Debunking the myth: EVs are not air conditioners

Published on June 5, 2019 in Smart Charging by Scott Lepold

Discover why load for electric vehicles can’t be viewed in the same way as air conditioners.

Electric vehicles (EVs) are not just another appliance on the horizon that will consume more energy. Though they can generate more demand than a house, that demand moves and their potential adoption rate is still unclear. What makes these challenges even more difficult for someone managing load is that there isn’t one standalone solution that will work for everyone.

Every service territory is going to have to look at their own unique EV ecosystem. With the evolution of this technology, problems may be approaching quicker than they realize. However, before utilities can come up with a solution for this problem, they need to better understand it.

See also: BYOC: Bring your own car and thinking of EVs as flexible assets

EV technology’s growing place in the market

It’s no surprise that charging electric vehicles is becoming a growing concern for anyone who is managing electrical load. Bloomberg New Energy Finance announced that over 2 million electric vehicles were sold in 2018 and they estimate that number will grow to 56 million by 2040, representing 57% of all passenger vehicle sales.

Global long-term passenger vehicle sales by drivetrain

Figure 1: Annual sales for passenger electric vehicles are expected to rise to 10 million in 2025, 28 million in 2030 and 56 million by 2040.

While 2040 is still a ways off, it’s important for utility companies to start preparing for this increase in demand now. It’s not just a question of how many EVs there will be eventually, but also what type there are currently. With the increases in battery technology, grid disruptions can now occur with fewer vehicles.

New long-range vehicles, such as the Tesla Model X, can have a battery capacity of up to 100 kWh, more than triple the average daily energy consumption of a household in the United States (28.5 kWh). Given that battery range is a primary selling feature for these vehicles, these capacities are going to continue to grow.

You also need to consider new vehicle types, like the planned Rivian R1T electric pickup truck with its 180 kWh battery, that will enter the market in the near future. The concerns brought on by these batteries are further compounded when you realize you will have numerous vehicles charging on the same feeder.

During our study on EV charging load, it was concluded that these electric feeders would overload from the simultaneous charging of as few as five long-range battery electric vehicles (BEV). Once you add the fact that current solutions for managing load are less effective when applied to EV charging, you come to the realization that profiling the EV ecosystem of your territory is critical.

The difference aspects of managing EV load

EV load presents many unique challenges that make it necessary to approach it differently. It’s dynamic and will continue to evolve with the previously mentioned changes in technology as well as the overall increased adoption.

Battery efficiencies and the availability of charging stations will greatly affect driver habits. This poses the next challenge: there is no static location as drivers can charge at home, work or public charging stations.

While it’s been well-established that most EV charging happens at home, this trend is now changing. The reduction in home-based charging coincides with the increase of workplace and public charging — an important distinction.

As EV market share increases, so does the likelihood that there would be more than one EV charging at these locations. The rise in EVs being used as fleet vehicles may also create concern. They will most likely charge at a single location and are less likely to be influenced by curtailment initiatives like time-of use rates.

These clustering effects are also not strictly limited to workplace charging. Socioeconomic factors can also result in a larger number of EVs in specific neighborhoods. Public charging stations are becoming more common in places like retail outlets, universities or hospitals. All of this can create pockets of high demand, making it difficult to plan for infrastructure upgrades.

Lastly, unlike other high demand residential devices such as air conditioners, EVs are used year round. Seasonal weather does affect battery performance but the peak coincident load on distribution infrastructure may not be seasonally impacted.

During the colder months vehicles have to be charged more often. However, overall they are typically driven more in the warmer months. When you consider all of these factors, it’s easy to say that EV load is unlike any other.

Service territories are not as similar as you think

Another challenge when planning for EV load is that no two service territories are alike. At first glance you might think you can compare your territory to another with a similar population or climate. However, this would be a mistake as there are many factors that are being overlooked.

The physical characteristics of an area, such as size, topography or population density, will greatly vary from one another. What is the make-up of city versus highway driving? How many commuters do you facilitate and what are their cycles? Every territory’s total EV market share, as well as model specific market share, will be different and this may influence the number of long-range BEVs versus short range PHEVs.

How drivers charge may also be influenced by local factors, like time-of-use (TOU). Service providers may use TOU rate structures to encourage charging off-peak. However, many workplaces that have charging stations offer free charging to their employees, making these TOU rates a non-issue. Simply put you can’t accurately assume what is in your territory or how it’s being used.

Managing EV Load

Since EV load is different from other types, it needs to be managed differently as well. Pricing signals, like TOU rates, are a common way for utilities to shift load to their off-peak hours. However when applied to EVs, they can create a new problem.

While a static residential TOU rate structure can reduce the amount of morning and midday charging it can also create a new second peak. This unintentional peak often begins immediately after peak-pricing ends and coincides with other shifted loads such as cooking, laundry, etc.

Some utilities may decide to monitor EV charging by installing a submeter, which would then allow them to create a separate EV-specific TOU rate structure. The issue with this is that it’s an expensive and time-consuming process that will require EV owners to have a networked electric vehicle supply equipment (EVSE) to meet regulatory standards. These pricing signals also do not take into consideration mid-trip (also known as opportunity) charging, which cannot be shifted. It also does not encompass the previously discussed workplace charging situation.

Time of peak histogram

Figure 2: Residential load curves for a five-vehicle set in suburban Ontario, where residents pay for electricity on a time of use scaled rate.

Utilities may also be considering using these EVSEs for direct load control. However, this is not a great option as ESVEs cannot detect the vehicle’s battery state-of-charge (SOC). Without this data, in the event of a demand response call, they cannot guarantee the driver will have the amount of charge they need for their next trip.

Managing EV-specific load is going to become a large component of load management. Before figuring out this solution though, you need to fully understand the problems by profiling your territory.

Profiling with vehicle-side data

When collecting data on the EVs in your service territories you have two options: infrastructure-side profiling or vehicle-side profiling. While infrastructure-side profiling can provide you with EV charging data, it’s going to be fragmented.

Firstly, you will only be capturing charge events from networked charging stations. As there are numerous competing networks, you would need to have agreements with each one. Most infrastructure-side profiling only takes home charging into consideration. This means any public or workplace charging wouldn’t be collected.

Even if you collected all home and public networked charging data you still wouldn’t have an accurate representation. Unfortunately, it doesn't factor in Level 1 charging, non-networked Level 2 charging or DCFC charging, which collectively represent the majority of charging.

2019 electric vehicle charging control path market share

Figure 3: 2019 electric vehicle charging control path market share by charging type and level.

Vehicle-side profiling ignores all of these issues by collecting from the EV itself. It is charge station agnostic from both a brand and type perspective. It also collects data regardless of the station’s location. Although, you can limit this through geofences so you aren’t including events that occur outside of your territory. Another benefit of this type of profiling is that you can gather data on the specific make and models of the EVs charging in your area as well as trip related information.

Finally, you can also collect battery SOC data. This data allows for the only direct load control solution, guaranteeing participants will have sufficient range for their next trip.


Electric vehicles are not only disrupting the automotive industry but are forever altering the way utility companies manage electrical load. The increasingly faster adoption rate and the advancing technology is not only a problem for the future but has potential to create one now.

EVs are vastly different from other types of electrical load and need to be treated as such. The first and most crucial step for utility companies is to accurately profile their service territory.

Learn how to profile and manage EV charging load with solutions for electric utilities by Geotab Energy.

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Geotab's blog posts are intended to provide information and encourage discussion on topics of interest to the telematics community at large. Geotab is not providing technical, professional or legal advice through these blog posts. While every effort has been made to ensure the information in this blog post is timely and accurate, errors and omissions may occur, and the information presented here may become out-of-date with the passage of time.

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