Energy transition implies a larger share of the intermittent renewable energy sources connected to the power grid. These utilities can change their production within a short period of time, thus, significantly affecting the voltage conditions and load flows in the grid. This adds to the complexity in achieving required reliability and stability of the system. Proper and timely insight into the grid parameters plays an important role in regulation of such power system. Implementation of Phasor Measurement Units (PMUs) provides information about electrical parameters of the grid with as much as microsecond precision. Therefore, possible occurring dynamical processes could also be observed and regulated in a proper manner. Considering PMU can give information regarding voltage phasor as well as currents of adjacent branches, the observability of the system can be achieved even if some nodes are not equipped with their own PMU. Furthermore, installation of PMU in every node is not economical solution considering the size of the power grid and the number of PMUs accordingly. One should assess the sufficient number of PMUs cautiously and locate them carefully in order to maintain observability, but also to reduce expenses as much as possible. In the grid topology with a vast number of nodes and branches, the usage of metaheuristic optimization algorithms with adequate criteria function and limiting conditions could reduce the computing time compared to the linear and non-linear programming algorithms. In addition, the quality of such solution is also preserved. In this paper, the usage of genetic algorithm is proposed in order to determine the number and position of PMUs for several different grid samples.