Movement-driven charging demand and the limits of residential-anchored network planning – a Byron Bay case study
Endgame Analytics is pleased to share the third instalment of our decarbonising transport research series, this time turning to the light vehicle fleet and what happens when a large, mobile block of EV charging demand hits a network sized for locals, not visitors.
We modelled a Byron Bay case study, using Compass IoT connected vehicle data to size what an additional 6,000 visiting EVs would do to peak demand for the local substation. This reflects a peak visitor day, when around 40,000 visitors join 11,500 residents, and assumes half of visiting vehicles are electric. We also test how charger speed and tariff-driven charging behaviour change the result.
Some key highlights:
- The peak roughly doubles on convenience charging alone: Against an 11.8 MW summer baseline, 6,000 EVs charging on arrival lift the peak to 23.9–25.1 MW, a 2.0–2.1x multiplier, regardless of charger speed.
- Price signals could make it worse, not better: Time-of-use and solar-sharer tariffs synchronise the fleet to commence charging at the same time. On Level 2 (15 kW) chargers, peak demand rises to 91.9 -98.4 MW, 7.8–8.4x the 11.8 MW baseline, against about 25 MW for convenience charging.
- Even perfect coordination doesn’t fully solve it: even the theoretical best case lifts the peak to 1.07x the baseline (12.6 MW) at 50% EV penetration, which would be 1.7x the baseline (19.5 MW) if EV penetration reaches 100%.
Pricing alone won’t coordinate this load. Direct load control, dynamic operating envelopes, and recognising the value drivers place on mobility will all need to be part of the answer, alongside the case for network augmentation itself.
Read the full paper here
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Endgame Analytics are helping clients navigate these interactions between policy, technology, and economic strategy.
- Martin Chow, Director (Endgame Analytics) | E: martin.chow@endgameanalytics.com.au
- Isaac Mann, Consultant (Endgame Analytics) | E: isaac.mann@endgameanalytics.com.au