Winners and Losers from Flattening Tiered Electricity Prices

The California Public Utilities Commission is moving closer to major changes in the steeply increasing-block residential electricity rates that the state has had since the 2000-01 California electricity crisis.  This Friday the Commissioners may decide to significantly flatten the tiered rate structure.  In a blog post last fall, I discussed the inefficiency of charging tiered prices that don’t reflect cost and the unfairness of charging different customers different prices for the same good – a kilowatt-hour (kWh) of electricity.

In that blog, I also addressed the three standard arguments that defenders of such steeply tiered pricing commonly put forward.  The first is that increasing-block pricing yields conservation.  While in theory this could happen, the best empirical work on this subject, by (my former student) Professor Koichiro Ito shows that it is likely to have about zero effect on overall consumption.  It does encourage high-consumers to consume less, but it also encourages lower-using households to consume more.  Professor Ito shows that the net effect is no reduction in overall consumption.

The second argument is that supplying electricity to high-use households is more expensive per kWh on average, because they consume more at peak times.  My own research has shown the difference is so small that it would justify less than a one-cent differential in price between high-use and low-use customers.

The third argument carries the most weight, that higher-use customers are on average higher-income customers.  That’s true, as I showed in research published in 2012, using household consumption data from 2006.  However, like most states, California has a separate tariff for the lowest-income customers: households up to 200% of poverty-level income are eligible for the CARE program and pay much lower rates.  With the CARE program now covering about 30% of all residential customers, is tiered pricing in the standard residential rate an effective way to help lower-income households?

My 2012 paper just showed the average bill change for households in each income bracket, not the distribution of changes within each bracket.  There is another issue of equity if a program designed to transfer wealth from high-income to low-income households actually does a poor job of targeting either group, harming many low-income and/or benefitting many high-income customers.  This week I went back to the usage data from 2006 to see how great of a concern that should be.

Using PG&E data, I applied my earlier work on usage and household income to current electricity rates and the flatter tariff that a CPUC administrative law judge has proposed.  I estimated the range of impacts the proposed change would have on households across the income spectrum.

PGETariffChange

The figure above shows Pacific Gas & Electric’s current residential rate and an alternative rate that would raise the same revenue, but would have only two tiers with a 20% increase between them, as the ALJ has proposed.[1]  The first thing to note is that the new rate would be higher for consumption out to what is currently the third tier, the point where the two lines cross at 130% of baseline quantity.  In order to be a “structural” winner with the flatter rate – that is, paying less without changing consumption at all — the household would have to be consuming out beyond the crossing point in order to offset the higher marginal prices for the lower kWhs.

In this case, the breakeven point is at 216% of baseline quantity.  The median household consumes about 130% of baseline quantity, so that means most households would pay more.  By my calculation about 21% of households would save, while about 79% would see a bill increase if no one changed consumption.   This reflects the fact that since the electricity crisis the great majority of price increases have been placed on the highest-use customers, resulting in the steep tiers.

Using census data and applying a statistical matching method I developed in the 2012 research, I estimated into which of 5 income bracket each household falls.   I focused on the customers who are not on CARE, because CARE households are on a separate tariff.   The 5 income brackets are based on census categories that are roughly equal parts of the entire population.  As the table shows, however, in this analysis the bottom two brackets are smaller due to the substantial participation in CARE.

Income Bracket 1 2 3 4 5
Income ($2015) Under $27,400 $27,400-$54,800 $54,800-$82,200 $82,200-$137,000 Over $137,000
Share of non-CARE customers 2% 16% 23% 31% 28%
Average change in Monthly Bill with 2-tier tariff $5.84 $4.59 $2.40 $0.70 -$5.78
Percent Structural Winners 5% 12% 18% 22% 32%

Next, I calculated how much the average monthly bill of each household would change if the rate were changed to the two-tiered structure in the figure above (and the household did not change its consumption).  The third row of the table above shows the average bill change for households in each income bracket.  Not surprisingly, because lower income households consume less on average, they are more likely to see their bills go up with the change.  But even in the highest income bracket more than two-thirds of customers would see bill increases.

What was particularly surprising to me is the figure below, which shows the distribution of the change in bills for each of the income brackets.  The impacts across brackets are more similar than I expected.     In every income bracket two-thirds or more of the customers see their bills rise between $0 and $20 per month, even in the highest-income bracket.  Are these high-income households that don’t use much electricity super-conservers?  Maybe, but I bet many of them are households with only one or two people, who work and travel a lot, and don’t spend much time at home.

PGETariffWinnerAndLosers

About 4% of households are the biggest winners with bills dropping by at least $50 per month under the proposed tariff.  Are these “energy hogs”? Maybe, but I bet some of them are big families and people who are home all day, because they are retired or have small children.   Among these biggest winners, I estimate that slightly less than half are in the highest-income bracket.

Undoing the steeply tiered rates that were created during California’s electricity crisis will on average cause lower-income households to pay more.  If there were no other consequences of the steep tiering, I could see keeping it on that basis.  But there are other impacts on both efficiency and fairness, not the least of which is the monthly harm to higher-consuming, middle- and lower-income households that is caused by a rate structure that has no basis in costs.

Some opponents of the two-tiered rate proposal have presented it as a simple shift of payments from poor to rich.  This analysis shows that the story is not that simple.  Both winners and losers are present at every income level.  The two-tier proposal makes bills more cost-based and more proportional to usage, as they were before 2000.  And as they are in nearly all other states, and in the parts of California served by municipal utilities.

I’m still tweeting energy news articles and new research papers @BorensteinS 

[1] All of these calculations assume no consumption response to the tariff change.  As I show in my 2012 paper, accounting for the small elasticity that has been estimated for response to a change in increasing-block pricing makes very little difference to these calculations.

Posted in Uncategorized | Tagged | 14 Comments

How Should Distributed Generation be Distributed?

Growth in the residential solar market continues apace. In the United States, residential solar PV installations last quarter were up 11 percent over the previous quarter:

q1-2015-install

Source: http://www.greentechmedia.com/research/ussmi

The figure  illustrates this impressive growth rate (in dark blue). However, this is growth on a very small base. By my crude calculations, less than half a percent of American households currently have solar panels on their roof.[1]

In those states where residential solar is starting to take hold, there are mounting concerns that rate structures currently in place to support residential PV will result in adopters bearing less than their fair share of system costs. If increasing levels of distributed solar generation puts additional pressure on grid equipment and aging infrastructure, these concerns loom even larger.

A new EI working paper takes a close look at how increasing levels of distributed solar generation can impact power system costs. For me, this paper raises a timely question: should we be paying more attention to where distributed generation gets distributed?

Bill savings for the adopters

Before diving into the details, let’s first review the basic issues.

If you have invested in putting solar panels on your roof, chances are the solar electricity you generate is valued at retail rates one way or another. This is thanks to net metering policies adopted in most states. If you consume the electricity you generate, you avoid purchasing electricity from your utility. If you do not use all the electricity that your solar panel is generating (it is estimated that almost half of electricity generated by net metering customers in California is exported), you can export the extra power to the grid and count it against consumption within the same billing period.

As we’ve discussed before on this blog,  the marginal retail price can significantly exceed the direct energy costs of producing a kilowatt-hour centrally. On the one hand, many of the costs that are reflected in retail prices (e.g. metering, billing, and infrastructure costs) are not avoided when you put solar panels on your roof. On the other hand, solar PV generates benefits that are not fully reflected in market prices.

So what is the right price for distributed solar generation?  Past blog posts have touched on some elements of this value-of-solar calculation that fall squarely in the purview of economists. But there are other important elements that push outside the boundaries of economics.  This week, we venture into the engineering-meets-economics world of distribution system costs.

I am no an engineer, but I am fortunately married to one, who is a co-author of the new EI working paper. Much to the chagrin of my kids (who’d rather be talking Frozen or fire trucks), I have been steering the family dinner table conversation towards this paper which looks at how distributed solar affects the electricity distribution system. The findings should be of interest to energy economists and engineers alike (but not so much three and five year olds it turns out).

The distribution system meets distributed generation

A quick summary of what I’ve learned at my dinner table.

If you install solar panels on your roof, this will impact how power flows through the distribution system that delivers power from high voltage transmission networks to the people in your neighborhood. The cartoon below helps to fix ideas.

cartoon

Source: http://www.slideshare.net/bhagwanprasad50/transformer-basic

Some of these impacts can reduce costs. For example, less electricity flowing into your neighborhood during peak times can reduce pressure on aging infrastructure (e.g. distribution lines, service transformers) and defer the need to invest in distribution system upgrades. That’s good. But increased PV penetration can also increase the need for investment in hardware such as voltage regulation because distribution systems are not designed to handle power flowing from customers back to the substation.  Not good.

The cartoon above shows a single “feeder” (a collection of distribution lines that carry power from the high voltage transmission system to customers). Using detailed data on all 3,000 feeders operated by the largest utility in California, PG&E, Duncan and coauthors simulate how increased solar PV penetration on each feeder would impact the need for system capacity upgrades, expenditures on voltage management, etc.

On average, they find that the levelized value of deferred investment in distribution system upgrades (avoided costs) is small: around half a cent per kWh. This is in line with rough estimates found in other reports that use highly aggregated data.

But the advantage of disaggregated data is that they can look beyond the average. It turns out that this economically insignificant average value obscures tremendous variation in feeder-specific capacity values. Capacity values are zero across a large majority of feeders where no capacity upgrades are anticipated over the next ten years. But for approximately ten percent of feeders, the picture looks quite different.

The figure below focuses on the 298 feeders where capacity upgrades are anticipated  in the next ten years under a business-as-usual scenario. This represents about 20 percent of the total capacity, or approximately 1 million customers.

distcapval_percentiles_alpha_neg50

The figure shows that estimated capacity values exceed $60/kW-year (or $33/MWh using their discounting and electricity production assumptions) for approximately 30 feeders (this assumes a solar PV penetration rate of 7.5 percent).  This is almost on par with the energy value.  The median capacity value in this select group exceeds $20/kW-year ($11 per MWh).

Although there has been much hand wringing over the potential for voltage regulation problems,  the authors find that these problems are actually relatively small.  Using PG&E’s current budget for repairing voltage regulating equipment, they estimated that even in extremely aggressive scenarios for PV deployment, the total costs to ratepayers would be less than half a million dollars a year.

Distribution matters

On average, this study finds that the average (distribution system related) net benefits of distributed solar PV are not very significant.  However, looking beyond the average, the value of deferred investments in distribution system infrastructure associated with a given level of distributed generation depends significantly on how these resources are distributed on the system. In other words, the net costs of future distributed generation could be significantly reduced if these resources are targeted to areas where they can generate the largest benefits.

There is precedent for targeting energy efficiency to defer investments in transmission and distribution system upgrades… why not solar PV?  If the next generation of distributed solar incentive programs and resource planning protocols reflect  the impacts that these resources could have on different parts of the distribution system, the next generation of distributed resources can be more efficiently distributed.

.

[1] To estimate the number of systems, I divide GTM research estimates of installed residential PV capacity in 2014 by the state-specific average residential system size (as reported in Tracking the Sun, 2014). I then divide this by the US Census estimate of the number of US households in 2014. Thanks to Naim Dargouth and Snuller Price for the solar PV numbers!

Posted in Uncategorized | Tagged | 9 Comments

Is the U.S. Investing Enough in Electricity Grid Reliability?

We had a 2-hour power outage at our house last week, together with 45,000 other customers in the East Bay. The lights flickered off just after 8PM and didn’t come back on until after 10PM. Nothing like going without something that you take for granted to make you realize just how valuable it is.

The East Bay outage was reportedly caused by a squirrel

The East Bay outage was reportedly caused by a squirrel

My son and I had fun gathering our candles and figuring out that our hand-crank radio played Mariachi music, but that only lasted for about half an hour. As the minutes ticked by without WiFi, the economist in me started thinking about just how much I would be willing to pay to get the electricity back. I had a meeting the next day to prepare for, and it was my turn to take a pass through the slide deck. I couldn’t even get good enough cell service to download the presentation to my phone, perhaps because local cell towers were also affected by the outage.

The beauty of the free market is that it allocates resources to the sectors of the economy where they are most valued. (Yes, I’m beating the economics drum, but this is econ 101 – we ALL agree on this one, even the two-handed economists.) If enough customers value a good highly and it’s inexpensive to produce, an innovative entrepreneur can make money by figuring out how to sell that good to consumers.

So, most goods and services that people value more highly than it costs to provide them exist, and things that aren’t valued don’t exist. The market supplies frozen pizzas and smart phones, but not condos in space, because they’re super expensive and not, currently, in high demand.

frozen pizzaThings are different with electricity. Given that the majority of the world’s citizens get electricity from some kind of regulated or state-owned monopoly, we’ve basically given up on using the market to figure out how much people value electricity reliability. So, regulators and the regulated companies are left guessing how much customers are willing to endure higher prices to cover a more robust system.

My personal hypothesis is that we have gotten this wrong in the U.S. I suspect we’re underproviding reliability and spending too little on making the grid more secure.

Even in areas of the U.S. that have restructured (or, what we used to call “deregulated”) their electricity industries, the distribution system remains regulated. Most outages are caused by failures at the distribution system level. Further, in most restructured wholesale markets, generation reliability is impacted by regulatory decisions on things like reserve margins.

Yes, there are many parts of the developing world where (only!) 2 hours without power is not a good day but an extraordinary day. But, there’s another side to the spectrum. Germany and other parts of Europe have much more reliable electricity systems than the U.S.

I first heard this anecdotally from a friend who grew up in Germany and said he could remember one outage throughout his entire childhood. The table below shows that his anecdote is true generally.

GT

Source: Galvin Electricity Initiative report, Table 1.

Being on top of this list isn’t good. Larger values of SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index) indicate less reliable power. Roughly, SAIDI reflects the average number of minutes per year that customers are without electricity and SAIFI reflects the average number of outages customers experience per year. Americans endure 10 times as many minutes of outages compared to Germans.

stormRecent work from Lawrence Berkeley National Labs (LBNL) suggests that, if anything, reliability has been getting worse in the U.S. over time.

If the regulators in both Germany and the U.S. were doing a good job approximating market outcomes, these vast differences in the amount of reliability would suggest that either the German utilities can provide reliability at a much lower cost or that German customers have much higher demands for reliability. My guess is that neither of these things is true. The electricity systems are very similar, so I don’t think Germans are using a radically different technology to drive their costs down. Maybe Americans live in areas that are more exposed to storms, but 10 times more exposed seems implausible.

Why do I think the U.S. is spending too little on reliability and not that Germany is spending too much? At a very macro level, estimates of the annual economic losses from electricity outages are very high, ranging from $20 billion to $150 billion annually. This seems like a lot of lost productivity and I would hope there are relatively inexpensive investments we can make in the grid to avoid these losses. Also, as I have blogged about earlier, to the extent we can back out how much regulators think customers value reliability, the estimates seem low.

Is Elon Musk going to solve this for us? In the post-Powerwall world, people who value reliability highly can vote with their pocketbooks and spend $3,500 to get a battery backup that will deliver 10 kWh each time there’s an outage. From what I’ve read, they’ll spend another $3,500 on installation and the ancillary equipment, like a smart inverter. Someone I spoke to recently who didn’t like outages was looking forward to installing a Powerwall, although he is a senior employee of a large tech company and probably thinks about $7,000 investments the way most of us think about spending $50.

Let’s run some quick numbers on the Powerwall. Let’s say it costs $7,000 for a 10kWh battery, which I assume you use for four 2-hour outages per year. According to the table above, the U.S. average is 240 minutes of outages across 1.5 events, but let’s think about people who are experiencing many more outages than average. The Powerwall is supposed to last for 15 years, so at a 5% real interest rate, the rental cost of capital is about $675 per year to get 10 kWh 4 times per year. This amounts to almost $17 per kWh. Given that average U.S. customer pays 12 cents per kWh, that’s a SUPER expensive backup.

powerwallFinally, it’s not clear to me that having a Powerwall at your house will deliver the kind of reliability we really want. In our highly networked world, it’s possible the outage will disable other services. If the battery backups on the local cell towers run out, it could be hard to make calls.

In short, while the Powerwall might satisfy the demand for reliability for a handful of very wealthy or very outage averse U.S. customers, I suspect it will leave a lot of unmet demand. Plus, if we’re just talking about backup electricity, it’s not even clear that the Powerwall fills a niche that a diesel generator didn’t already fill, though it does look sleek.

We have a lot more to learn about reliability. This post makes some assertions that I would love to see substantiated with hard evidence! But, as the LBNL folks point out, we currently don’t even collect very good data.

The good news is that new technologies seem poised to deliver better information on reliability and to give us new ways to enhance the electric grid. But, whether utility companies and regulators have the right incentives to use this information to ensure that systems are delivering the correct amount of reliability is an open question.

Posted in Uncategorized | Tagged | 37 Comments

A Deeper Look into the Fragmented Residential Solar Market

(Today’s post is co-authored with Alex Chun, who just received his MBA at Haas and is an alumnus of our Cleantech to Market class.  Alex is the Business Intelligence Manager at Sungevity.)

Who sells residential solar photovoltaic systems (PV) in California? How many companies operate in this market?  What fraction of the market is controlled by the largest companies? How is this changing over time? In today’s post we look at data from the California Solar Initiative (CSI) to better understand the structure of this market.

Since 2007, 1.9GW of residential solar PV capacity have been installed under the California Solar Initiative. One of the truly laudable features of the CSI program is that data from the program has always been made publicly available. This has given market participants an unprecedented view into the market and spurred innovative research like the paper Severin Borenstein blogged about two weeks ago. For today’s post, we used the CSI data to look at the spectrum of companies working in this market.

Market Share by Company, Top 30 Companies 2013top30

We first looked at market share by company in 2013. The first thing that becomes apparent when looking closer at the CSI data is the high degree of fragmentation in this market. The largest firm, SolarCity, sold almost 18% of all installations in 2013, but after that market share falls precipitously. The top five companies together account for only about 40% of the market and beyond Solar City and Verengo at 9%, no other company comes close to having a double-digit market share.

Also notable is the long right tail. This is apparent among the top-30 sellers and can also be seen in the figure below which shows market share for all companies including those outside the top 30. The rainbow of tiny vertical slices shows that beyond the top five, this is a market made up of small companies, each with only a tiny market share.

Market Share by Company, All Companies 2013all

Before we go any deeper, an important caveat is that the CSI data include only those installations for which the household received a CSI subsidy. If you installed solar PV and received the Federal tax credit, but not the state subsidy, then you are not in the CSI data. This was not a large category a couple of years ago because most solar PV customers in PG&E, SDG&E, and SCE opted to participate, but the subsidy amounts have decreased over time and in 2013 the CSI covered only 22% of all new California residential solar installations. Data from Greentech Media suggest that the CSI data are approximately representative of the broader market, for example with similar market share for the top-five companies. Moreover, in 2012 the CSI covered 48% of all new California installations, and results (here) are very similar. Nevertheless, you have to be very careful interpreting these data, particularly because the fraction of the market covered by CSI has decreased so much over time.

The Long Right Tail

We next constructed a figure to look at installation volume by company. In 2013, there were a total of 840 companies who installed systems that received CSI rebates and the median volume installed was 21KW per company.  A typical system is about 4KW, so the median company installed only about 5 systems during the entire year. Even the third quartile company installed only 79KW.

Distribution of Installer 2013 KW Volumevolume

Solar City, in contrast, installed 28,000KW, approximately 1000 times the median volume. Solar City, Verengo Solar, and REC Solar look like outliers when compared with the rest of the market. The line at the bottom represents the median, 25th, and 75th percentiles. With this scale, three-quarters of the companies in the market are nearly imperceptible at the bottom of the figure, underscoring the fact that while there were 840 companies competing in the market, most of them were operating at a tiny fraction of the scale of the biggest players.

Market Consolidation Since 2010

While the market remains highly fragmented with large numbers of small installers, the CSI data show that over the past three years there has been a considerable amount of consolidation.

Installer Count Over Timeovertime

Between 2007 and 2010, the number of companies in the market increased by about 200 per year. It then peaked at 1,050 in 2010. Since 2010, however, the number of companies has decreased every year with an overall ~25% drop from 2010-2013.  While it is possible that this pattern is driven by the decreasing coverage of the CSI data, the evidence is suggestive of a consolidating market.

We also looked at the breakdown of new entrants versus surviving companies. The green line below shows the fraction of companies each year who were not in the market during the previous year. From 2008-2010, nearly 50% of the companies in the market were not in the market during the previous year. This is a remarkably high level of entry and reflects that this is a rapidly growing market. Since 2011, this “churn” has decreased somewhat with only about 30% new entrants each year.

New Entrants vs Previous Year Survivorssurvivor

The figure also shows the number of new and surviving companies in the market each year. Starting in 2010, the number of survivors (companies who were in the market the previous year) started to flatten out at around 600. Meanwhile, the number of new companies entering the market decreased significantly in 2011 and appears to have further decreased in 2013.

Long-Term Market Structure

It is too soon to say, but we may be headed toward a more consolidated solar PV market with fewer companies controlling larger market shares. In his Business Strategy class, Haas Professor Ned Augenblick discusses the five factors that lead to a sustainable strategic advantage. One of us took this class recently and can still remember all five:

  • Network Effects
  • Switching Costs
  • Restricted Access to Resources
  • Economies of Scale
  • Economies of Scope

Companies in the residential solar market do not benefit from any of the first three factors. Consumers do not receive an additional benefit from going solar from the same company as other people in their network. Sales in the residential solar market are a one-time sale, thus preventing any switching costs, and there is no restricted resource that would give companies in this market a sustained strategic advantage. To the contrary, the large number of smaller companies in this sector suggests that barriers to entry are minimal.

In the absence of these sustainable strategic advantages, the solar market does not have the winner-take-all dynamics that will drive it naturally to an oligopoly market in the same way as, for example, the cell phone OS market. Thus, consolidation will be driven solely by economies of scale and economies of scope. Where potentially there could be economies of scale is in the “soft” costs like marketing, customer acquisition, permitting, and inspections. Companies are hoping that the larger they become, the more they will be able to spread these costs across customers. Moreover, economies of scope could become important as companies take advantage of their growing customer bases to sell related products and services.

For market observers, understanding these underlying economics and market trends is important because it provides an idea of where the market is going and what the long-term market structure will be. For companies operating in the space, however, it’s even more critical.  Understanding the scale necessary to capitalize on economies of scale and scope and hitting this volume can be the difference between surviving and exiting the market. The CSI data doesn’t have all the answers, but it does suggest that the market has been consolidating over the last couple of years. If economies of scale and scope end up being important, then we would expect to continue to see smaller companies exit the market and the remaining companies increase their share of the pie.

Posted in Uncategorized | Tagged , | 3 Comments

Exiting Coal?

On March 11, 2011 I was sitting in a coffee shop in Berlin, dressed appropriately in a black turtleneck and leather jacket, reading about the terrible Fukushima Daiichi Nuclear disaster. The next day I read that the German government was pushing for “Atomausstieg,” which is German for “let’s retire all nuclear generating capacity.” 80% of Germans surveyed were in favor of this move. The nine remaining German nukes are being phased out and the last one will shut its doors by 2022.

The Energiewende Law, which was proposed only months before the Fukushima disaster, was enthusiastically approved in 2011 and has led to rapid growth in the penetration of solar PV and wind power across Germany, as the advertising below indicates.

germanyenergy

While there is no way to establish causality here, no one can argue with the fact that the installed cost of PV has come down by 66% in a decade. And the creation of the German market could have had something to do with this. In 2012 Germany (1.1% of the world’s population) had 32% of installed solar capacity globally, according to government figures. And capacity continues to grow – 2014 installed capacity was 113% above that in 2010 suggesting a 21% growth rate p.a. This has come at a cost. While owners of PV installation have to pay for some of the cost of the solar panels privately, the average German household now pays about 260 Euro per year to subsidize renewables, which is nothing to sneeze at. But it’s also not the end of the world as some have suggested (about the equivalent of a Starbucks latte twice a week, which unlike the renewable subsidy, does not come with a green halo). The Energiewende enjoys less, but still strong, public support. So now the government is starting to contemplate what to do next to achieve its ambitious emissions reduction goal of 80% by 2050.

germany energy long

Sigmar Gabriel, who is Angela Merkel’s Energy minister, has started talking about something called “Kohleausstieg” (German for Coal Exit). When visitors from Germany to the Energy Institute lunch table mentioned this, I thought I misheard. But I did not. There is a slowly emerging vision of the German energy system, which will no longer have domestic baseload generation. Just say Nein to coal and nukes. This is fascinating. Let’s take a look at what estimated power supply looks like in May 2012 versus 2020:

german energy power demand

What we are seeing here is the huge variability in generation of renewables, which of course does not line up quite as beautifully with demand as has been pointed out elsewhere. This picture also shows nicely that by 2020 renewables are generating more power than is demanded (at least on the weekends). And if the installation trend continues, this will be true for most weekdays, too.

This means that we may not need the always-on baseload (coal and nuclear in most places). In one version of the world you use fossils that ramp up quickly to meet residual demand (e.g., gas from Russia). In a second version of the world you use clean hydro power from Northern Europe instead. In a third version, which is the one Elon Musk would like you to consider, you use a giant battery in your house, which stores renewable power at times when there is plenty of it to be had for cheap (requiring a pricing revolution).

I am a confessed hip-/techie. I like the last version of the future. But I have some questions.

  • Is Germany this bold since it can always buy cheap nuclear baseload from France if things go terribly wrong? What if you are a country like the US, where you do not have this type of backup at scale?
  • What about the political economy of a coal exit? Coal mining unions are very powerful and this would put a lot of people in poor areas out of jobs. And miners will not go into installing PV panels on people’s roofs, since the sunny rich areas are not usually where the coal mines are.
  • How much storage do we need to make this work? I can see a residential model, where Elon Musk sells me a battery or my car serves as storage. But what about BMW, Porsche, and Intel? Will we come full circle where firms will have their own fossil backup generation (which is the case for most manufacturers in China currently)?
  • What if the major players exit coal? That shift in demand, drives down price and leads to consumption elsewhere. In order to make this work you would have to exit coal and find a way to leave what you don’t consume in the ground.

While writing this blog post I was surprised by how similar California’s and Germany’s energy policies and challenges are. Both places are pushing hard for an almost fossil free future using a combination of market based policies and huge number of competing standards. Both places have political leadership proposing radical long range policy targets, which we do not necessarily know how to achieve. Both places are relatively wealthy. Both places have industries that have been at the forefront of technological innovation, especially in the STEM fields.

Germany, specifically, has been at the forefront of pushing new distributed generation technologies and shouldering much of the cost of the global energy transition. This is laudable. California is along for the ride and doing its part. It looks like we might be the ones leading the charge on designing cost effective storage. Thanks Elon. While I don’t think a coal free Germany is necessarily an unrealistic idea, I want us to keep our eye on the prize. What we should shoot for are drastic global reductions in CO2. Germany and California are small. If what comes out of our policies is a way to drive coal and natural gas up the merit order in places like China and India, this would be the real success.

Posted in Uncategorized | Tagged , , | 36 Comments

What Put California at the Top of Residential Solar?

California leads the nation in residential solar photovoltaic installations.  In fact, nearly half of all systems installed have been in the Golden State.

So why is California the leader?  Sure, California has plenty of sunshine, but there are many other states that can compete on that dimension, including Florida, the Sunshine State.  It’s not the federal tax benefits, which are available to all US residents.  It’s not California’s Renewables Portfolio Standard, which effectively excludes residential solar.  Some point to the California Solar Initiative that gave rebates for new systems from 2007 to 2013, and that is surely part of it.

But another factor is the “solar friendly” residential electricity prices.  Not only do California’s two largest utilities have some of the country’s highest average residential electricity prices, the rates are also tiered, meaning that they increase for additional kilowatt-hours as the household consumes more over the month.  As a result, large users face rates for much of their power that can be three times higher than rates in many other states, including the Sunshine State.

SolarPVIncentives-Tiers

Have the level and structure of retail rates been a major factor in California’s residential PV boom?  I’ve been wondering that for a while, so in the last few months I’ve been sizing up the various solar incentives for customers of Pacific Gas & Electric, the state’s largest utility, which has by far the most residential rooftop solar capacity in the country.  The result of this work is being released today in a new Energy Institute working paper, “The Private Net Benefits of Residential Solar PV: And Who Gets Them”.

Using data on PG&E households that installed solar from 2007 to 2013 (and for some data, into early 2014), I examine the collection of incentives that were available, whether the system was bought by the homeowner or owned by a solar company, known as third-party owners (TPOs).  TPOs can lease the panels to the homeowner or agree to sell the electricity the panels generate under a power purchase agreement that specifies the price per kilowatt-hour (kWh), usually for 20 years.   I then put all these incentives together with reported prices of the systems to calculate the net benefits.

The incentives include direct rebates and tax credits, as well as indirect incentives from the structure of retail tariffs and the credit for electricity grid injections from the panels under “net metering” policies, as I’ve discussed in an earlier blog.

To start with the easiest ones, the California Solar Initiative was offering $2.50 per watt rebates back at the beginning of this period – when the full systems cost around $10 per watt on average.  The CSI rebate stepped down over time, eventually hitting $0.20/watt in 2013 just before it disappeared.  In the first half of 2014, the average full system price was down to around $4.50/watt.

SolarPVIncentives-CSI

If you bought the system, you got the CSI rebate.  With a TPO, the company that owns the system got the rebate and — I hope — you got a lower price reflecting at least part of that savings. In either type of transaction, how much the price adjusted to pass through the savings to the homeowner, or how much the installer captured, is a point of strong dispute.  Different analyses have estimated 17%, 45% and 99% passthrough rates to homeowners.  Unfortunately, my study can’t unpack that even in the simple case of system purchases, let alone with much more complex lease or power purchase agreements.  I estimate the incentive the homeowner and seller jointly received, not how they divided it up.

At the same time as California had the CSI, the federal government was giving a 30% tax credit for solar, but only up to $2000 for the entire system if a homeowner bought it in 2007 or 2008.  TPOs got the full credit from the start.  Since 2009, homeowners have also had no cap on the tax credit.

If you think figuring out federal tax credits could get a bit tedious, imagine the thrill of analyzing the economics of accelerated depreciation.  I’ll spare you the details here (a phrase that may have been more welcome a couple paragraphs earlier), but the bottom line is that accelerated depreciation — which only TPOs can utilize — amounted to an additional 12%-15% incentive, about half the size of the 30% federal tax credit, and larger than the CSI since 2010.  The figure below shows my estimates of the size of these incentives, all per kW of installed capacity, from 2007-2013.

SolarPVIncentives-Estimates

That brings us to the incentive from residential rates.  During the period I studied, the 5 tiers of PG&E’s rate structure averaged $0.13, $0.15, $0.28, $0.37, and $0.40 per kilowatt-hour (kWh).  The solar PV on your rooftop crowds out the most expensive kWh first by reducing the total kWh for which you get billed.    Over these years, the systems installed were on average displacing kWhs that would have cost the customer an average of about 26 cents.  Importantly, that is much higher than the 19 cents per kWh they would have saved if PG&E charged a single flat rate for electricity (that raised the same revenue).  If PV adopters expected the tiered prices to stay at those levels (adjusted for inflation), I show that PG&E’s tiering of rates created nearly as much additional incentive to install solar as did the 30% federal tax credit.

The savings are so large in part because of net energy metering (NEM), which means the household only pays for the net consumption — that is, total consumption minus the electricity the panels produce — even if some of the panel production gets injected into the grid (which happens any time that the household consumption is lower than production).  An alternative approach, used in other parts of the world, is to pay the household a lower price for grid injections than the retail price the household pays for receiving electricity.  Surprisingly — at least to me — moving from NEM to that alternative approach, but keeping the same tiered rates, would reduce the incentive for solar by only about half as much as moving from tiered to a flat electricity rate.  The steep tiers create a much larger incentive than NEM, though the combination creates a still larger incentive.

Important note: those steep tiers created strong incentives only if they were expected to last.  Maybe they were, but they didn’t.  Already, in 2015, the lowest tier prices have risen and the highest have fallen so much that the highest tier price is now about twice the lowest rather than three times.  Proposals now before the California Public Utilities Commission would change the spread to just 20% or 66% depending on which proposal is adopted.  This will further lower the average price of electricity that the solar panels replace, and lower the incentive for large users to install PV.

Beyond the size of these incentives, I also wondered who was going solar, particularly how much the recipients of incentives tilt towards high-income households.  Using very granular census data, I estimated household incomes for each PG&E customer who installed solar.  Not surprisingly, they are heavily skewed to the wealthy with 35%-40% of systems going to households in the top 20% of earners.  But that has been changing since 2011, with the measure of inequality among adopters declining by nearly one-fifth from 2010 to 2014.  In the first few months of 2014, households in the highest of the five income brackets were still 82% more likely to adopt solar than households in the middle bracket, but that’s down from 116% in 2010.

Estimating incomes of solar adopters also give some insight into how the private benefits vary among those who do install PV systems.  As you would expect, the lower income adopters tend to consume less electricity and put in smaller systems, but they actually put in larger systems relative to their consumption.  That means they start lower down on the tiered rate structure and they crowd out a larger share of kWh, which are kWh that wouldn’t have cost that much anyway.  Systems on the roofs of the highest income bracket households crowded out electricity that would have cost them 27 cents per kWh on average, while the systems on middle income households displaced 25 cent power, and the households in the lowest bracket displaced 21 cent electricity on average.  Among those who installed solar in 2007-14, the wealthiest customers were likely to get the largest savings.

As I wrote a few weeks ago, we need a careful analysis of the societal costs and benefits of deploying renewable power at grid scale versus distributed generation.  At the same time, we also need a careful analysis of the incentives that have been created for generating energy from all sources.  Regardless of one’s views on solar, distributed generation, or renewables generally, understanding the size of the financial incentives from direct and indirect factors is critical to evaluating which programs are likely to have the greatest effect on adoption and which customers are likely to get the greatest benefits.

Posted in Uncategorized | Tagged , , | 9 Comments

Is Clean Coal Too Expensive?

Policies that subsidize the demonstration of large-scale technologies make economists queasy. Severin explored this topic in a recent blog.

In retrospect it’s easy to point to failures, including the United States Synthetic Liquids Fuels Program that died in the 1980s and Solyndra’s bankruptcy in 2011. But there are a few clear winners too. Take the government-supported technologies that enabled the US shale oil and gas boom.

Of course in retrospect, it’s easy to identify the failures and the successes. It’s much harder to do it in real time. Still, policymakers presented with many options and limited resources need to make decisions.

One important set of technologies that deserves a critical review right now is the use of coal to produce electricity but keep the carbon dioxide from entering the atmosphere and contributing to climate change.

The Tavan Tolgoi coal mine in Mongolia. Mongolia exports most of its coal to China.

The Tavan Tolgoi coal mine in Mongolia. Mongolia exports most of its coal to China. SOURCE: http://en.wikipedia.org/wiki/Mining_in_Mongolia

Many of the world’s fastest growing economies are relying on coal to lift their populations out of poverty. In 2013, 70 percent of global coal consumption occurred in rapidly growing Asian countries. Remaining coal reserves are enormous too. According to BP’s latest statistical survey, world coal reserves in 2013 were sufficient to meet 113 years of global production.

If clean coal technologies do not become cost effective, developing countries will continue burning coal in an uncontrolled way to meet societal needs.

In the US, clean coal technologies have received hundreds of millions of dollars in subsidies since the mid-2000s, but the federal government is starting to yank its support.

In February, the US Department of Energy pulled the plug on the high profile FutureGen 2.0 project in Illinois. The project’s blue chip sponsors, including major coal producers like Peabody Energy and BHP Billiton, as well as foreign utilities E.ON of Germany and China Huaneng Group of China, needed continued government subsidies to build this first-of-its-kind project. The project had already gone through more than $200 million in federal money, and the DOE decided that was enough. Now FutureGen 2.0 has joined the dozens of other cancelled carbon capture and storage (CCS) projects.

While news from the Prairie State (Illinois) is grim, there has been some progress in the Hoosier State (Indiana), Magnolia State (Mississippi), and the Land of Living Skies (Saskatchewan!). Three plants have been completed or are approaching completion:

  • Duke Energy’s 595 megawatt Edwardsport Integrated Gasification Combined Cycle (IGCC) plant in Indiana. The world’s first large scale IGCC plant. The carbon capture and storage component of the project was dropped part way through construction, although the plant could be upgraded with carbon capture and storage in the future.
    Online date: June 2013. Forecast cost: $1.985 billion. Actual cost: $3.55 billion. Cost per unit of capacity: $6,000 per kilowatt.
  • The Southern Company’s 582 megawatt Kemper plant in Mississippi. The world’s first large scale IGCC plant with CCS. The carbon dioxide will be injected underground in a nearby oil field. Online date: first half of 2016. Initial forecast cost: $2.4 billion. Revised forecast: $6.2 billion. Cost per unit of capacity: over $10,000 per kilowatt.
  • SaskPower’s 110 megawatt Boundary Dam Project in Saskatchewan. The world’s first post-combustion coal-fired CCS project. The plant takes the flue gas from a pre-existing coal power plant and strips out the carbon dioxide. The carbon dioxide will be injected in a nearby oil field. Online date: late 2014. Actual cost: C$1.467 billion. Cost per unit of capacity: over US$12,000 per kilowatt (at today’s exchange rate).

The three plants received either direct government subsidies, or have been authorized by the government to recover costs from their captive customers—a sort of off-the-government’s books subsidy.

To put the plants’ costs in perspective, the graph below compares the capital cost per kilowatt of these plants with the capital costs of other technologies as estimated by the US Energy Information Administration:

Data from US Energy Information Administration (http://www.eia.gov/forecasts/capitalcost/)

The capital cost does not tell the whole story of how power generation technologies compare. Plants also vary in terms of fuel cost, percentage of time they operate, operations and maintenance costs, expected life and pollution they generate. Capital costs are, however, one of the most important components of the comparison between technologies.

The graph shows that these three plants were more expensive than the estimates for similar plants of the same technology, and were much more expensive than many alternatives.

However, it is also important to note that substantial knowledge and experience have been produced as a result of those government investments. Valuing that knowledge and experience is difficult.

Now it is time to ask—should the government subsidize additional coal projects like these? Should these first-of-their-kind projects be the last-of-their-kind?

Does this guy deserve more subsidies? Maybe so. SOURCE: http://www.gutenberg.org/files/36141/36141-h/36141-h.htm

Does this guy deserve more subsidies? Maybe.
SOURCE: Punch, Vol. 105, August 19, 1893 at http://www.gutenberg.org/files/36141/36141-h/36141-h.htm

To make this decision, policymakers should be exploring a number of things: Why did the projects cost so much? What caused the budget over-runs? How can costs be reduced and output increased for future plants? Is there a plausible path to make the technology cost competitive? How can clean coal avoid the increasing cost trends experienced by nuclear energy, highlighted by Lucas in a prior blog?

Policymakers need to carefully consider subsidizing second, and even third, versions of each promising clean coal plant. That may be a hard case to make in the US given expectations of large natural gas supplies and low natural gas prices, but European and Asian countries may be able to justify further government investments in coal.

The opportunity is too big to ignore coal.

Posted in Uncategorized | Tagged , , , | 16 Comments

Subsidizing renewables for the damage not done

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.

solarSource: http://www.americasupportssolar.org/

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.

plot1

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[1]. 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).

 blog_figure

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.

[1] 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.

Posted in Uncategorized | Tagged , , , | 23 Comments

Is the Future of Electricity Generation Really Distributed?

Renewable energy technologies have made outstanding progress in the last decade.  The cost of solar panels has plummeted.  Wind turbines have become massively more efficient.  In many places some forms of renewable energy are cost competitive.  And yet…just as these exciting changes are taking place, the renewables movement seems to be shifting its focus to something that has little or no connection to the fundamental environmental goals: distributed generation, particularly at the residential level.  In practice, this means rooftop solar PV.

Instead of seeking the most affordable way to scale up renewables, the loudest voices (though possibly not most of the voices) in the renewables movement are talking about “personal power”, “home energy independence”, “empowering the consumer”, and rejecting “government-created monopolies”.  In the not so distant future, residential PV may be augmented with onsite storage (as suggested by Tesla’s announcement this week of its Powerwall home battery system).

SolarInstallCapacity

Residential is now a growing share of U.S. PV installations. Source: GTM research

The new emphasis on distributed generation has created a very unusual coalition between some traditional environmentalists and some anti-government crusaders.  Parts of the tea party movement have joined the Sierra Club in advocating for “DG-friendly” residential electricity tariffs, which mean high volumetric electricity charges in order to make rooftop solar economic.

I’m sorry, but count me among the people who get no special thrill from making our own shoes, roasting our own coffee, or generating our own electricity.  I don’t think my house should be energy independent any more than it should be food independent or clothing independent.   Advanced economies around the world have gotten to be advanced economies by taking advantage of economies of scale, not by encouraging every household to be self-sufficient.

That’s not to say that distributed generation couldn’t be the best way for some people at some locations to adopt renewables, but simply that DG should not be the goal in itself.  We desperately need to reduce greenhouse gases from the electricity sector, not just in the U.S., but around the world, including some very poor countries where affordability is a real barrier and electricity access is life-changing.  If DG is the least costly way to get that done, I’m in, but the choice should be driven by real cost-benefit analysis, not slogans about energy freedom.  TopazSolarFarm The 550 MW Topaz Solar Farm in San Luis Obispo County, California

The Pros and Cons

Compared to grid-scale renewables, DG solar has many advantages.  Generating and consuming power onsite means no line losses, which typically dissipate 7%-9% of grid-generated electricity before the power gets to your house. In addition, DG solar occupies your rooftop, a space that doesn’t have a lot of alternative uses, so the real estate cost is essentially zero.[1]  And as an extra bonus those solar panels also shade part of your roof, reducing the heat gain on hot sunny days.

In certain cases, distributed generation delays distribution system upgrades as demand on a circuit grows, because less power has to be shipped into the circuit on sunny days.  It also can reduce the need to build new transmission lines to carry power from distant grid-scale generation.

Having many small DG solar installations also spreads them around – spatial diversification – reducing the overall volatility of generation when clouds roll through.  Plus, spatial diversification and onsite generation can make the system more resilient to natural or man-made disasters, such as storms or sabotage.

Solar_panels_on_house_roof_winter_view

The obligatory residential PV photo  (Source:http://256.com/solar/images/)

But distributed generation also has some serious drawbacks.  The first and foremost is that design, installation and maintenance of solar PV small rooftop by small rooftop costs a lot more per kilowatt-hour generated than grid-scale solar, probably about twice as much these days.  The scale economies that are lost with small systems on roofs of different size, shape, and orientation is a big disadvantage compared to grid-scale solar plants that are 10,000 to 100,000 times larger than a typical residential installation.  The size of grid-scale plants also makes tracking devices practical, which allows the panels to move throughout the day to continually face the sun and generate more electricity.

While small scale spatially-diversified generation could in theory reduce distribution upgrades and improve resiliency if the location and types of installations were optimized for those benefits, that’s not how DG solar is actually getting installed.  Systems are put in where homeowners choose to install for their private benefits regardless of the impact on the grid, and they can actually destabilize distribution circuits when they pump too much power back into the grid.  In Hawai’i, where 12% of houses now have rooftop solar, that’s already a serious concern.

Though it’s great that DG solar can contribute energy to the grid when the household doesn’t consume it all onsite, exporting power from the house reduces the DG advantage in line losses and distribution capacity upgrades.  For a typical residential system, at least one-third of the electricity generated is injected into the grid, though that may change with cheaper small-scale storage, one of the many technological factors in flux.

The technology installed with DG solar also is not optimized for the grid, so current systems aren’t contributing to resilience.  Solar PV installed today doesn’t have the smart inverters or the onsite storage that would be necessary for the systems to remain operational when the grid goes down.  Closely related, DG solar systems aren’t communicating with – or controllable by — the grid operator, so the system operator has to just guess when they might start and stop pumping power into the grid.

How do these pros and cons sort out?  Right now, I believe that residential solar loses to grid scale.  But I’m not convinced that will always be true.  And I don’t think that means households should be impeded from adopting DG solar today, just that we shouldn’t be giving it special incentives.   We need to recognize that DG’s role in the electricity future is uncertain and locking in on this (or any other) technology is unwise.  

An economically resilient system for renewables adoption

Well, then, how should we decided whether to go with DG renewables or grid-scale technologies?  We shouldn’t decide.  Instead we should design incentives that reflect the real benefits and costs of each type of system and then let them battle it out.  This has two big advantages.  First, it reduces the political fighting that comes with policymakers choosing one technology over another, or even the share that each technology should get.  Second, it pushes all alternative technologies to keep innovating and lowering their costs.

Designing such science-based incentives isn’t easy.  It requires detailed examination of each of the costs and benefits I’ve listed (and probably others that commenters will suggest).  It will not be possible to nail down each of these factors exactly, but we can’t make good electricity policy if we don’t carefully study what benefits and costs each technology brings to the table.  Tying renewables incentives to the best engineering and economic analyses of their net benefits will involve some heated debates about those analyses, but at least we will then be arguing about the right issues.

Then we should craft incentives that accurately reflect the net benefits each alternative technology offers.  I’m not sure exactly how those incentives should be structured.  But I can tell you that they don’t involve paying households retail rates for power injected into the system, as net metering policies currently do.  And they don’t involve maintaining retail rates that are many times higher than avoided costs — even including pollution costs — in order to create artificially high savings for PV adopters, as the current tiered electricity rates do in many states, especially in California.

They do include much greater use of time-varying pricing and, probably, location-varying pricing to reflect the real value of power on the grid.

Smart incentives based on careful analyses can reflect the dynamic value of distributed solar and distributed storage.  Curtailing net metering would boost the value of battery storage.  A lower cost of storage would smooth out prices over time and location, which would reduce the production timing advantage solar has, but would also reduce the problems of load balancing on individual circuits as DG solar ramps up.  Lowering volumetric residential rates would make end-user storage less valuable by closing the gap between retail and wholesale prices.

If DG solar with incentives that reflect its true benefits wins, that will be great, because we will know we’ve got the least-cost approach to reducing the externalities of electricity generation.  If it sputters, that will be fine too, because it will indicate that there are other less-expensive ways to achieve our environmental goals.  Either way, it’s time for incentives that are truly calibrated to costs and benefits, not to achieving penetration of one low-carbon technology over another.

[1] Though many people don’t have a roof for solar, either because they live in multi-family housing or, in the developing world, because the roof can’t hold the weight of solar panels.

To join the Energy Institute email list and receive notices of new blogs, working papers and events (one or two per week), click here

Posted in Uncategorized | Tagged , | 38 Comments

Air Conditioning and Global Energy Demand

Sales of air conditioners have exploded worldwide over the last few years, driven by middle-income countries where households and businesses are buying air conditioners at startling rates. My colleagues Max and Catherine have written about China, for example, where sales of air conditioners have nearly doubled over the last 5 years. In 2013 alone there were 64 million air conditioners sold in China, more than eight times as many as were sold in the United States.

china

In a new paper coming out this week in PNAS, Paul Gertler and I examine the enormous global potential for air conditioning. The paper is available here. Household incomes are rising around the world and global temperatures are increasing. Both factors will drive increased adoption of air conditioners.

This is mostly good news. Air conditioning will bring relief to the more than three billion people who live in the tropics and subtropics. However, meeting the increased demand for electricity will also be an enormous challenge requiring trillions of dollars of infrastructure investments and potentially resulting in billions of tons of increased carbon dioxide emissions.

Our evidence comes from analyzing rich microdata from Mexico, a country with an unusually varied climate ranging from hot and humid tropical to arid deserts to high-altitude plateaus. As the figure below illustrates, we find little air conditioning in cool areas of the country, at all income levels. Even at high income levels saturation never exceeds 10%. In warm areas the pattern is very different. Saturation begins low but then increases steadily with income to near 80%. In gray is the distribution of annual household income.

Fig 4a

Fig 4bFig  4 LabelSource: Davis and Gertler, PNAS, 2015.

We combine our estimates with economic and temperature change forecasts to predict future air conditioning adoption in Mexico. Under conservative assumptions about income growth, our model predicts near universal saturation of air conditioning in all warm areas within just a few decades. Temperature increases contribute to this surge in adoption, but income growth by itself explains most of the increase.

To get some sense of the global implications, the table below lists the top 12 countries in terms of air conditioning potential, defined as the product of population and cooling degree days (CDDs). Excluding the United States, the list is dominated by middle- and low-income countries with warm climates. A total of almost 4 billion people live in these 11 countries, subject to an average of 2,700 annual CDDs.

Table 2Source: Davis and Gertler, PNAS, 2015.

Take India, for example. Compared with the United States, India has four times the population, but also more than three times as many CDDs per person. Thus, India’s total potential demand for cooling is 12+ times that of the United States. India already experiences frequent brownouts and blackouts, as Catherine blogged about here, which would be exacerbated by increased air conditioning if infrastructure does not keep apace of demand.

What air conditioning will mean for electricity consumption and carbon dioxide emissions depends on the pace of technological change. Continued advances in energy-efficiency or the development of new cooling technologies could reduce the energy consumption impacts substantially. Similarly, growth in low-carbon electricity generation could mitigate the increases in carbon dioxide emissions.

The future pattern of air conditioning adoption will also reflect what happens to prices. Equipment prices are likely to continue to decrease, which would further accelerate adoption. What will happen to electricity prices is less clear. A substantial increase in electricity prices, for example, resulting from carbon legislation, would slow both adoption and use.

Finally, there are broader adaptations that over a long time period could substantially reduce the need for air conditioning. Previous studies have found that people move away from regions affected by extreme temperature, so migration could mitigate the need for air conditioning. Demand for cooling also depends on how we build our homes and businesses, norms that can evolve over time in response to changes in climate as well as the availability and cost of cooling technologies.

The continual increase in global incomes means people are living more comfortably. This should be celebrated. But at the same time, it also means real challenges for electricity infrastructure and the global environment. We need an “all-hands-on-deck” approach including aggressive funding for innovation, efficient pricing of energy, and evidence-based environmental policies. We need efficient markets if we are going to stay cool without heating up the planet.

Posted in Uncategorized | Tagged , , | 7 Comments