A continuously rising load demand places an increasing pressure and voltage decrease on the current power distribution network. Due to previously unheard-of issues, including a supply-demand gap, growing costs, and global warming, and the power supply sector urgently needs reform. This, in turn, highlights the significance of an intelligent grid. The smart grid includes generating integration at the distribution level as one of its features. If sized and appropriately located, distributed generation (DG) may significantly reduce power losses in the distribution system. For efficient voltage management, power management, and the reduction of power loss, the position and size of the DG are essential in this new power system topology. This article describes applying a genetic algorithm to reduce distribution losses in a feeder by maximizing the size and placement of DG at an existing radial distribution system that represents load with wind production linked to the substation. The performance of a Genetic Algorithm (GA) depends on several factors that must be accurately calibrated. The work in this article is an effort to address this connecting issue. With a voltage-dependent load model, the natural radial distribution system is considered. In this article, the ideal placement and size of the DG are determined by experimenting with different GA operator combinations while maintaining constant values for factors like population, crossover %, and generation. To examine the impact on active and reactive power loss, the best placement and size are implemented for the most minor loss. In the first instance, the available generation is employed, and the Genetic Algorithm (GA) determines the ideal position; in the second instance, both the optimal placement and size are implemented. The test findings show a 56.49 % decrease in loss if existing DG is linked at the ideal location as per GA and a 91.47 % reduction in loss if the location and size of DG are compared to existing DG, respectively. The evolutionary algorithm GA significantly improves the tail-end voltage and power losses.
Hole et al. (Thu,) studied this question.