Ausgrid - GridFleet DNSP Network Wide Electric Vehicle Forecasts

Evenergi conducted modelling to predict the impact of electric vehicles on distribution networks across 225 postcodes in Ausgrid’s licensed distribution area, using GridFleet’s typology-based methodology.\

The challenge

Provide a projection of electric vehicle maximum demand impacts by postcodes in Ausgrid’s network (225 postcodes in total) that can be used as an input to Ausgrid’s post model adjustment for the zone substation spatial demand forecast for 2020.

The approach

Evenergi, with the collaboration of Ausgrid, has built a bottom-up modelling tool (GridFleet) for predicting the impact of electric vehicles on distribution

Networks. By applying the fundamental principles and algorithms of GridFleet’’s typology-based methodology, the following method was adopted to deliver this project:

Project electric vehicle maximum demand impact based on data obtained for each of the 225 postcodes in the Ausgrid license area based on data obtained from key data sources such as Australian Bureau of Statistics and Ausgrid zone substation interval data.

Produce hourly interval typical load profiles for summer weekday, summer weekend, winter weekday and winter weekend out to 2040

Provide scenario modelling for the five scenarios identified in the Integrated System Plan

The outcome

Evenergi was able to support Ausgrid by projecting detailed allocation of EV load on specific assets across their entire distribution area in half-hourly interval load data based on real typology types in each postcode (buses, fleets, residential, DC fast charging and carparks). The data was used by Ausgrid in its post-model adjustment submission to AEMO and will help drive better investment decisions around network planning.

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