An increasing number of inverter-based power generators have been connected to the distribution network in recent years. This phenomenon coupled with the adoption of open energy markets has significantly complicated the power-flows on the power networks, requiring advanced and intelligent parameter knowledge to optimise the efficiency, quality and reliability of the system. This study describes a method for identifying parameters associated with the power system model. In particular, the proposed algorithm in this study addresses the line parameter and topology identification task in the scope of state estimation. The goal is to reduce the a priori knowledge for state estimation, and to obtain online information on the power system network. The proposed parameter estimation method relies on injected stimulations in the network. Broadband stimulation signals are injected from distributed generators and their effects are measured at various locations in the grid. To process and evaluate this data, a novel aggregation method based on weighed least squares will be proposed in this study. It combines and correlates various measurements in order to obtain an accurate snapshot of the power network parameters. To test its capabilities, the performance of this algorithm is evaluated on a small-scale test system.