It’s no overstatement to say that managing today’s electric grid is one of the most complicated exercises in existence. It’s an incredible challenge to supply the precise amount of power at the right level that matches an ever-changing demand for energy to ensure a reliable power supply, all while minimizing waste.
The mismatch in daily energy supply and demand promises to get even more challenging as more renewables come onto the grid. Utilities must not only manage the complexities of distributed generation by redistributing power across a vast service territory, but they must also factor in the intermittent nature of renewables.
For example, Texas recently set a record for wind energy when 40 percent of the state’s energy came from wind for 17 consecutive hours. Of course, once the wind stopped blowing, grid managers quickly had to ramp up traditional energy sources to maintain supply. A successful price-signaling strategy for consumers can help stabilize the grid while utilities navigate the inherent uncertainty renewables bring to the table.
How to move forward? Many utilities and regulators rely on peaker plants to provide power during energy spikes. While these plants are often relatively costly and dirty, they do ensure reliable supply. On the other side of the equation, demand-side management programs often turn to price signaling, whereby higher prices encourage less energy use. These programs engage customers while avoiding the costs and pollution of building peaker plants, but unfortunately they are not in widespread use—yet.
The commercial and industrial sectors already have made major inroads in balancing the grid with price signals. Through mature demand response programs, utilities and energy companies work directly with large commercial or industrial enterprises to dial the power down with the help of financial incentives.
It’s easier for utilities to work closely with a few enormous energy users than smaller consumers. The reason is because they engage fewer points of contact, all of whom face much larger-than-average energy bills and are more sophisticated about energy management. Price signaling has been proven to make an impact in the commercial and industrial space.
Taking that powerful communications approach to the greater residential market is frankly long overdue. But the residential sector is a harder nut to crack, with millions of stakeholders and much smaller potential savings per customer.
However, we do know that customers consistently change behavior when they receive clear communications about when their rates vary, including incentives like “free night and weekends,” which take advantage of lower-cost energy sources like surplus wind power at night.
A major challenge is that consumers usually have no idea when they’re using energy at peak hours versus hours when the wholesale cost is lower. Most utilities provide simple pricing that’s either fixed or set to a fixed schedule based on the time of day energy is used. These retail pricing models do not necessarily correlate to the variable wholesale energy rate that governs supply and demand on the generation side.
The result is that retail electricity prices don’t reflect actual costs or the interplay of supply and demand. It’s like charging people for groceries based on the time they visit the store rather than the actual cost of the products they buy.
Price signals have been a smash hit in other consumer arenas. The obvious example is Uber, the most popular ridesharing service in the country. High demand for rides triggers surge pricing, which in turn attracts more drivers, solving the driver shortage. Mobile networks instantly deliver clear price signals to passengers and drivers via clear notifications that pop up in the app. To use the service, consumers must engage with these price signals.
The electricity market now has the technology to bring this same level of powerful information to consumers. Through smart meters, mobile apps and new smart grid networks, we can access and present far more real-time data about energy production and consumption than ever before.
For example, Comcast launched Xfinity Home, an energy management service that “that learns heating and cooling patterns of a home for additional energy savings.” Automated thermostats can integrate into the home and time devices to go off or on when the homeowner is actually present and using the devices. Energy disaggregation software like Bidgely analyzes appliance-specific consumption data and can provide recommendations to reduce energy use.
It’s time to fix the information asymmetry between energy supply and demand, create new pricing models and seize new communications channels to bring signals to consumers. We’ve already seen strong progress in consumer DR programs. The next step is simply to provide these price signals around the clock, not simply during peak demand. With the help of intuitive apps, we’ll have a world where consumers modify their behavior due to price signals, much as we select different clothing based on weather reports or take a different route to work based on traffic updates.
As energy demand continues to grow and fragmented renewables gain steam, managing demand will only become more vital to overall grid health. By harnessing price signals to influence consumer behavior to a degree never before possible, we can make enormous strides in stabilizing the grid, reducing power overproduction and enhancing operational efficiency for energy companies and larger grid networks.
About the author: Gregory L. Craig is a 25-year energy industry veteran and the founder and CEO of Griddy, a next-generation energy company. He is also the founder of PowerToConfuse.org.