It is a curiosity of the energy market that people tend to have a good idea of what gasoline prices are–so they might drive five or 10 miles to a different station to get cheaper gas–but don’t know what they’re paying for electricity at home. What’s my charge per-kilowatt-hour this afternoon? Couldn’t tell you.
That is likely to change, as utilities roll out home smart meters, and systems like one being developed by IBM for charging electric vehicles come to market.
IBM’s system, which it is developing with the Swiss utility EKZ, allows customers to see from a mobile handset what the current cost of electricity is, and to decide the best moment to charge their EVs. It works from a simple app, which links to a book-sized unit in a car, and the grid itself, which relays information on power availability. Drivers can see whether their car needs topping up, then decide when to charge, and whether to use conventional or renewable output. If the car is plugged in, they can even complete the process remotely. “The mobile application essentially allows people to control how their electric vehicle is charged,” says Clay Luthy, IBM’s global distributed energy resource leader. “They can choose to charge immediately, delay the charge until when electricity rates are cheaper, or use an optimized charge schedule.”
The third option turns the timing of the charge over to the utility. It can then schedule when to charge based on the resources available, smoothing out peaks in demand, and avoiding use of backup sources that tend to be more expensive, and worse for the environment.
The app could also help manage the irregularity of renewable energy production. “Electric vehicles can be used to buffer the irregular production of electricity from future renewable sources, which will contribute to the overall stability of the electrical network,” says Peter Franken, head of energy distribution at EKZ.
There are already apps that connect in with home smart meter systems. But the IBM-EKZ system is the first to react to the real-time status of the grid. So, for example, if a truck has knocked over a transformer a hour before, the system will be able to factor the information into the optimization schedule.
Clay says the research project will continue to be piloted for the rest of the year, before it is taken to full commercial trial. He says IBM and EKZ still need to work out the cost incentive that will drive consumers to charge at off-peak times. But he is confident consumers will eventually become more price sensitive, and want to be involved.
“Electric vehicle charging will be part of a shift in how people look at electricity pricing. I think these early adopters of EVs will be early drivers of off-peak charging.”