I’m the last one in my family to own a Tesla. This is an odd statement until you understand that I live in coastal California where a Tesla is as a popular as a Honda Accord. Just yesterday, I counted at least 10 Teslas on my 5-mile commute home.
If I used my commuting observations as an indicator for electric vehicle saturations, my forecast would majorly distorted. Whether it’s overstating saturations (like me) or understating saturation (like some of you), our personal experience is biased and needs a healthy injection of unbiased data.
So, how many EVs are in my area?
The Auto Allianceis an industry trade group that provides statistics on the auto industry. While you can view data by any state, I drilled into California.
Scrolling down to the bottom of the California data, is a section labelled “Registrations”.
And there it is. In 2018, California had 31.5 million registered vehicles and 16.1 million were cars. There are 262,481 electric vehicles which is 0.83% of all vehicles. If you assume all electric vehicles are cars (not a bad assumption), then the ratio is 262,841 to 16,139,269, or 1.6% of cars.
For many, state-level data are not refined enough. In this case, drill down to the congressional district level and do some math. Once you figure out how districts map your service territory, you can get close to what’s registered in your service territory.
On second thought, my perception of electric vehicle ownership in my family isn’t 75% (1 family out of 4), it’s really 30% (3 vehicles out of 10). That make me feel a bit better. After all, it’s all about getting good data.
Mark Quan is a Principal Forecast Consultant with Itron’s Forecasting Division. Since joining Itron in 1997, Quan has specialized in both short-term and long-term energy forecasting solutions as well as load research projects. Quan has developed and implemented several automated forecasting systems to predict next day system demand, load profiles, and retail consumption for companies throughout the United States and Canada. Short-term forecasting solutions include systems for the Midwest Independent System Operator (MISO) and the California Independent System Operator (CAISO). Long-term forecasting solutions include developing and supporting the long-term forecasts of sales and customers for clients such as Dairyland Power and Omaha Public Power District. These forecasts include end-use information and demand-side management impacts in an econometric framework. Finally, Quan has been involved in implementing Load Research systems such as at Snohomish PUD. Prior to joining Itron, Quan worked in the gas, electric, and corporate functions at Pacific Gas and Electric Company (PG&E), where he was involved in industry restructuring, electric planning, and natural gas planning. Quan received an M.S. in Operations Research from Stanford University and a B.S. in Applied Mathematics from the University of California at Los Angeles.
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