It’s 3 p.m. on a warm summer San Diego afternoon. My south facing windows are hot to the touch, but the building air conditioning units efficiently maintain a comfortable temperature. Nevertheless, it’s now time to stretch my legs and breathe some fresh air.

I exit the front door of the building and turn right, following the path along the building through the shade. As I reach the end of the building, once again, I turn right and see a world without prices. That’s right, an electric vehicle with a long extension cord snaking its way into the building.

I can’t speak to the moral qualities of this picture. I do not know what the electric charging arrangement is between the car and building owner. Perhaps there is an agreement or charge back mechanism that allows this person to charge the EV in this manner. Or perhaps it’s just stealing. In fact, I technically don’t know whether or not the car is plugged in beyond the locked mirrored doors.

But, I do consider the economics of this picture and wonder. For the past couple years, utilities have explored time-of-use rates, EV rates, and EV load shape impacts. In all those studies, price is assumed to change customer behavior leading to higher off-peak usages. Yet, sitting before my very eyes is a prime example of what happens in a world with incorrect price signals (whether incorrect, hidden, or ignored). Without an appropriate price signal (or maybe you just don’t care about the cost), the rational thing to do is charge your car during the peak hours just in time for the commute home. As forecasters, let’s hope they get the price signals correct.

Mark Quan on EmailMark Quan on Linkedin
Mark Quan
Principal Forecast Consultant - Itron
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.