NewtonX data collected from 300 executives, senior engineers, and academics in the electric vehicle (EV) sector indicated that there will be a grid tipping point that occurs when 15% of vehicles on the road go electric. At this point, if the grid is not prepared for rising electricity demand during peak hours, entire neighborhoods could experience blackouts and intermittent power loss.
This tipping point is projected to occur by 2033, and much sooner in select pockets, such as in and around San Francisco. Charging one EV is equivalent to adding at least two houses to the power system, and if utilities do not adapt to this demand and identify ways to reduce it and spread the load throughout the day, the entire system could collapse.
A Modern Car and an Ancient Grid: Why EVs Pose Such a Problem
By 2040, electricity consumption from EVs is expected to account for 5% of total global consumption. Currently, the power grid is equipped to handle a certain level of “peak demand,” but if this is exceeded then neighborhoods can experience flickering lights or blackouts. To prevent this from happening, many utilities have already deployed or are developing time-of-use (TOU) rate plans that incentivize charging during off-peak hours. Additionally, utilities companies will need to make the following adjustments over the next decade:
1. Install more distribution transformers
Distribution transformers are the final point of energy transfer between the grid and individual homes. They are used to transform high voltage electricity from the transmission wires into the 240V or 120V electricity that most homes use. This low voltage electricity is safe for homes, but is inefficient for EVs. To meet EV demand, utilities will need to install more transformers so that more high voltage electricity can be transmitted to residential levels.
2. Use sensors and real-time analytics to make the grid smart
As we recently wrote in an article on smart grids, as it stands, when demand outpaces supply, utilities companies turn on fossil fuel-powered plants, called Peaker Plants, to avoid blackouts. This process is incredibly wasteful and expensive, both in terms of consumer cost and in terms of environmental impact. AI-powered systems mitigate the risk of this happening, as they can more accurately predict demand and supply, and can also tweak energy loads to increase efficiency. Additionally, an AI-powered system could buy excess energy from private users who generate and use their own electricity from renewable sources, such as solar roof panels, and send that excess back to the grid. This has major implications for EVs: if they were to charge during peak wind or solar hours, they could end up feeding the grid rather than starving it. An AI-powered grid can also determine optimal charging times for EVs to even consumption load throughout the night and day.
3. Stagger demand to even out peaks and valleys throughout 24 hour periods
To meet the daily peaks and valleys of electricity demand, utilities currently have to go through a cycle of powering plants up and down, which is costly (think of it like turning a light switch on and off over and over again). However, a year-long study in Denmark proved that utilities can use parked electric vehicles to deliver power into the grid and provide owners with a monetary return for doing so. By giving EV owners incentives to charge during off-peak hours, companies both avoid the costly valleys that they currently experience, and also can use EVs as mobile energy storage units to give excess power back to the grid.
The End of the Grid or the Beginning of a Better Grid?
A study of EVs in California (the state with the highest EV density) from 2012 to 2016 indicated that EV owners on time-of-use (TOU) rates charged their vehicles in ways that minimize harm to the grid. TOU rate structures charge customers based on an expensive “on-peak” period, usually weekday afternoons, an affordable off-peak period, usually night and early-morning hours, and a “mid-peak” period. TOU was shown to be effective at encouraging EV owners to shift their electricity usage to low-cost hours.
Additionally, California can be seen as a test case for the true cost of EVs on the grid — and the results demonstrate that the cost is actually exceedingly low. Over the past 5 years, fewer than 0.2% of EVs have caused a distribution transformer or service line upgrade, and the average costs associated with all upgrades have amounted to a mere $21 per vehicle.
While the grid would buckle if we were all to start driving EVs tomorrow, even in neighborhood clusters with a high percentage of EVs, incentive programs and minor updates to grid infrastructure have been sufficient to shoulder the extra electricity demand. As EVs become increasingly popular, utilities will need to continue making the adjustments outlined by the executives, engineers, and academics surveyed by NewtonX, in this article. However, based on California’s success in doing just that, it’s likely that EVs will not destroy the grid — and may even end up helping it.