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March 18, 2026Scientific Reports2 citationsOpen Access

Enhanced power management in PV-Integrated hybrid energy storage systems using fuzzy 2DOF-PI control optimized by hippopotamus algorithm

HKHossam KotbAKAhmed G. KhairallaHEHesham B. ElRefaie

Key Points

  • The research aims to enhance power management in photovoltaic systems using a new control strategy for hybrid energy storage systems.
  • Developed a fuzzy logic-based two-degree-of-freedom proportional-integral controller.
  • Optimized the controller using the hippopotamus optimization algorithm.
  • Simulated the system's performance in MATLAB/Simulink under different solar and load conditions.
  • Compared results with classical PI and other optimized controllers.
  • Achieved at least a 15% improvement in peak overshoot compared to classical methods.
  • Reduced transient duration by 10% relative to alternative optimization techniques.
  • Demonstrated enhanced stability and optimal power distribution in the hybrid energy storage system.

Abstract

Abstract This study presents an advanced control strategy for a standalone photovoltaic (PV) system integrated with a hybrid energy storage system (HESS) comprising batteries and supercapacitors (SCs). The proposed system employs a novel Fuzzy Logic-based Two-Degree-of-Freedom Proportional-Integral (Fuzzy 2DOF-PI) controller, optimized using the Hippopotamus Optimization (HO) algorithm, to enhance power management and stability. The batteries address long-term energy demands, while SCs handle instantaneous power fluctuations, mitigating stress on the batteries and extending their lifespan. The control strategy ensures optimal power distribution, maintains DC bus voltage stability, and prevents battery overcharging by regulating the State of Charge (SOC) within safe limits. The system’s performance is validated through MATLAB/Simulink simulations under varying solar irradiance and load conditions. Comparative analyses with classical PI, Fuzzy PI-based Teaching-Learning-Based Optimization (TLBO), and Particle Swarm Optimization (PSO) demonstrate the better dynamic response, reduced transient time, and minimized overshoot of the proposed approach. Results indicate improvements of at least 15% in peak overshoot and 10% in transient duration, highlighting the robustness and efficiency of the Fuzzy 2DOF-PI controller in hybrid energy storage applications.

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Cite This Study

Kotb et al. (2026) studied this question.

synapsesocial.com/papers/69ba43694e9516ffd37a4a92https://doi.org/10.1038/s41598-026-40106-4
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