There are many definitions of coincidence available from different publishers and communities [1].

In most cases, the data is only available or published as a curve on a graph, making it difficult to set up a coincidence definition in PowerFactory.

In such cases, we use tools such as the WebPlotDigitizer (https://automeris.io/) to extract data points from a plot, as we have done for the coincidence curves for rural, urban or metropolitan areas for private EV charging in the appendix.

The data comes from a study provided by the Forum for Network Technology & Network Operation in the German Association VDE: “Ermittlung von Gleichzeitigkeitsfaktoren für Ladevorgänge an privaten Ladepunkten” (translated: Determination of coincidence factors for charging at private charging points. The plot is on page 24, figure 13.

The scenario for the coincidence curves was done for a 11 kW charging point. Depending on the area, the average driving distance of the electric vehicle and the energy consumption have been varied. In metropolitan areas, the average driving distance tends to be shorter than in urban or rural areas. In rural areas, energy consumption tends to be higher due to higher speeds.

The coincidence definitions can be downloaded from "FNN area dependent coincidence curves.pfd". Please note that the curve table has been created using the WebPlotDigitizer, but 100% accuracy is not possible. The data used will be slightly different from the raw data provided by the publisher.

[1] Shawki Ali, Patrick Wintzek and Markus Zdrallek, “Development of Demand Factors for Electric Car Charging Points for Varying Charging Powers and Area Types”, Electricity 2022, 3, 410–441. https://doi.org/10.3390/electricity3030022