A novel MPPT technique based on Henry gas solubility optimization

Abstract

Solar energy is the most promising renewable energy resource. In order to harvest maximum solar energy in PV systems, maximum power point tracking (MPPT) techniques have been investigated. In this paper, a novel MPPT technique based on the henry gas solubility optimization (HGO) is proposed. The HGO-based MPPT technique can successfully tackle two major issues of PV systems, including random oscillation caused by traditional MPPT techniques and power loss caused by partial shading (PS). The proposed HGO-based MPPT technique is compared with some state-of-the-art MPPT techniques, including perturb and observe (P&O), particle swarm optimization (PSO), dragonfly optimization algorithm (DFOA), cuckoo search algorithm (CSA), and grasshopper optimization (GHO). The comparative results confirm that the HGO-based MPPT technique can the aforementioned two major MPPT issues and outperform those existing MPPT techniques. Moreover, a study using field atmospheric data is done to estimate the impact on energy harvest during different seasons of a year. The HGO-based MPPT technique is robust and effective in improving power efficiency by 1–4% against some SI (swarm intelligence)-based techniques. Compared with a few traditional gradient-based techniques, the HGO-based MPPT technique reduces the tracking time by 15–30%, the settling time by 20%, and the oscillation by 80%.