Stochastic modelling of the correlation between transformer loading and distributed energy resources in LV distribution networks

Abstract

The rapid growth of distributed energy resources (DER) poses operational challenges for the low-voltage (LV) distribution networks, such as overloading of the transformer and/or voltage violation. Many smart strategies based on flexibility and coordinated control DER have been developed to address these issues. To facilitate this implementation, this paper presents a stochastic modelling technique, based on the Monte Carlo approach, to analyze the correlation between transformer loading and voltage magnitudes measured at the point of connection (POC) of DER in the network. A case study has been performed using IEEE European LV test feeder and smart meter measurement from the Netherlands to reflect the realistic aspects of operational conditions. Advanced statistical modelling techniques are applied to generate a set of scenarios, consisting of solar irradiation, and EV charging and load consumption profiles. Simulation results reveal a strong linear relationship between transformer loading and voltage magnitudes at the POC of DERs. Thus, these findings can aid in implementing flexibility and coordinated control DERs for congestion management in the LV distribution network.