Boosting Energy Quality in Hybrid Power Systems Through Fractional-Order Adaptive Fuzzy Logic–Based Direct Power Control of SAPF
The intermittent nature of renewable power sources, nonlinear load effects, and harmonic distortions induced by power electronic converters complicate the maintenance of high energy quality in microgrid-connected hybrid renewable power systems. In a range of operating conditions, conventional strategies-including fractional-order proportional-integral (FOPI) controllers-frequently prove ineffective in delivering both robust harmonic mitigation and expeditious dynamic response. To surmount these constraints, the present paper puts forth an intelligent control solution that is predicated on a fractional-order fuzzy logic (FOFL). The FOFL is integrated into a multi-converter HRPS, comprising a photovoltaic generator, a lithium-ion battery power storage system, and a wind turbine equipped with a permanent magnet synchronous generator. A multifunctional voltage source inverter has been developed to control these parts, which are interfaced via a common DC bus. Through the implementation of MATLAB 2021 simulation studies, the efficacy of the suggested algorithm is verified and evaluated in comparison to the FOPI. The findings indicate that the FOFL enhances system efficacy by minimizing harmonic distortion, improving energy quality, and achieving a faster dynamic response under various circumstances. In the context of grid-connected microgrid environments, the FOFL has been demonstrated to offer superior overall energy management, robustness, and adaptability when compared to other evaluated strategies.
Authors
- Khaoula Nermine Khallouf
- Habib Benbouhenni (ORCID: https://orcid.org/0000-0001-8253-4863)
- Nicu Bizon (ORCID: https://orcid.org/0000-0001-9311-7598)
Institutions
- University Frères Mentouri Constantine 1 (DZ)
- University of Pitesti (RO)
- Hassiba Benbouali University of Chlef (DZ)
- Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Publication Details
- Journal
- Algorithms
- Published
- 2026-05-21
- DOI
- https://doi.org/10.3390/a19050418
- Primary Topic
- Microgrid Control and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00