Utility planning has become increasingly complex. The power system has always been inherently interactive, but new technologies, an increasingly dynamic distribution system, and resource variability have made it more so. We have begun to think more holistically about generation, transmission, and distribution. For example, non-wires alternatives such as distributed storage may replace the need for distribution upgrades, and transmission connecting diverse regions may remove the need to build additional capacity. Another essential tool in this toolbox for planners to meet grid needs is electricity pricing.
In the resource planning process, utilities need to forecast the load that they will serve. Traditionally, they consider historical load patterns, weather, and economic growth projections. They also need to forecast their distributed energy resources (DERs): distributed generation, distributed storage, energy efficiency programs, demand response, and new flexible loads like electric vehicles. They might project from historical trends and add accelerated growth in key DERs where costs or policies are increasing uptake. Based on their net load data, they can optimize for least-cost resource portfolios.
But there’s a chicken and egg problem here: utilities directly influence demand through electricity pricing. For example, time-of-use (TOU) rates act like energy storage — they flatten load profiles. And critical peak pricing acts like peaking plants— they shave peak load. Brattle’s meta-study of 332 dynamic pricing experiments shows that stronger price signals result in greater reduction of peak load. So how are utilities to plan when they simultaneously have the means to justify building new generators and the means to reduce the need for new generators?
Dynamic Pricing Acts Like Other Grid Resources
Historically, regulators and consumer advocates have worried that time-varying rates were too complicated or that low-income consumers did not have the technology to manage their usage. At the same time, utilities had built-in financial incentives to invest in new generation. This resulted in limited efforts in many places, e.g., air-conditioner cycling programs or efficient lighting or appliances, rather than strong price signals to influence customer behavior.
Today we have no excuse to ignore the power of pricing. Moreover, we need this tool to help us achieve our clean energy goals. While my non-college-educated mother got on a TOU rate starting in 1992 and religiously operated her 90’s vintage appliances during off-peak hours, she may have been the exception. Brattle’s meta-study shows that customer responses to time-varying rates are significantly better when enabling technologies, like smart thermostats, are available to them. Many of today’s appliances from electric vehicle chargers to dishwashers to water heaters can be easily scheduled or controlled. For example, the CTA 2045 standard developed in the Pacific Northwest for water heaters is a poster child for a plug-and-play approach to controlling appliances. The ability to control these loads is essential for the ongoing process of electrification, as electrification is a double-edged sword: some of these high-powered loads can create problems if uncontrolled (high penetrations of electric vehicle chargers contributing to peak loading on feeders); alternatively, they can alleviate problems if controlled (scheduling charging during low prices or oversupply conditions). Also, we’re talking about a lot of new demand: studies show demand increasing 50% or even 100% depending on how far we decarbonize our energy economy.
Asking customers to reduce load through demand response or peak time rebate programs are certainly a valuable and useful way to extract flexibility. But the utility needs to establish a baseline and then monitor and verify the reduction which can get complicated and perhaps may be gamed. Pricing is simpler: send customers appropriate pricing signals and let them pay for what they use. It goes without saying that there are limits as to how much volatility and risk customers can manage. Cost-causation and a number of principles (economic efficiency, equity, revenue stability, bill stability, customer satisfaction) outlined by Bonbright 60 years ago underpin the science of rate-making. But within these principles is ample room to deliver the price signals to incent desired behavior.
We need to stop thinking of all demand as firm, or “must-give” (the way we used to think about wind and solar as being “must-take” on the generation side before we got smart about how to really extract their benefits). Instead of demand being fixed and system operators balancing it with a portfolio of generators, we could (and should) be balancing both sides of this equation. There may be times in the future when total generation is fixed and system operators balance it with responsive demand.
Dynamic Pricing Will Be Critical as We Increase Wind and Solar Penetrations
We know from many integration studies that net load duration curves typically become more “peaky” (fewer hours of peak loads) as wind and solar penetrations increase. Generation resources are less attractive investments if these peaking resources are run for fewer hours; on the other hand, responsive demand becomes more attractive if it is not called upon too frequently. Reducing total system costs by encouraging responsive demand ought to be of great interest to consumer advocates and policymakers. Pricing, and its direct effects on the attractiveness of responsive demand, will become especially important as utilities move toward 100% clean energy.
There are utilities that are getting this right. Arizona Public Service has a long history of TOU rates with about two-thirds of their customers on them. ERCOT (Electric Reliability Council of Texas) skated through a record high peak demand in the summer of 2019 with a 9 percent reserve margin using some 3GW of responsive demand. Their four critical peak (4CP) transmission charges (this program allocates transmission charges for the following year on the basis of demand during the ERCOT coincident peak 15-minute intervals for the four summer months of June, July, August, and September of the previous year) were a key driver to realizing this price-responsive demand.
One thing is certain. As our grid transforms, it is essential that we take a systems perspective. There’s a lot to be said about comprehensive integrated planning of generation, transmission, and distribution resources, because resources in one of these buckets may obviate the need for more expensive resources in another bucket. Electricity pricing is an important mechanism to directly influence the demand that might otherwise require investment in new resources.
As this goes to press, ERCOT is in the middle of an unprecedented energy crisis, with the loss of tens of GW of generating resources due to extreme cold weather. Dynamic pricing is sure to come under fire as customers on real-time prices receive bills that reflect the extremely high energy market prices. It is incumbent upon us to NOT throw the baby away with the bathwater, but rather to learn from these events to design pricing structures that provide price signals that enable economically beneficial, grid-friendly behavior while simultaneously protecting customers from rare, massive failures of our system.
Associate Director, ESIG