## 5 Discussion
Also, it has to be noted, that Req is the parameter of equivalent circuit and it is influenced by the mismatch between equivalent schematics (Figure 4) and electrical circuit used to generate training and testing datasets (Figure 1) or real electrical grid topology (in case of experimental testing in this article Figure 13). Therefore, the cause of samples dispersion is not only due to random measurement errors (outlier detection could reduce the dispersion of the mean estimate) of meters but also due to the power consumption and locations in the grid (Figure 4) and consumer power step size and consumption before the power step. Even though \(R_{eq}\) could be affected by these factors, it is the most important that its repeatability is ensured during testing compared to training phase. A way to reduce dispersion of mean value of \(R_{eq}\) is to seek for the similar conditions (same power steps, same initial consumer consumption, same total grid consumption) of \(R_{eq}\) sampling both during training and testing phases. Equivalent circuit parameter \(R_{eq}\) is aimed to model the distribution branch ohmic resistance, but it has to be non-sensitive to other mentioned power consumption conditions. The similar consideration for \(dP_{n}\) dispersion reduction applies. The research must also continue in the aiming at method verification in real grid conditions. The key assumption of the event-driven technique [37] is that probability of power consumption changes of other consumers except the consumer whose load is metered by MUT is very low at the moment of power event (consumption change). Electrical quantities (voltage, current, power) before and after the power event are sampled during the time interval of 10 s before to 10 s after the moment of sudden power change. If at the same moment (in the period of 20 s) power events take place not only in the load of consumer monitored by MUT but at some other consumer loads, then the power balance equation definition (1) becomes not valid. Therefore, it is important that within this period (20 s) a consumption of other consumers remain constant, because their power consumption fluctuations influence readings of the sum meter. In case these rear events of overlapping of power consumption changes due to other consumers load activities, the data acquired at the moment of this power step must be rejected and not used for the PCC in the branch prediction or MUT gain error detection. Though not applied in this research (in synthesized data set and during experimental testing overlapping of power events was prevented), a quite simple rejection rules can be suggested, like if the difference between sum meter and consumer MUT power change differs more than a preset threshold, for example 10% (because typically power losses in LV distribution grid is less than 5%). If power consumption before and after the power step is non-constant due to some power consumption transient processes or dynamic behavior, certain power step samples processing is applied as described in [37]. It is specified that the average of 10 samples (10 s) of V/I/P before power step and average value of 10 samples (10 s) of V/I/P after power step are used to calculate V/I/P values before and after the power steps. Therefore, fluctuations of power V/I/P are suppressed and their influence on \(dP\), \(dV\), and \(dl\) is minimized. The influence of network noise did not deteriorate method performance during testing with experimental test bench, which was power from a LV network. A more extensive verification with sum meter placed at some network node closer to the transformer is underway and will be reported in follow-up research. The influence of more specific energy quality indicators like voltage sags remains unexplored and should be targeted in the future. Nevertheless, we do not expect a severe influence because 10 voltage samples before and 10 samples after (sampling period is 1 s) will be always averaged and this should filter several periods voltage magnitude decrease during the sag.