Bonobo optimizer: dynamically adaptive heuristic for enhanced MPPT in photovoltaic systems under partial shading – experimental validation with buck converter DOI
Soufyane Ait El Ouahab,

Firdaous Bakkali,

Abdellah Amghar

et al.

International Journal of Emerging Electric Power Systems, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 29, 2024

Abstract The integration of shunt bypass diodes in photovoltaic (P-V) module to mitigate hot spots frequently leads the emergence multiple PV array characteristics. Researchers consistently strive develop, integrate, and refine innovative techniques inspired by various natural processes achieve a global optimum that enhances overall efficiency systems. However, these face challenges adapting parameters strike delicate balance between exploration exploitation, which is essential for circumventing local optima, reducing computation times, refining precision optimize energy capture. In this context, paper introduces groundbreaking new adaptive Maximum Power Point Tracking (MPPT) controller social behavior reproductive tactics observed bonobos (BO). This approach underpinned two key strategies: fission fusion, with dynamic parameter adjustment real-time. enables efficient exploitation search space, following positive negative phases BO. method was compared three methods: PSO, DE, ICS, evaluated through six simulation scenarios, ranging from 1 6 peaks, as well experimental scenarios: one uniform other involving partial shading, using an Arduino board buck converter. According comparative analysis, BO algorithm outperforms approaches all performance evaluation parameters. It shows average improvement convergence time more than 39.18 % exceeding 99 %, minimal oscillation steady-state operation. translates into MPE over 96.66 %. Additionally, results confirm findings simulations.

Language: Английский

Intelligent adaptive PSO and linear active disturbance rejection control: A novel reinitialization strategy for partially shaded photovoltaic-powered battery charging DOI

AL-Wesabi Ibrahim,

Jiazhu Xu, Abdullrahman A. Al-Shamma’a

et al.

Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 123, P. 110037 - 110037

Published: Jan. 4, 2025

Language: Английский

Citations

2
Bonobo optimizer: dynamically adaptive heuristic for enhanced MPPT in photovoltaic systems under partial shading – experimental validation with buck converter DOI
Soufyane Ait El Ouahab,

Firdaous Bakkali,

Abdellah Amghar

et al.

International Journal of Emerging Electric Power Systems, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 29, 2024

Abstract The integration of shunt bypass diodes in photovoltaic (P-V) module to mitigate hot spots frequently leads the emergence multiple PV array characteristics. Researchers consistently strive develop, integrate, and refine innovative techniques inspired by various natural processes achieve a global optimum that enhances overall efficiency systems. However, these face challenges adapting parameters strike delicate balance between exploration exploitation, which is essential for circumventing local optima, reducing computation times, refining precision optimize energy capture. In this context, paper introduces groundbreaking new adaptive Maximum Power Point Tracking (MPPT) controller social behavior reproductive tactics observed bonobos (BO). This approach underpinned two key strategies: fission fusion, with dynamic parameter adjustment real-time. enables efficient exploitation search space, following positive negative phases BO. method was compared three methods: PSO, DE, ICS, evaluated through six simulation scenarios, ranging from 1 6 peaks, as well experimental scenarios: one uniform other involving partial shading, using an Arduino board buck converter. According comparative analysis, BO algorithm outperforms approaches all performance evaluation parameters. It shows average improvement convergence time more than 39.18 % exceeding 99 %, minimal oscillation steady-state operation. translates into MPE over 96.66 %. Additionally, results confirm findings simulations.

Language: Английский

Citations

0