Ternary genetic algorithm for load dynamic balancing in low voltage three-phase 400 V networks

In three-phase low voltage networks, the random behavior of single-phase loads and also their placement in different parts of single-phase feeders, leads to load imbalance in these networks. Unbalanced load causes losses and voltage drop in three-phase feeders. In this paper, using a different proposed approach based on genetic algorithm, N loads are spread over the grid phases so that the minimum current difference between the phases is formed and the ground current approaches zero. The proposed method is compared with the random load distribution method and the results are analyzed. Among the most important results obtained, we can point out the difference in the calculation time of the two methods by reaching an optimal value, and the calculation speed of the proposed method is significantly better. The proposed method can be an effective tool for dividing the load on different phases of the network in order to prevent imbalance.