ABSTRACT
Solar energy is a sustainable source of energy that is renewable and inexhaustible. It is clean and pollution free in nature; its usage is strongly influenced by environmental and technological aspects. This work mainly focuses on the application of novel optimisation technique for extracting maximum solar energy with the solar photovoltaic (PV) module. The solar radiation and temperature fluctuate throughout the day; hence the maximum power extraction using PV panel is always variable which results in decreasing the efficiency of PV module. Generally, Maximum Power Point Tracking (MPPT) method is widely used for extraction of optimum energy from the solar PV panels under certain conditions. Numerous conventional MPPT methods were developed by the earlier researchers such as Perturbation and Observation, Incremental Conductance and hill climbing for extracting maximum energy at a uniform irradiation level. Most of the conventional MPPT methods are generating errors under certain circumstances and this leads to further reduction in the efficiency of the PV systems. In this context, this research work explores an evolutionary technique referred as Particle Swarm optimisation (PSO) employed in MPPT detection and in harnessing maximum solar power from the solar PV module in order to enhance its efficiency. This work also depicts the superiority of PSO of the MPPT method over Perturbation and Observation approach.
Disclosure statement
No potential conflict of interest was reported by the authors.