In this divided age, few topics beyond motherhood, apple pie, and the iPhone 6 enjoy widespread public approval. So it is notable that, in a recent Gallup Poll, two out of three Americans support an increased reliance on solar and wind energy sources.
While (almost) all of us seem to agree that more is better when it comes to renewable energy, things get more complicated when it comes to determining what form that more should take. In other words, how do we get the biggest bang for our green energy buck?
In last week’s blog post, Severin argued convincingly that the answer lies in the creation of policy and market incentives that accurately reflect the real benefits and costs of different renewable technology options. A great idea! But messy and controversial to implement. To design these incentives, we need to measure and monetize the various costs and benefits that alternative energy technologies incur and afford.
Some co-authors, Duncan Callaway and Gavin McCormick (who was featured in an earlier post), and I have been trying to tackle one corner of this larger valuation exercise. In some ongoing research which will be released soon as an Energy Institute working paper, we estimate the greenhouse gas emissions impacts associated with incremental increases in renewable energy generation in different parts of the country.
The basic idea is as follows: when a wind turbine or solar PV system is connected to the electricity grid, the clean energy produced will displace electricity generation at other sources. We estimate the associated emissions impacts which largely depend on the emissions intensity of the marginal production that gets crowded out.
At this point, you might be wondering why we should be so concerned with measuring the emissions damages not done. If our objective is to design policy incentives to accurately reflect emissions costs, why not penalize emissions damages directly with an emissions price?
“Tax carbon” is a hallowed refrain on this blog (and on a vanity license plate of an economist we know and love). But when it comes to designing policies to encourage renewable energy, production-based subsidies and credits (such as the production tax credit and renewable portfolio standards) are a politically preferred policy instrument in the U.S. This is true now, and as states look to leverage existing renewable energy policies to comply with the proposed Clean Power Plan, this could hold true for the forseeable future. So long as we are in the business of subsidizing renewables for avoided emissions damages, it’s worth thinking about how to design these second-best incentives.
Measuring damages avoided
To estimate the emissions impacts of marginal changes in electricity generated by existing sources, we use hourly data from six major independent system operators (ISOs) in the United States over the years 2010-2012. We then match these estimates with simulated renewable energy production across thousands of wind and solar sites to estimate the average quantity of emissions displaced per MWh of renewable energy generated across different regions and technologies. We also consider the emissions impacts of some common energy efficiency improvements.
The figure below summarizes our estimates of avoided emissions on a per MWh basis over the 2010-2012 period. The colors denote the different technologies we consider. Technology-specific estimates are grouped by region. The bars of each box plot denote the range of/variation in our estimates due to the day-to-day variability in power system operations.
Pounds of Carbon Dioxide displaced per MWh of renewable energy generated (or energy saved)
The graph shows lots of variation across regions in the average quantity of emissions displaced per MWh generated or saved. This is not surprising given the large differences in the generating portfolios across regions. Displacing a MWh of conventional electricity production had a relatively small impact on emissions in California where the generating mix is not very carbon intensive. The largest emissions reductions are found in the Midwest (MISO) and Mid-Atlantic (PJM). In these regions, the generating units that would be crowded out when renewables kick in are often coal-fired.
There is much less variation in avoided emissions across different resources – for example solar PV versus wind – within a region. Intuitively, this is because marginal emissions rates are fairly constant within regions across hours and across seasons. One exception is New York (NYISO), where the marginal emissions rates are significantly lower on average during high-demand hours. Solar PV resources and commercial lighting retrofits, which generate electricity/savings disproportionately during daylight hours, displace fewer emissions per MWh than wind energy or residential lighting improvements.
What does this mean for subsidizing green?
If we want to design production-based credits or subsidies to accurately reflect emissions damages avoided, these results suggest that subsides should vary significantly across regions. Variation in avoided damages across technologies within a region appears less important.
To put these estimates into some kind of perspective, we assign a dollar value to each ton of CO2 displaced, $38/ton, and compare these monetized avoided damage benefits to the average wholesale electricity market value of the renewable electricity generated. The graph below summarizes our estimates for solar and wind energy for two extreme cases: California (relatively less carbon intensive on the margin) and the Mid-Atlantic (relatively more carbon intensive generation).
Marginal value per MWh of Solar and Wind Energy Generated
The blue bars show the average wholesale market value of the electricity produced by wind and solar resources, respectively, in these two regions over this period. These values reflect the fuel and operating costs avoided at marginal sources. Electricity generated by solar PV is somewhat more valuable because solar resources are disproportionately available during high demand hours when marginal operating costs are higher.
Our estimates of avoided emissions damages, measured in terms of dollars per MWh, are shown in green. In California, these avoided emissions benefits are approximately a third as large as the wholesale market value. In PJM, monetized emissions benefits and the wholesale market value are of similar magnitude.
Smart subsidies for renewable energy
Our punch line is that the marginal value of emissions displaced per MWh of renewable energy generated has been economically significant in recent years. And these values vary significantly across regions with different generation portfolios. Of course, the quantity of emissions damages truly avoided will also depend on what other policies and programs are in play. For example, if a region imposes a binding emissions cap, an incremental increase in renewable energy will not reduce overall emissions in any meaningful sense.
These estimates of avoided emissions damages capture only one dimension of the potential benefits generated by incremental increases in renewable electricity generation. But it’s an important dimension, particularly when it comes to policies that are designed to reduce the carbon intensity of the electricity sector. From an economic perspective, these policies would ideally impose a tax on emissions calibrated to the damage caused. If instead these policies take the form of renewable energy credits, these incentives should reflect the level of – and variation in- the damages avoided.
 Note that if a region has imposed a binding cap on emissions, increasing renewable electricity generation may affect the way the emissions target is met, but not the level of aggregate emissions. Emissions in California were not capped during our study period.