Wideband Identification of Power Network Parameters Using Pseudo-Random Binary Sequences on Power Inverters

Due to the push for renewable energy in the last decades, European countries have witnessed an exponential growth of Distributed Generation (DG) on the Medium Voltage (MV) network. An increasingly large portion of the electricity demand is fed in through the distribution grid, whose good health and operational status will be important for guaranteeing grid stability. In Luxembourg, the distribution network is sparsely monitored and controlled, thus instabilities arising due to line overvoltage or DG malfunctioning are not rapidly detected and resolved. This research discusses a novel and low infrastructure methodology for online monitoring of the distribution grid. Such a tool will be increasingly necessary in order to guarantee the stability, reliability and security of the power network, as a larger and larger portion of the energy demand will be satisfied by DG in future years. In this research, advanced system identification techniques utilized in communications, such as Pseudo-Random Binary Sequences, Successive Interference Cancellation are applied to estimate the transfer function of power network propagation paths. The developed method proposes an online monitoring tool that computes grid parameters in real time during operation, without extensive infrastructure addition, by utilizing the PWM based inverters on the grid for active system identification.