By regarding the high cost of photovoltaic systems, utilizing the maximum efficiency of these power sources is a fundamental and undeniable necessity. Photovoltaic systems rarely work at the maximum power point, because the output power of the cell is strongly influenced by the two factors of radiation and ambient temperature. Therefore, peak power tracking (MPPT) plays a key role in increasing the efficiency of these systems. By considering the importance of this issue, in this paper a new MPPT method has been presented for dual axial photovoltaic systems. The occurrence of partially shaded conditions for photovoltaic systems is one of challenges of the proposed MPPT approach. Partially shaded conditions reduce the energy obtained from photovoltaic systems and the occurrence of several peak points in their voltage characteristics. In this paper, using a multi-objective genetic algorithm (genetic algorithm with non-dominated sorting), we seek to optimize the proposed target function. This objective function includes maximizing the power output of photovoltaic units in different conditions, including partially shaded conditions and minimizing losses with the presence of these units in the network.
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