Which network provides the strongest price signal for EV charging?
The transition to decarbonised and decentralised energy systems is occurring in lockstep with the growth in e-mobility. Whether it’s countries ratcheting up emissions standards, outright bans on new sales of internal combustion engine vehicles or the auto manufacturers simply no longer making them, the future of passenger transport is electric. Even down here in Australia where EVs have struggled the shift to electrification is inexorable.
With this shift comes the need for development in charging infrastructure, and thankfully Australia is doing rather better in this regard with businesses like Jet Charge and Tritium selling EV charging infrastructure all over the world.
The neat thing about EV charging, of course, is that it breaks the mould in terms of vehicle owners needing to drive to a traditional service station to fuel up. EV charging hardware isn’t that expensive and with every business using electricity this means that, much like solar and storage, pretty much anyone can own the necessary charging infrastructure.
There’s already growing interest from businesses wanting to understand how they might be able to offer EV charging to their customers and some of them have been using the Gridcognition digital twin software to help explore their options.
From an energy systems perspective, one of the most interesting characteristics of EV chargers is they pull a lot of current. Even a small single-phase residential charger can draw around 7kW, which for most homes will make it the largest single energy load. If you want to charge faster then of course the numbers get bigger, with the super-fast chargers drawing into the low hundreds of kilowatts these days.
With high current draw comes large demand spikes, and for customers what typically follows large demand spikes is high charges from your local distribution network, who increasingly skew their fees towards demand-based pricing rather than energy consumed.
This has really been brought home to us when we’ve been simulating the impact of EV charging for customers. The process entails firstly simulating how their load shape might look if an EV charger were installed (this is a factor of charging hardware and usage patterns), then pricing this against the various costs they’re exposed to, then assessing how other DER assets like solar and storage might improve the economics and finally taking a look at what fee they’d need to charge for their customers looking to top up the ‘tank’.
Perhaps not surprisingly given the earlier observation that EV chargers are thirsty things, the network charges end up being a big part of the economics, with demand charges in particular looming large. Having only recently looked at how the different distribution networks in Australia provide price signals for solar and battery investment, it seemed like an interesting lens to use to explore EV charging, so that’s what we did.
In this analysis we’ve:
- Taken a C&I load shape representative of a 24/7 retailer, so just the kind of business that might look to offer EV charging to customers, and virtually placed them in each of the 14 major distribution networks in the country. We’ve used the same network tariffs as we previously used for the solar and storage analysis.
- To establish a baseline we’ve calculated the network charges they’d pay based on their business-as-usual energy consumption.
- We’ve then simulated the load shape with the addition of a 50kW EV Charger and used a simple probabilistic model to determine when the charger is used (the analysis is highly sensitive to this usage model). This provides a new load profile, seen as the orange trace in the graphic below.
- We’ve then repriced against the relevant network tariff to establish the additional network charges the site would be liable for.
- Finally, we’ve taken those additional annual costs and divided them by the total kWh of energy supplied through the EV charger to calculate a breakeven charging rate. That is, the price they would need to charge users of the EV charger in order to cover the additional network costs.
Of course, there are other costs associated with this additional energy use but we’re ignoring those in this stripped back analysis. You can click on the graphic below for a higher resolution image.
The final graphic focusses on one particular part of the country and one particular road, the Hume Highway that runs between Melbourne and Sydney, Australia’s two largest cities. At over 800km in length the Hume, marked as a blue line in the graphic, passes through a number of distribution networks and a typical EV will likely require at least a couple of charges along the way.
Whilst in the future we’re likely to see the creation of new network tariffs tailored towards EV charging, what’s clear from this analysis is that if we’re relying on today’s tariffs then owners and operators of EV chargers along this particular stretch of road have a very large spread in the potential running costs of their infrastructure.
Perhaps the most dramatic example of this is the Victoria/NSW border town of Albury-Wodonga. Place your EV charger on the south bank of the Murray River (Ausnet distribution network) and your breakeven cost is in the region of 9c/kWh. Move a kilometre or two north over the river and you’re on Essential Energy turf and facing costs nearly three times as high!
As the two mega-trends of energy system decarbonisation/decentralisation and electrification of transport continue apace we’re increasingly seeing organisations viewing energy in the context of value-generating assets that can sit on their balance sheet, rather than as an inevitable operating cost.
Whether it’s EV chargers, battery storage, solar PV, controllable loads or even hydrogen electrolysers, forward-thinking businesses are looking for a slice of the action, but these investments can be complex and the commercial returns are highly sensitive to load shape, location, market jurisdiction and operating model. Hopefully, this stripped back look at one particular DER asset type and one particular element of the cost/value stack goes some way to illustrating that.