Power flow optimization in distribution networks: Estimating optimal distribution generators through pseudo-inverse analysis

The past decade has witnessed a substantial increase in the integration of generators into distribution networks, owing to their positive impact on network performance. These generators have proven effective in enhancing voltage levels at all buses and reducing power losses in the network. In this study, the authors explore a novel method for estimating the optimal distribution generators, employing an efficient and simplified approach using the Pseudo-Inverse method. By incorporating the generators into a virtual model of the distribution system, the paper identifies constraints necessary for achieving optimum power flow, thus establishing a foundation for target achievement. Since determining the values of the generators can pose challenges and result in nonconvergence of the optimum power flow, the Pseudo-Inverse method is employed to ensure a solution. The research also considers the system's reconfiguration process while estimating the optimal location for large-scale distribution power systems, utilizing a sequential Construction Strategy. The proposed method is applied to various networks, such as IEEE-33 and IEEE-119, demonstrating its effectiveness through comparisons with several contemporary approaches serving the same purpose. The obtained results showcase the superiority of the proposed method and its ability to efficiently achieve the desired goals, despite its simplicity. The proposed method offers several advantages over previous works in terms of minimizing power losses, optimizing voltage levels, and ensuring that current levels in the lines remain within permissible limits.