Comparative analysis of different MPPT techniques using boost converter for photovoltaic systems under dynamic shading conditions

Abstract

Photovoltaic technology acts as an effective alternative to fossil fuels due to its availability, cleanliness, economic and environmental friendliness. However, the performance of photovoltaic systems remains a significant concern in terms of design, measurement, and assessment under different operating conditions to achieve maximum power and efficiency. Since photovoltaic systems offer significantly different power densities due to variations in external conditions. This paper focuses on extracting and tracking maximum power under different shading conditions using a Boost converter. Three MPPT techniques - Perturb and Observe, Incremental Conductance, and Particle Swarm Optimization are implemented on a monocrystalline PV panel with a variable load under dynamic shading conditions using MATLAB/Simulink. Subsequently, the performance of these algorithms is compared, and it is observed that the Perturb and Observe Algorithm failed in many cases, Particle Swarm Optimization was unable to work properly under dynamic shading conditions, and incremental conductance performs better with few failures under some cases. From the average results of all MPPT methods; Perturb and observe, Particle Swarm Optimization and Incremental conductance have average power of 135.9306 W, 137.4167 W and 148.7361 W respectively. It becomes evident from these average values that incremental conductance performs better than the other algorithms.