Artificial Intelligence Based Multiport Converter For Seamless Integration Of Hybrid Energy Sources
This paper presents a multi-port converter (MPC) designed for efficient battery charging and power delivery through multiple output ports using various power sources, including solar PV arrays and the AC grid. The study explores three distinct battery charging modes: PV-only charging, hybrid PV-grid charging, and grid-only charging, each optimized for different conditions. Maximum Power Point Tracking (MPPT) techniques, Power Factor Correction (PFC), and Proportional-Resonant (PR) controllers ensure stable voltage, minimal ripple, and low total harmonic distortion (THD). Additionally, the MPC supports four output port operation modes, enabling flexible power distribution to high-voltage (500V) and low-voltage (36V) loads. Results demonstrate the system’s ability to maintain stable voltage and current levels, smooth mode transitions, and efficient power management under varying source availability. The proposed control strategy, including an Artificial Neural Network (ANN) controller, ensures reliable performance highlighting the system's modularity and adaptability.
Authors
- Mohamed-Salem Ahmed (ORCID: https://orcid.org/0009-0000-0361-0558)
- Alaa A. Mahmoud (ORCID: https://orcid.org/0000-0002-4202-9915)
- Ahmed A. Hafez (ORCID: https://orcid.org/0000-0003-1745-6357)
Institutions
- Assiut University (EG)
- Sohag University (EG)
Publication Details
- Published
- 2025-07-12
- DOI
- https://doi.org/10.1109/imsa65733.2025.11167654
- Primary Topic
- Multilevel Inverters and Converters
- Type
- article
- Field-Weighted Citation Impact
- 0.00