Abstract
In this paper, we propose an Aquila Optimizer (AO) algorithm specific to photovoltaic (PV) energy storage conversion system for the global maximum power point tracking (GMPPT) of a battery in partial shade conditions (PSC). Several simulation experiments were run in the Simulink 2021a environment to evaluate the performance of the suggested MPPT control. The simulation results show the highest accuracy, speed and stability of the suggested AO algorithm under PSC. After being integrated on a "Raspberry Pi 4 Model B" embedded board, the embedded software produced underwent a validation and verification procedure.
Keywords
Maximum power point tracking
Photovoltaic system
Computer science
Algorithm
Battery (electricity)
Raspberry pi
Software
Stability (learning theory)
Power (physics)
Point (geometry)
Real-time computing
Simulation
Embedded system
Engineering
Mathematics
Operating system
Electrical engineering
Subject Areas
Photovoltaic System Optimization Techniques
·Renewable Energy, Sustainability and the Environment ·Physical Sciences
Advanced Battery Technologies Research
·Automotive Engineering ·Physical Sciences
Solar Radiation and Photovoltaics
·Artificial Intelligence ·Physical Sciences
Citations by Year
2023: 4
2024: 6
2025: 10
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).
Affordable and clean energy 87%
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