Electric vehicle smart charging: the transmission-distribution conflict

Electric vehicles will play a key role in decarbonising the transport sector. However, transitioning energy demand from oil to electricity will increase the strain on electricity networks. This will be especially true in countries that primarily rely on gas heating, as their systems typically aren’t designed to handle large loads.

The higher-level national network is referred to as the transmission network (think of those large pylons you see on the sides of motorways). At all times there needs to be an approximate balance between the total power demand and supply on the transmission network. If there is a mismatch in supply and demand, bad things start to happen very quickly (see the UK’s August blackout). One of the particular concerns with electric vehicles is that charging might be concentrated in the evening, which would coincide with the existing peak demand. This would be expensive because additional power plants would need to be built, but they would see a very low utilisation (as they will only be required for a short period each day). 

In order to avoid this, a framework for smart charging is being developed. This will allow users to be reimbursed for delaying charging to a time when the other load on the system is lower. The wholesale electricity price varies significantly throughout the day, as shown in the graph below. This means that, even without accounting for the avoided cost of new power stations, there is potentially a lot of value to be gained by shifting charging to off-peak times. One suggestion for a smart charging system is to use a variable charging tariff whose price moves to reflect the current wholesale electricity price (e.g. the Octopus Energy agile tariff). Then a consumer (or more likely a piece of software) will make decisions to charge so as to minimise cost.

Fig 1: The average wholesale electricity price

A national tariff would have a similar effect on all vehicles regardless of their location. This is potentially problematic because there are also local network constraints that could be violated with vehicle charging. The lower-level network is referred to as the distribution network (think the overhead lines you see on the side of the street). Violation of distribution network constraints has less serious consequences than transmission system limits (e.g. street-wide power cut rather than millions of consumers disconnected), but are still undesirable as they necessitate costly upgrades to the network.

If operated correctly, smart charging could be used to avoid these network. However, it is important that both the transmission network (national scale) and the distribution network (local scale) are considered simultaneously. If smart charging is used only to protect the transmission system, then many additional local networks will require upgrades. If it is used only to protect the distribution network, then additional power plants will be needed. This point is illustrated below.

Fig. 2 shows the estimated GB electricity demand profile with a fully electrified fleet of private vehicles under various charging regimes. As demand must be met at all times, the required power generation capacity is dictated by the peak demand. Three charging schemes are shown: uncontrolled – without smart charging, controlled (T) – smart charging controlled at the transmission level (e.g. national tariff), and controlled (D) – smart charging to protect distribution networks. In terms of peak demand, controlling only for the distribution network is almost as bad as implementing no smart charging.

Fig 2: GB demand with 100% electric vehicle charging

It is worth unpacking this result slightly. Here it has been assumed that charging will occur in residential networks. This means that the existing load on those networks will be mostly household load. Therefore when smart charging is used to protect the local networks it smoothes out the household demand, but doesn’t offset any of the other demand on the system. In the UK a large amount of the electricity demand is industrial (e.g. manufacturing, transport). This demand tends to peak in the middle of the day, hence the new peak in the controlled (D) case.

On the other hand, Fig. 3 shows the percentage of residential networks predicted to experience violations in each charging case. Without wanting to get bogged down by technical details, transformer violations cause street-wide power cuts and voltage violations result in poor power quality in homes at the ends of the network. Either type of violation would necessitate upgrades to the network. Controlling charging at the transmission level reduces the number of constraint violations, but there are still many that could be avoided.

Fig 3: The percentage of networks expected to have constraint violations.

While there is an inherent conflict between the two system levels, it is possible to achieve both the flat national demand and the local network protection simultaneously. This is because there are many networks which have large overheads, meaning they will not hit local constraints even with uncontrolled charging. Fig 4 shows an estimate of the percentage of networks that will experience violations broken down by geography. Both the 100% electrified and the 2030 scenarios are shown.

Fig 4: The percentage of predicted network violations by geography.

Note that these are estimates based on imperfect information; in order to know with certainty the likelihood of a network overload, more extensive monitoring of the distribution system is required. However, these estimates demonstrate the scale of variation that can be expected between networks in different areas. The differences can be attributed to local driving behaviour, network design, and socio-economic factors. For example, many of the worst effected areas are the urban areas outside London, which have high population densities but poor public transport.

If the vehicles on the most constrained networks can be identified, then these can be controlled to protect their local network. Meanwhile, the vehicles on the least constrained networks can over-compensate in order to avoid the midday peak in national demand. This will require a more complicated smart charging system than a national tariff, and may bring up difficult questions when it comes to compensating consumers. However, the result will be a cheaper electricity system – in theory, lower prices for all.

In conclusion, in order to be most effective, smart charging needs to take account of the location of vehicles in the network. Let’s make national tariffs a stepping stone, not the destination.

[A/N] This post covered the core concept from my new journal paper. If you are interested in reading the full manuscript, it is available here.

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