Development and implementation of a novel maximum power point tracking algorithm for photovoltaic systems

This thesis proposes a new method for tracking Maximum Power Points (MPP) of photovoltaic (PV) arrays. Different from the existing methods, the proposed method adds hardware dynamism to the Maximum Power Point Tracking (MPPT) algorithms. This dynamism is achieved through an uncomplicated and feasible PV array reconfiguration strategy, which is achieved by relocating the PV array interconnects. By integrating this strategy into the MPPT algorithm, an MPPT approach that can modify the PV array interconnections is developed. The new approach is able to increase the power generated from the PV array under different environmental conditions thanks to its ability to revise the PV characteristic curve. The applicability of the proposed approach is tested on a Particle Swarm Optimization (PSO) based MPPT algorithm, and its performance is tested under simulation and real conditions. The proposed approach for different partial shadowing cases achieves at least 9% power improvement compared to commonly used algorithms such as PSO and P&O.