(Today’s post is co-authored with Judson Boomhower, who recently received his Ph.D. at Berkeley where he was a graduate student researcher at the Energy Institute and is now a post-doc at Stanford)
Along with everyone else in Berkeley, we’ve enjoyed watching the home-team Golden State Warriors pull out comeback after miraculous comeback on their way to the NBA Finals. Has anyone else watched Steph Curry and Klay Thompson catch fire at just the right time and thought, “this team could really teach us something about energy efficiency policy?”
Crunch time in electricity markets are those few highest demand hours each year when generation is operating at full capacity. During these ultra-peak hours there is little ability to further increase supply so demand reductions are extremely valuable.
This feature of electricity markets is well known, yet most analyses of energy-efficiency policies completely ignore timing. For example, when the Department of Energy considers new energy-efficiency standards, they focus on total energy savings without regard to when these savings occur. With a few notable exceptions, mostly from here in California, there is surprisingly little attention both by policymakers and in the academic literature to how the value of energy-efficiency varies over time.
We take on this issue in a new Energy Institute working paper, available here. Our evidence comes from Southern California Edison’s residential air conditioner program. We use anonymized hourly smart-meter data from 9,700 rebate recipients to estimate how electricity savings vary across months-of-the-year and hours-of-the-day. As the figure below shows, electricity savings tend to occur between June and September, and between about 3pm and 9pm.
As a side note to duck chart aficionados, this savings profile differs somewhat from engineering models, which predict more savings earlier in the afternoon and in non-summer months. As more solar generation comes online, there is growing concern about meeting the steep evening ramp. Our estimates suggest that air conditioning investments deliver more savings than expected during these evening hours, and thus could become more valuable as renewables penetration increases.
These savings are highly correlated with the value of electricity. The figure below shows the value of electricity by hour-of-day in California for February and August, in dollars per megawatt-hour. We include wholesale electricity prices and the “resource adequacy” payments that generators receive to make sure they will be available when demand is high. The different data series in each panel show different methods for allocating resource adequacy contract prices to high load hours. For example, with “Top Hour” we assign the entire capacity value to the highest load hour-of-day in each month.
Wholesale Electricity Prices and Capacity Values
Regardless of exactly how we allocate resource adequacy payments, these figures make clear that summer afternoons are crunch time in California electricity markets. Unlike natural gas, electricity cannot be cost-effectively stored even for short periods so during these ultra-peak periods there is nothing preventing wholesale prices and capacity values from rising sky high.
And this is exactly when air conditioning investments yield their largest electricity savings. Efficient air conditioners don’t save electricity in the middle of the night or during the winter, but electricity is less valuable at these times anyway. Overall, we estimate that accounting for timing increases the value of air conditioner investments by 50% relative to a naive calculation that ignores timing.
How does this compare to other energy-efficiency investments? So glad you asked. We next brought in engineering-based savings profiles from the E3 calculator for a whole variety of energy-efficiency investments and calculated the timing premium for California and for several other major U.S. markets. The table below shows the results.
Timing Premiums for Energy-Efficiency Investments
Overall, there is a remarkably wide range of value across investments. Residential air conditioning has a 35%+ average premium across markets. The premium is similar whether we use our econometric estimates (first row), or the engineering estimates (second row), reflecting the fact that, despite some interesting differences, both sets of estimates indicate large savings during high-value summer peak hours.
Other investments also gain value when timing is considered. Non-residential heating and cooling investments enjoy a 20-30% timing premium, reflecting the relatively high value of electricity during the day when these investments yield savings. This is particularly true in CAISO and ERCOT, but also true in NYISO.
Refrigerators and freezer investments have the lowest timing premium. This makes sense because savings from these investments are only weakly correlated with system load. Lighting also does surprisingly poorly, reflecting that LEDs save electricity mostly during the winter and at night, when electricity tends to be less valuable.
We hope our paper will help move the energy efficiency discussion away from total savings and toward total value. To do this will require more rigorous ex post analyses of energy savings based on real market data. It will also require integrating these savings estimates with prices from wholesale and capacity markets, rebalancing the energy efficiency portfolio toward investments that save energy in more valuable hours.
Of course, these premiums are not everything. In evaluating energy-efficiency policies it is still important to evaluate all the costs and benefits. The numbers above don’t say anything about how much these different types of programs cost, or about how large ex post savings are relative to ex ante estimates, or about how many participants are inframarginal (i.e., “free-riders” in the energy efficiency literature). We’ve discussed these issues in previous blog posts here, here, and here. But our paper makes a strong case that, when calculating benefits, it is important to account for timing.
More generally, our paper highlights the power of smart-meter data. The econometric analysis we performed for residential air conditioning would have been impossible just a few years ago, but today more than 40% of U.S. residential electricity customers have smart meters, up from less than 2% in 2007. We are just scratching the surface of what is now possible using this flood of new data and its potential to facilitate smarter, more evidence-based energy-efficiency policies that are better integrated with market priorities.