| Issue |
E3S Web Conf.
Volume 692, 2026
3rd International Conference on Intelligent and Sustainable Power and Energy Systems (ISPES 2025)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 7 | |
| Section | Energy | |
| DOI | https://doi.org/10.1051/e3sconf/202669201001 | |
| Published online | 04 February 2026 | |
Adaptive Neuro-Fuzzy Energy Management of Grid-Connected PV Systems with Hybrid Storage for Voltage and Frequency Stability
1 Dept.of EEE, B V Raju Institute of Technology, Narsapur, Telangana, India
2 Professor, Dept. of EEE, B V Raju Institute of Technology, Narsapur, Telangana, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS)- smart energy management scheme for a grid-connected hybrid power conversion system integrating photovoltaic (PV) generation, battery, and supercapacitor storage. The devised control maintains stability of the DC-side voltage stability, smooths PV power fluctuations, and ensures reliable operation under variable load and irradiance. Synergistic storage system utilizes a battery for long-term energy balancing and a supercapacitor for transient stabilization. The ANFIS controller adaptively manages power sharing between PV, grid, and storage elements, enhancing power quality and reducing Harmonic content ratio. Simulation results Evident that the proposed ANFIS-based Controller sustains THD at 0.24%, outperforming conventional PI and fuzzy controllers in dynamic response, settling time, and voltage regulation.
Key words: ANFIS controller / Composite energy storage unit / grid-connected PV system / DC-link voltage control / total harmonic distortion (THD) / power management scheme
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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