Enhancing MPPT performance for partially shaded photovoltaic arrays through backstepping control with Genetic...

Area of Science:

• Renewable Energy Engineering
• Control Systems Theory
• Photovoltaic Technology

Background:

• Solar panel performance is crucial, especially at the maximum power point (MPP), but variable weather and partial shadowing in Maroua, Cameroon, reduce efficiency.
• Existing monitoring systems struggle with dynamic environmental conditions, leading to suboptimal energy generation.
• There is a growing need for advanced systems to accurately track the Global Maximum Power Point (GMPP) in challenging solar environments.

Purpose of the Study:

• To introduce a novel approach for tracking the Global Maximum Power Point (GMPP) in photovoltaic systems.
• To enhance the efficiency and adaptability of solar energy systems in the specific environmental conditions of Maroua, Cameroon.
• To develop a system that outperforms existing methodologies in terms of tracking speed and power loss reduction.

Main Methods:

• Utilized a combination of Genetic Algorithm (GA) and Backstepping Controller (BSC) methodologies.
• The BSC dynamically adjusted the duty cycle of a Single Ended Primary Inductor Converter (SEPIC) to match the GA's reference voltage.
• GA was employed to optimize BSC gains for improved performance in Maroua's solar environment.

Main Results:

• The proposed GA-BSC approach demonstrated superior performance compared to INC-BSC, P&O-BSC, GA-BSC, and PSO-BSC.
• The system achieved a stabilization period of fewer than three iterations after shadowing events.
• The Global Maximum Power Point Tracking (GMPPT) methodology significantly reduced power losses by a minimum of 33% compared to Local Maximum Power Point (LMPP) methods.

Conclusions:

• The developed system effectively enhances photovoltaic system efficiency in Maroua by adapting to local solar dynamics.
• The novel approach provides a robust solution for GMPPT, outperforming conventional methods in environments prone to partial shading.
• This research contributes to improved solar energy generation in regions with challenging climatic conditions, minimizing power losses and maximizing energy output.