Sensorless beta-particle-filter strategy for optimizing solar trackers under Partial Shading Condition

Abstract

The solar tracking system is one of the effective methods to enhance Photovoltaic (PV) power generation efficiency. However, existing systems face challenges in managing power losses when PV panels experience partial shading, resulting in prolonged tracking times and reduced average power output. In this study, we propose a sensorless Beta-Particle-Filter (BPF) solar tracking method that introduces a Beta parameter to define a restricted search area, thereby avoiding unnecessary global exploration. Additionally, a shadow identification process is incorporated, allowing the system to dynamically adjust the initial tracking range according to the shading level, thereby significantly reducing search time. Simulations and experiments demonstrate that the proposed solar tracking method increases the power generation by 60% under the Partial Shading Condition (PSC) compared to the fixed PV panel and achieves an 8% improvement in power generation compared to the latest particle filter method