The peer to peer (P2P) electricity market is gaining global attention with the growing uptake of low carbon technologies in distribution networks. Increasing number of prosumers and consumers are eager to optimize the exploitation of their local energy resources and reduce their electricity expenditures respectively. In the establishment of a fair P2P energy trading environment, viable transactions have to be identified and the sellers require accounting for their share of losses in the network to estimate the power involved in each transaction and determine the sale price. Power flow tracing (PFT) techniques are required. PFT techniques rely on the proportional sharing (PS) principle (Bialek J. , 1996), which is generally accepted, but has never been proved. The purpose of the experiments described in this document is demonstrating that nodes in the network are perfect ‘mixers’ of incoming flows proportionally shared among the nodal outflows. During the 2 weeks Trans-national Access (TA) detailed in this report, 183 tests were carried out over 5 network configurations exposed to three different sort of disturbances. High resolution and accurate records of distorted waveforms were gathered and an appropriate analysis will be regarded during the next months. This has been achieved thanks to the flexibility offered by the Distributed Energy Resources Test Facility (DER-TF) of Ricerca sul Sistema Energetico (RSE S.p.A.). Preliminary findings: Harmonics based disturbances were not the best approach for power flow tracing as the waveforms by the sources side became highly distorted and harmonics in other frequencies appear. The grid forming and grid following modes of operation of the converter-based sources affect the PFT. The application of Wavelet Transform techniques to the signals obtained display an easy recognition of the perturbance events. Open threads: PS demonstration. Converter-based generators modes of operation and their effect over PFT. Usage of signal processing techniques for power quality analysis in microgrids. Including not only Discrete Wavelet Transform analysis but also Stockwell Transform, and Mathematical Morphology.