The implementation of genetic algorithm to MPPT technique in a DC/DC buck converter under partial shading condition

The solar home system (SHS) often experience a shading condition that caused by the objects near the PVs installment. The shading affect to the harvesting of power from generation side of the system. The system will experience lower output power because the characteristic of PVs have chance, such as the P-V curve. P-V curve changed by the rapid changing of irradiation level and temperature. In this curve, there is a point that produce highest rate of power harvesting, its called Maximum Power Point (MPP). The MPP Tracking is technique to track the MPP, so the system will run in optimal mode. In the other side, the partial shading to PV surface will cause more than one MPP, even though only one MPP that produce highest rate of output power. It is called global MPP, the other is local MPP. This article shows the genetic algorithm (GA) which is implemented in MPPT technique as a meta-heuristic search. The GA implemented in a DC/DC buck converter with the STM32 F4 microcontroller to run the algorithm and control the converter as real-time. The GA performance is compared to the PO's by their system efficiency, power output, and tracking time. The experimental treatment done by a single tracking cycle and a single solar daily cycle in the roof of Herman Yohanes Building, Universitas Gadjah Mada. The test conducted for single solar daily cycle, shows that GA implementation on MPPT has 91% efficiency (in average) and PO implementation on MPPT has 89% efficiency (in average). In terms of output power, GA has an average output power + 10% higher than PO. While in terms of time tracking, GA has a mean time of + 61% longer than the PO.