EV growing pains: The evolution of EVs and their growing impact on the electric grid
Published on January 6, 2021
Increasing rates of electric vehicle (EV) adoption and the advances in EV battery and charging technology is changing the impact EVs have on electric utility distribution infrastructure. New electric vehicles differ greatly from older models from as recent as five years ago. They are driven more, they consume more energy, they draw power at a higher energy level and are less predictable.
Long-range battery electric vehicles (BEV) are the most demanding class of electric vehicle from a utility perspective and they are also the fastest growing segment. Long-range BEVs represented over 66% of all new EV sales in the U.S. for 2019, which is up from 14% in 2014. With the popularity of these EVs increasing, along with the expansion of models being offered with higher battery capacities, their potential to disrupt or damage distribution assets will continue to grow. Utility companies can prepare for this by utilizing up-to-date and highly accurate charging load data gathered through territory-specific load profiling.
This report provides an overview of the general types of impact utility companies can inspect from an increase in EV adoption, specifically how the understanding of EV charging load has changed over the last several years. It identifies risks to residential distribution grids created by an increase in long-range battery electric vehicle market share and how to manage this impact.
“Long-range battery electric vehicles (BEV) are the most demanding class of electric vehicle from a utility perspective and they are also the fastest growing segment.”
Analysis from one of the largest electric vehicle data sets
The Geotab Energy team has collected data from over 3,900 vehicles across North America, making this one of the largest and most up-to-date EV charging load studies ever conducted. This study includes 40 different EV makes and models, 10,010,535 charging slices that were grouped into 761,096 charging sessions, 2.3 million hours of charging representing 8,576 MWh of energy, and 28.9 million miles of driving data.
Today’s electric vehicles have a bigger impact on the grid
One of the primary barriers preventing consumers from choosing an electric vehicle are concerns around range, known as “‘range anxiety,” and automobile manufacturers have certainly taken note. The desire to address this need has resulted in significant advancements in battery technology and there are more new EV models on the market today which address the concern of not having enough range.
These long-range BEVs have a battery capacity of 50 kWh or more and can achieve ranges of up to 335 miles. They are a significant improvement over the older models, now referred to as short-range BEVs, which have a battery capacity of under 50kWh and typically achieve a maximum range around 150 miles. Lastly the third type of electric vehicle, the plug-in hybrid electric which is powered by a small battery before switching to an internal combustion engine, has decreased in popularity as drivers try to transition away from fossil fuels.
While this increased range of fully electric vehicles is beneficial for drivers, it creates multiple issues for utility companies. The charging behavior of a long-range BEV is less predictable, since they do not need to be charged every day. Also, since they have larger batteries they either need to be charged for a longer period of time or at a higher power level.
“While this increased range of fully electric vehicles is beneficial for drivers, it creates multiple issues for utility companies.”
Figure 1: When comparing the average monthly driving distance per vehicle, long-range BEVs drive significantly more than the other types of EVs. It should be noted that on average 40.3% of the miles driven by the PHEVs observed were powered by gasoline.
Up-to-date data is required to understand the rapidly evolving electric vehicle industry
The electric vehicle industry is going through significant changes as the rate of EV adoption grows exponentially. This has driven product innovation and as a result there have been considerable improvements in EV technology. While this progression has moved the industry forward it has also rendered data from previous studies obsolete.
The introduction of long-range BEV models such as the Tesla Model 3 and the Chevrolet Bolt, have redefined not only the industry standard for vehicle range, but also vehicle battery capacities and charging capabilities. The Tesla Model 3, which now represents 47% of all 2019 EV sales to date in the U.S., did not come into production until 2017. This drastic change in vehicle sales signifies that previous data, on EV driving and charging behavior, is no longer an accurate representation of today’s vehicle composition.
Figure 2. Long-range BEVs are the most unpredictable and demanding class of electric vehicle, from a utility perspective, and account for 66% of new EV sales in the US.
Today’s EVs use twice as much energy while spending the same amount of time charging
By reviewing a vehicle’s state-of-charge (SOC) you can determine how “full” the battery was when charging started and when charging ended. When comparing 2014 and 2019 vehicle groups it was found that they had similar charging patterns. On average, owners would begin charging events at an SOC in the 40% range and would end in the 80% range.
The total amount of time spent charging per charge for both vehicle groups was also the same averaging between 3 to 3.5 hours. However, when comparing the average amount of energy for a charge session, the 2019 vehicle group consumed almost exactly double the amount of electricity. This is the direct result of the higher proportion of long-range BEVs, as they simply require more energy to fill their batteries.
Long-range BEVs draw electricity at twice the power level
While some aspects of charging behavior is similar, what is dramatically different is the charging load for each charging session. It doubled from 4.5kW on average in 2014 to 9.7kW on average in 2019. The reason for this is that there were more long-range BEVs. These vehicles have larger batteries, which enable the vehicles to drive further distances more frequently. In order to avoid having to charge for longer periods, for the convenience of the EV owner, more power is used when charging. To do this reliably, these owners are relying on faster, higher-powered residential charging equipment.
As the long-range BEV category continues to become more popular, this average will continue to grow. Also it should be noted that this vehicle category is still growing and evolving. More powerful new vehicles, including light-duty trucks, are entering the market. Some of these vehicles feature a 180 kWh battery, which is almost double the capacity of the current long-range BEV. Since it was the growth in battery capacity that has driven changes in EV behavior over the last five years, this new increase will also fundamentally alter the impact EVs have on the grid.
“What is dramatically different is the charging load for each charging session, doubling from 4.5kW on average in 2014 to 9.7kW on average in 2019.”
Long-range BEVs do not charge everyday, making them less predictable and harder to manage
From a load-management perspective, the most challenging aspect of long-range BEVs is trying to predict when charging will occur, as long-range BEVs do not need to be charged every day. To show this, the number of hours spent charging per month was analyzed. The data shows that vehicles spent more time charging per month in 2014 than they did in 2019.
Given that from 2014 to 2019, hours per charging session stayed the same but total hours charging per vehicle per month decreased, this means that drivers are charging less frequently. In fact, in 2019 long-range BEV drivers charged on average 19.18 times per month, compared to 28.67 and 30.73 times per month for short-range BEVs and PHEVs, respectively.
Home charging stations now utilize double the amount of power
Electric vehicle charging technology has evolved to accommodate the needs of newer long-range electric vehicles. There are two types of charging stations used by EV owners at home. Level 1 charging utilizes a standard 110/120V plug which can provide up to 1.9kW of charging power, or approximately 4.5 miles of range per hour.
Level 2 charging utilizes a 208-240V plug and can provide between 2.5 and 19.2kW of charging power and over 40 miles of range per hour, making them the preferred home charging station. Not only are Level 2 charging stations becoming more popular, they are also becoming more powerful. In 2014, the largest-selling EV in the US was the Nissan Leaf, which has a maximum charging capability of 6.6kW. By comparison, the most sold EV in 2019 was the Tesla Model 3, which has a maximum charging capability of 11.5 kW.
Level 2 charging stations account for the majority of away charging as well
While the majority of EV charging still occurs at home, the newer data shows a significant increase in the frequency of charging events away from home. The majority of away charging, which could include workplace charging, charging at stations in public areas such as a mall, or charging at dedicated charging areas, is Level 2 charging and not DCFC fast charging. Since it takes longer for vehicles to be charged at Level 2, this most likely means drivers are using workplace charging stations.
Newer electric vehicles will have a greater impact on the grid
EV charging load is unique and to properly assess its impact data needs to be reviewed at multiple levels, beginning at the system-level. Also, it should be noted that EV charging behavior is influenced by temperature and seasonal climate. More energy is used for comfort features like cabin temperature in the winter, but people drive more miles during the summer months. In order to show these potential impacts, load curves were made for January and July, to represent Winter and Summer. By reviewing the load curves you can see the increase in the average maximum power per vehicle, for both the 2014 and 2019 vehicle groups, is drastic.
The data shown in the load curves includes vehicles that are being influenced by different load management initiatives, including TOU rates and a program that incentivized participants to start charging at midnight. This results in EV charging being shifted to off-peak time periods for both 2014 and 2019 vehicle groups. Since EVs are typically charged as soon as the driver returns from work, when left unmanaged, it is reasonable to assume that this load would have most likely occurred between 5-9pm if it was not shifted. The real insight is the overall growth between the 2014 and 2019 peaks.
Preparing for the day with the highest peak
Utilities are used to planning for the day with the most demand, or the hottest day of the year. EVs also need to be considered in this as they days of highest peaks also take place in the summer and when averaged over a longer period they have a lower peak. When reviewing the single day with the highest peak, representing the hottest day in summer, you can see that the peak load is higher than monthly averages, reaching up to 1.31kW.
“...if you were to examine these peak days closer you would see that long-range BEVs have a much larger impact.”
However, if you were to examine these peak days closer you would see that long-range BEVs have a much larger impact. When comparing the peak day of 100 vehicles, from each vehicle type, you can see that the PHEVs and short-range BEVs bring down the average peak. The group exclusively made up of long-range BEVs and had a significantly high peak of 1.83 kW. This number will continue to grow as more powerful BEVs enter the market.
Long-range BEVs pose a significant risk to the grid by overloading street-level transformers
The reason the 2019 group had higher peaks was a direct result of having more long-range BEVs. When diving deeper into the average power per vehicle for the summer months, you can clearly see the impact of the long-range BEVs. The average maximum power for that vehicle type had peaks that were considerably higher, up to 1.01 kW.
While this might not pose much of a risk at the system-level, it can cause a serious risk at the distribution level. Electric vehicles have been demonstrated not to be distributed evenly across utility service territory. Location, governmental mandates, as well as a number of other factors mean electric vehicles tend to cluster in specific areas. As a result, charging will occur with a larger number of electric vehicles in some areas more than others. It is in these areas where charging load will impact the distribution grid first.
To simulate this, five vehicles from each vehicle type were selected at random and their load was combined for a randomly selected day. This would represent vehicles being charged on the same residential transformer. The long-range BEV group had the highest peak of 7.34kW. As this is the fastest growing type of EV, this number will continue to increase as more powerful BEVs enter the market.
“Electric vehicles have been demonstrated not to be distributed evenly across utility service territory.”
Shifting electric vehicle charging load, without direct load control
As electric vehicle charging load increases it will need to be managed and shifted to more desirable times. There are two primary methods for utilizing a demand response program to control EV charging load: utility-controlled (DLC) and customer controlled (behavioral). Direct load control methods, such as charging station networks, are expensive and only address a small portion of all charging. A behavioral program offers the flexibility to scale, while still offering significant loadshifting capabilities. The load curve below shows the average load from three different groups for the summer of 2019. It should be noted that the goal of these SmartCharge programs was to shift the EV charging load from evening peak-periods to overnight periods with available capacity.
Another consideration is that while a standard residential TOU rate program will influence EV charging, it typically shifts the load to immediately after peak pricing ends. This can result in a secondary coincident peak as other household loads are shifted according. Utilizing an EV-specific TOU program will shift the load further off peak and is more effective.
“A behavioral program offers the flexibility to scale, while still offering significant loadshifting capabilities.”
The impact EVs have on the grid, particularly this risk they pose to damaging distribution assets, has changed dramatically over the last 5 years. Long-range BEVs are very different from older electric vehicles: they are driven more, they consume more energy, they draw power at a higher level and they are less predictable. As the fastest-growing vehicle type, long-range BEVs continue to represent a larger proportion of new EV sales.
The destructive potential of EVs to local transformers was covered in a case study on Integrated DER Planning designed for the Sacramento Municipal Utility District (SMUD). In that study it was estimated that if they continued with their current EV charging management strategy, using an EV rate structure to encourage charging between midnight and 6 am, it could result in overloading up to 17 percent of their service transformers by 2030. While this is startling, what is more concerning is the fact that the EVs observed during that study were not an accurate representation of what is being sold today.With the popularity of long-range BEVs increasing, with new models being offered with much higher battery capacities, their destructive potential on distribution assets will continue to grow.
So while the last 5 years have completely changed the EV ecosystem, it is nothing compared to what is coming in the next five and utilities need to start preparing a solution. In order to create a solution, you need to fully understand the problem and you need data to understand EVs.
Glossary and methodology
Charge session: A term for measuring EV charging, which begins when the battery starts drawing energy and ends once it stops.
During analysis, it was discovered there were multiple occasions where a charge session occurred that lasted for a few seconds. It is hypothesized that these small sessions are a result of battery conditioning within the vehicle. To avoid skewing the data, all charging sessions that occured between consecutive trips were grouped together.
Calculating charging power for the per charge statistics: These values were achieved by measuring the total amount of energy (kWh) provided by the charging station during charging events within a given charge, and then dividing that sum by the total time spent charging.
Calculating maximum power in load curves utilizing charge slices: Charge slices are charging events that are broken into 15-minute intervals. From each charge slice, a maximum power, which is the highest power from the 15-minute interval, is measured. Each data point on a load curve is the average maximum power across charge slices for each 15-minute interval in a day.
Long-range battery electric (LR BEV): A fully- electric vehicle that has a battery capacity of 50 kWh or more.
Plug-in hybrid (PHEV): An electric vehicle which has both an internal combustion engine and an electric engine.
Short-range battery electric (SR BEV): A fully-electric vehicle that has a battery capacity below 50 kWh.
Vehicle composition based on market share from sales data: The single largest differentiating factor between the 2014 and 2019 vehicle groups is market share of long-range BEVs. In 2014 this vehicle type represented 14% of new EV sales. In 2019, the market share of this vehicle type increased to 66%. Market share data was used to simulate an accurate composition of the vehicles being driven in each time period from the available sample set. Each aggregate statistic was calculated by taking a weighted average across vehicle type based on market share. EVs in the 2014 group were drawn from those whose manufacturing date was from 2014 or earlier as determined through VIN verification.
Line loss: None of the energy calculations consider any electricity transmission and distribution (T&D) losses, which could add an average of about 5% to the overall demand.
Battery degradation: Battery degradation is a natural process that permanently reduces the amount of energy a battery can store and EVs, on average, experience a capacity loss of 2.3% per year. As a result, the analysis of driving and charging data from the 2014 group may not be an exact representation of driving and charging behavior during that time period.
Geotab is advancing security, connecting commercial vehicles to the internet and providing web-based analytics to help customers better manage their fleets. Geotab’s open platform and Marketplace, offering hundreds of third-party solution options, allows both small and large businesses to automate operations by integrating vehicle data with their other data assets. As an IoT hub, the in-vehicle device provides additional functionality through IOX Add-Ons. Processing billions of data points a day, Geotab leverages data analytics and machine learning to help customers improve productivity, optimize fleets through the reduction of fuel consumption, enhance driver safety, and achieve strong compliance to regulatory changes. Geotab’s products are represented and sold worldwide through Authorized Geotab Resellers.
© 2021 Geotab Inc.All Rights Reserved.
This white paper is intended to provide information and encourage discussion on topics of interest to the telematics community. Geotab is not providing technical, professional or legal advice through this white paper. While every effort has been made to ensure that the information in this white paper 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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