Modelling Active Distribution Networks under Uncertainty: Extracting Parameter Sets from Randomized Dynamic Responses

This paper deals with the dynamic modelling of distribution systems hosting a large amount of Inverter-Based Generators (IBGs), more precisely their response to large disturbances in the transmission system. It is assumed that the individual behaviour of IBGs and loads is reasonably well captured by a parameterized model, but the values of its parameters are uncertain. Monte-Carlo simulations involving random variations of those parameters are performed. The dynamic response closest to the average is extracted as being representative. A simple procedure is described to stop the simulations as soon as sufficient information is available. Detailed simulation results are provided, relative to a distribution grid with 75 loads and 75 IBGs. The latter are represented by a generic model that reproduces the main requirements of typical grid codes.