Simulation and Characterization of Genetic Algorithm Implemented on MPPT for PV System under Partial Shading Condition

On the field of photovoltaic powered system study, there is maximum power point tracking (MPPT) keeps the energy transfer on its peak condition. This condition is on a P-V curve where the characteristic depends on temperature of PV surface and irradiation level. Many algorithms have been established to this MPPT technique including algorithm based on artificial intelligence. One of the algorithms is genetic algorithm (GA) as heuristic algorithm that ran by emulate the process of natural selection. This algorithm application is conducted for MPPT technique. This research was conducted by making model to compare GA to the conventional one, perturb and observe (PO) being used as analytical method. Moreover, correlation analysis was conducted to analyze the characteristics of the GA to MPPT technique. The results of this research presented that the genetic algorithm applied to MPPT had worthy met accuracy on tracking and power output. Whilst correlation test displayed that parameter of individual quantity and generation quantity influenced importantly to the escalation of tracking accuracy and power output.