Impact of Data Granularity and Distribution Network Modeling on the Energy Community Operation

The ongoing energy transition is opening innovative ways in the energy use. The increasingly higher share of Non-Dispatchable Renewable Energy Sources (NDRES) calls on the one hand for matching the loads with the production from NDRES. On the other hand, the trend towards setting up energy communities able to be mostly independent of the main grid requires effective management of the internal grid with the opportunity to offer grid services for proper operation of the main grid. To properly manage the interactions among the energy community members, as well as between the energy community and the main grid, it is necessary to know the correct values of the energy flows, to calculate and allocate the energy losses, and to assess the share between technical and nontechnical losses. This paper shows how the presence of data collected at different time intervals and the use of simplified network models may affect the performance of the energy community electrical infrastructure, creating issues in the internal management of the community and in the interactions with the main grid.