT technique showed a production effectiveness of 99.75%.
- The proposed system maintained stable voltage at the DC bus.
- Simulation results indicated that the proposed approach outperformed traditional methods in energy management.
- The study demonstrated effective load-side management using fuzzy logic.
- The ANFIS controller minimized oscillations and improved response time.
Takeaway
This study shows how smart technology can help solar and wind energy work better together, making it easier to use renewable energy in places without power.
Methodology
The study utilized MATLAB/Simulink to simulate a hybrid system combining photovoltaic and wind energy sources with an ANFIS-based control system.
Limitations
The study primarily focuses on simulation results, which may not fully capture real-world complexities.
Digital Object Identifier (DOI)
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