*4.1. Novel Approach*

The first step to compress and decompress the impedance data is the generation of the dataset obtained from impedance measurements (Section 2). In a second step, the dataset is smoothed to generate a periodic pulse signal with spikes. For this step, either the moving average filter (FIR filter) method or the Δ *sin*-signal method is chosen. The latter method uses the basic function of the voltage output (depending on the measured dataset (7)) to extract the noise of the input function of *U*DS. The basic function (7) is determined by the impedance evaluation program and approximated by using fitting algorithm toolboxes.

$$\text{lI}\_{\text{base}} = -\sqrt{2} \cdot 11.56 \text{ kV} \cdot \sin\left(2\pi \cdot 48 \text{ Hz} \cdot t\right) \tag{7}$$

The result of delta (*<sup>U</sup>*base − *<sup>U</sup>*DS) or the FIR-filter output from delta (*<sup>U</sup>*FIR − *<sup>U</sup>*DS) extracts the difference, the so-called spikes *U*noise, *I*noise, shown in Figure 6. These spikes are challenging to compress and the main reason for the complexity of the developed approach. Typically, existing programs (e.g., smooth from Matlab) smooth out these minimal data swings or spikes directly, thus eliminating the possibility to determine the grid impedance (depending on *U*DS).

**Figure 6.** Overview of *U*DS and generated *U*Base (**a**) and *U*Noise (**b**).

Regarding the current, this procedure can only be carried out with the FIR filter because the *I* function cannot be readjusted similarly.

Step 3 includes the compression of the dataset. Using different types of lossy compression algorithms, the spikes *<sup>U</sup>*noise(C) and the current *<sup>I</sup>*DS(C) are converted into a compressed dataset that is stored or saved in online or local data storage systems by their owner (e.g., distribution grid owner, utilities, etc.). After decompression, the recombination of the basic signal and the decompressed spikes is realised (only for the voltage). A validation of the output signal and an automatic performance check, including a comparison between the different compression approaches, ensues. As a result, the generated grid impedance can be compared to the input dataset (and the determined grid impedance) to determine the differences and whether or not the procedure has to be repeated. A flowchart and overview of these steps are shown in Figure 7.

**Figure**Flowchartofthe novelapproach.

 paper

 **7.**
