Heuristic monitoring method for sparsely measured distribution grids

There is an increasing interest in operating the power system close to its limits in order to avoid grid reinforcements. Distribution management requires the knowledge of grid state parameters, but outfitting grids with a large amount of measurements is costly. Therefore, we developed a new heuristic monitoring method (HMM) for balanced grids that relies only on few mandatory measurements and enables a fast way to monitor the grid for off-limit conditions. Due to a new formulation of the power flow equations, it has a low computational complexity for radial grids. The method analyzes the network topology; network buses are categorized and sorted into branches. Depending on the location of available voltage measurements, the bus powers of the corresponding branches are adjusted iteratively to better fit the measured voltage. To test the performance of our new algorithm, we design an evaluation process to compare our approach with the standard weighted least squares (WLS) state estimation (SE) method. Simulation results on artificial and real unmeshed distribution grids on the medium voltage (MV) level show very promising results, outperforming the WLS estimator even with a high amount of distributed generation (DG)