Managing the impacts of EV charging on the grid


EV CHARGING SERIES

EPISODE 1: INTRODUCING GridFleet FOR DNSPs

At Evenergi we have been working hard towards our mission to support accelerating the adoption of renewably powered electric vehicles and help to ensure the grid can support them.


The approach we have taken is multi-faceted. In addition to removing barriers to electric vehicles adoption for fleets and consumers across Australia, Evenergi also supports Distribution Network Service Providers (DNSPs) in managing impacts of charging electric vehicles on the electricity distribution network.


Impacts of EV charging on the electricity distribution grid


The grid of the future will include a huge number of electric vehicles. Our cities and regions will be filled with smart, connected electric buses, passenger vehicles, logistics related trucks and vans and micro-mobility sources. These may well be autonomous and will include a higher degree of car sharing when it comes to passenger vehicles.


This future state will create new demands on the distribution network. Evenergi has been working with DNSPs to model the impact of electric vehicles charging on the electricity distribution network. This is done by creating a virtual map of regions on the network and bringing together data points and algorithms to create a digital representation of the power that may be used on the network in the future.



Introduction to GridFleet


GridFleet™ is a platform that enables DNSP forecasting teams to spatially allocate demand to specific zone substation areas. It uses real time, catalogued and emulated data to create load curves for summer, winter, weekday and weekend with a focus on annual peaks. Most importantly it includes all typologies that may impact a network - buses, car parks, DC fast charging, fleets and residential. By entering in a specific zone area and some additional information the tool can use its own data sources to produce load curves. The model has been designed to be entirely configurable for forecasters who can manage and modify escalators for all assumptions. It also has a powerful scenario analysis tool that enables you to modify high impact assumptions across all typologies. All the assumptions used in the tool are provided and many of them are user configurable. In addition, the tool allows for new data sources such as locally completed surveys or locally connected vehicle data.

Benefits for DNSPs


GridFleet™ allows DNSP forecasters to take a risk-adjusted view on the impact of eMobility on major assets, giving them the ability to overlay location-specific parameters such as localised demographics, dwelling structures, business types, heavy consumers to produce an output that accurately reflects the impact on a particular zone substation.


Evenergi is constantly adding data sources to improve accuracy and improving emulation algorithms used to produce the forecasts and through addition of this data the model will become more and more robust over time.



Grid impact modelling with GridFleet™


DNSP forecasting teams can leverage GridFleet's scenario planning capabilities in a way that will maximise the social and economic benefits of an eMobility future.


Find out more about GridFleet here.

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