With estimates of new electric vehicles and plug-in hybrids climbing in every research report, you can already hear politicians boasting about “electric highways” with charging stations sprouting out of the ground outside every Starbucks.
But the truth is most EV owners are going to charge up at home and how long and when they charge will ripple across the power industry, affecting everybody from early adopters accessing “smart house” applications with their iPhones to coal miners shaking the dust out of their boots. Ascend Analytics’s PowerSimm and Curve Developer programs can help portfolio managers keep that ripple from splashing over their profits. Modeling for load, regulations and fuel prices, Ascend products factor risk and uncertainty into decision analysis. Electric vehicles owners promise plenty of both.
A report released in July by the Electric Power Research Institute placed their mid-range prediction at 35 million electric vehicles on the road by 2030 and pegged the annual power consumption for those cars at 80 terawatt hours.
EPRI’s more optimistic estimate brought the number of EVs on the road up to 65 million, more than doubling the electricity demand.
At either number, the impact could be dramatic when residential customers start plugging their cars into high-amp chargers all timed to click on at 9 p.m. spiking the load on a system tuned to off-peak evening hours (a study released in September noted that 89 percent of customers intend to charge their cars at home). Businesses running fleets of EVs and plug-in hybrids could be switching their chargers to “on” at entirely different times.
Utility managers know that off-peak and on-peak load can be served by different mixes of generation assets and they know that mix will shift constantly over time with fuel prices, regulation costs, transmission upgrades and new renewables coming on line. Ascend Analytics products can handle all of that with precision, tallying uncertainty and optimizing financial performance.
With simulations for load, spot market fuel costs, renewables, forward option volatility, weather and regulation modeled in short-term and long-range runs, utility executives can optimize their portfolio to meet the potential growth in off-peak demand. PowerSimm models load by the hour and into the years, with portfolio managers able to look at dispatch scenarios constrained to meet a user-selected set of inputs. PowerSimm also models renewables by site so a manager might know that the night wind picks up at a particular wind farm just in time to charge a factory fleet of plug-in hybrids.
That kind of data granularity will be indispensable to utilities and retailers customizing rate plans for homes equipped with smart meters and vehicle charging stations or business fleets drawing power under demand resource contracts.
Nobody is predicting electric vehicles will replace internal combustion autos tomorrow, but with Ascend Analytics software, portfolio managers can be ready for those changes today.