An Investigation of Solar Friendly Policies in American States’ Renewable Portfolio Standards

CLOSUP Student Working Paper Series Number 32 April 2018

An Investigation of Solar Friendly Policies in American States’ Renewable Portfolio Standards Will Horne, University of Michigan

This paper is available online at http://closup.umich.edu Papers in the CLOSUP Student Working Paper Series are written by students at the University of Michigan.

This paper was submitted as part of the Winter 2018 course PubPol 495 Energy and Environmental Policy Research, that is part of the CLOSUP in the Classroom Initiative.

Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the view of the Center for Local, State, and Urban Policy or any sponsoring agency

Center for Local, State, and Urban Policy Gerald R. Ford School of Public Policy University of Michigan

An Investigation of Solar Friendly Policies in American States’ Renewable Portfolio Standards

By Will Horne Abstract: Solar power has historically been a high cost form of renewable energy. Other renewables like wind have dominated the market, leading to a lack of diversity within American states’ renewable portfolio standards (RPS). To combat this lack of diversity, states have started to pass solar friendly policies that either spur solar development in their state (multiplier), or force their state to develop solar power (solar carve-out).This paper uses an inventory to attempt to better understand the extent to which solar friendly policies exist within RPSs, and whether or not patterns exist within these policies. The analysis section highlights three major conclusions: 1) the higher the percent solar used/potential in a state, the less likely that state is to have a multiplier; 2) the higher a state’s solar technical used is, the greater the likelihood that it has a solar carve-out; 3) the legislative language for RPSs differs drastically across states—some use RPS to create jobs, some use it to protect the environment, and some use it to support local renewables manufacturers. Therefore, there is no one “best” solar friendly policy, and instead policymakers can tailor these policies to both help their state and the environment.

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Introduction: In 1983, Iowa passed the Alternative Energy Law, establishing the first Renewable Portfolio Standard (RPS) in the U.S. A renewable portfolio standard is a binding piece of legislation that requires either a certain amount or a certain percentage of a state’s electricity come from renewable energies. It called for its two largest investor-owned utilities to create 105 MW of renewable and associated energy production (IAC 199-15.11, 2007). In 1999 Iowa met the requirement and has since significantly exceeded that goal (American Wind Energy Association, 2017). To reach this goal, Iowa ramped up its wind production and has now become a leader of wind development among American states. In 2016, wind energy accounted for 36.59% of Iowa’s total energy, which ranked first in terms of wind as a percentage share of the state’s total energy production (American Wind Energy Association, 2017). Overall, Iowa’s RPS represents a success story of American renewable energies, and it set a precedent that 28 other American states would follow.

Within the RPS success story, however, a deeper problem exists: lack of renewable energy diversity. In 2017, U.S. renewable energy production accounted for 17.1% of its total energy production, but 13.8% of that production came from just wind and hydropower (U.S. Energy Information Administration, 2018). All other renewable energy sources including biomass, solar, and geothermal accounted for just 3.3% of total U.S. energy production (U.S. Energy Information Administration, 2018). This is not surprising when examining the economic conditions surrounding renewable energies, though. Historically, wind has been a far more cost effective option for utility companies, particularly when compared to solar energy (Barbose, 2017). As a result, wind energy became utility companies’ favorite medium to reach RPS requirements. From 1998-2009 wind accounted for 93.9% of all RPS-motivated capacity

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additions, while solar accounted for only 1.5% of these additions (Wiser, Barbose, Holt, 2011).

This lack of diversity has placed solar manufacturers at a disadvantage, because they have lacked the opportunity or resources to stack up to wind. This lack of diversity has further tipped the balance toward wind.

In the last four years, however, some states have attempted to combat this lack of diversity by passing solar friendly polices within their renewable portfolio standards. These policies are almost exclusively an iteration of either a solar carve-out or a multiplier. A solar carve-out works as a mandate, requiring utility companies to provide a certain percentage of their energy through solar power. Multipliers work as a financial incentive, allowing utility companies to double or triple count their solar energy projects toward meeting their renewables mandate.

While policies that aim to increase solar power within renewable portfolio standards exist, the extent to which they exist and their relationship with a state’s solar power utilization or its potential has still gone largely under researched. Therefore, it becomes crucial to understand which states have these solar friendly policies, and whether or not patterns exist within these policies.

Literature Review: In their research, Wiser, Barbose, and Holt (2011) address the current state of Renewable Portfolio Standards in the United States and respond to the growing dialogue around the makeup of renewable portfolio standards. Their first point of emphasis is that wind effectively monopolized early RPS investments. Through their research they discovered that 94% of all RPS-driven renewable energy capacity additions came in the form of wind between 1998 and 2009. They also use the historically high cost of solar as a piece of evidence to support the

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expansion of wind early on. The second half of their paper focuses on the changing economic situation surrounding solar power, particularly in the Southwestern United States. In California between 2002 and 2010, the state’s investor owned utilities and publicly owned utilities signed contracts that resulted in 21 GW of new renewable capacity in the state, of which 41% was for solar power. Finally, they briefly discuss how federal tax incentives, state renewable energy rebates, solar set asides, and incentive programs have played a major role in shifting solar capacity and encouraging the growth of solar power in RPS.

However, while Wiser, Barbose, and Holt (2011) discuss the historical significance of incentivizing solar growth, Herche (2017) conducts the ground-level research necessary to actually determine how falling prices, increased support from the public, and favorable legislation affect the most recent wave of renewable portfolio standards. Herche has a series of hypotheses regarding the correlation between solar generation, RPS, and overall electricity price, but the most applicable hypothesis is that there is a moderating interaction effect between RPS percentage targets and potential solar generation—meaning Herche believes states with higher RPS will have a stronger positive correlation to overall solar energy potential. He uses data collected by the US Department of Energy to examine these interactions with actual electricity generation from utility-scale solar sources aggregated by year and state representing the dependent variable. Herche was able to discover that there was in fact a statistically significant positive relationship between RPS standards and solar energy production. This confirms the belief that states that have higher renewable portfolio standards have higher energy generation from solar.

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Herche’s conclusion, while intuitive, was crucial to the existing set of research, solidifying the belief—with real data—that increased RPS standards lead to increased solar energy production. However, Herche doesn’t examine the actual reason this occurs; more specifically, Herche’s research is unable to inform us on what might be the best way to reach increased solar capacity. This is where Sarzynski, Larrieu, and Shrimali’s (2012) research on “The Impact of State Financial Incentives on Market Deployment of Solar Technology” is so crucial. They investigate how states’ adoption of financial incentives has encouraged market deployment of solar energy technology. To determine the correlation between state-level financial incentives and solar energy adoption the paper uses a cross-sectional time-series approach. The data was collected from a variety of different sources including the Database of State Incentives for Renewable Energy. The four types of financial incentives examined are the following: cash incentives, income tax incentives, sales tax incentives, and property tax incentives. Their final conclusion was that states offering cash incentives had “significantly stronger” market deployment of solar PV than states without cash incentives. However, states with tax incentives did not see a systematically stronger deployment of solar PV than states that did not have tax incentives. One caveat they make though, is that this is likely the result of the difference in effective size of the incentives and the ease at which they can be claimed. Cash incentives tend to be larger and easier for customers to understand. This proved particularly true for PV installation. Overall, Sarzynski, Larrieu, and Shrimali’s research better equips us to understand the effectiveness of different state financial incentives on solar deployment.

Buckman’s (2011) research on the effectiveness of banding and carve-outs in RPS with regards to supporting high-cost types of renewable portfolios helps to provide the last piece of contextual research. Banding operates in a similar way to cap and trade. A certain number of

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certificates are issued for each form of energy, and that is the amount of energy the government allows to be produced. These are very popular in the UK, and help high-cost renewables by closing the gap between low-and high-cost renewables through issuing more of a high-cost certificate than would be reached in a system operating only under market forces. 1 Buckman’s examination occurs across nations, as opposed to just within the United States, because banding is a central part of the UK and other European countries’ plan to address greenhouse gas emissions. In 2011, when Buckman wrote his paper, only 11 of the 26 RPS plans had carve-outs of any kind, and only four state had carve-outs that accounted for at least a quarter of their states’ RPS target (Maine, New Hampshire, New Mexico, and Pennsylvania). Also, a majority of these carve-outs were not solar specific. For example, in 2004 Pennsylvania passed a RPS that called for 18% of the state’s energy to be renewables by 2020. The carve-outs accounted for 10.5% of the RPS, with the largest carve-out being a 10% carve-out for waste coal, distributed generation, and large hydro, municipal waste or gasified coal. Furthermore, of all the carve-outs, the largest solar carve-out is only 4% of the RPS. Overall, Buckman’s paper highlights the fact that in the first decades of RPS plans, solar energy has effectively had no significant place. Even within states that used carve-outs as a way to force their utility companies to pursue high cost renewables, the solar carve-out was rare and often solar energy was still seen as too costly to force utility companies to invest in. Instead, these states and utility companies pursued other forms of high-cost renewables.

The previous articles lay the foundation for understanding both renewable portfolio standards and the solar policies that can exist within them at the state and international level, but

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This doesn’t mean more high cost certificates are issued, but it does mean that more high cost renewables will be used than would be without the banding.

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they do not address the connection between solar policies and cities. This is where Li and Yi’s (2014) research on U.S. cities and their role in implementing solar PV installations is crucial.

They help us better understand the grassroots level of solar energy and solar installation. Li and Yi use a cross sectional data set gained through survey data to examine the various factors influencing solar deployment in U.S. cities. They found that cities that are subject to RPS requirements have 295% more solar PV installations. However, Li and Yi did not find a significant correlation between solar carve-out and cities’ solar PV capacity. On the local level, they found that local financial incentives played a significant role in motivating local PV installations—69% more PV installations in cities with incentives. Overall, Li and Yi’s study proves that local governments do play a significant role in solar PV developments.

After using Li and Yi’s research to better understand how local governments can influence solar installation and development, the next step is to look at how states have historically incentivized solar, and how that is changing. Daim, Kayakutlu, and Cowan (2010) help us accomplish this through their examination of Oregon’s 2007 Renewable Portfolio Standard, which required 25% of the state’s electricity come from renewable energies. Their research is more economic than those previously mentioned, because it focuses on how policy will be implemented. They use a “Fuzzy goal programming” model which allows them to control and adjust for confounding variables. And while they address a series of broader questions in their study, their examination of solar power is particularly interesting. Their model describes how in 2008 the provision of solar was only 8% and wind was 35%, but that by 2023 solar will overtake wind as the primary supplier of energy for Oregon. In their discussion they specify that the falling cost of unit construction and unit production are the primary reasons for this shift.

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Finally, Schelly’s (2014) paper on Renewable Portfolio Standards comparing Wisconsin and Colorado’s rebate and incentive structures and how they differ regarding the adoption of residential PV technologies uses a two-case study approach to provide a useful understanding of solar carve-outs. Schelly mainly focuses on how Wisconsin and Colorado’s policies differ with regards to how they incentivize residential solar electricity adoption. Colorado only provides rebates up to 10 kW, while Wisconsin provides them up to 20 kW. Colorado also differs in that it offers a large upfront rebate and PV adopters are paid back at wholesale rates, while Wisconsin offers a smaller one-time rebate with more lucrative buy-back agreements. Then, Schelly conducted interview research with people who have solar panels in both states. Schelly’s two main conclusions are that, because of financial incentives, feed-in tariff policies encourage even those without an environmental orientation to install PV technologies, while large one-time rebate incentives like Colorado’s may decrease up-front costs, but do not necessarily increase access to residential PV systems.

The previous seven pieces of research provide the necessary context and insight into RPS, solar-carve outs, and solar pricing needed to understand this paper and its objective. Wiser, Barbose, and Holt (2011) and Herche (2017) explain the current state of RPSs in the U.S. and how fallings prices and increased public support affect them. Sarzynski, Larrieu, and Shrimali (2012) expand on how state incentives are effecting the actual deployment of solar installations, and Buckman (2011) provides information on banding and carve-outs in America and abroad. Li and Yi (2014) then explain how cities fit into the equation surrounding solar energy, installation, and legislation; Daim, Kayakutlu, and Cowan (2010) expand on Oregon’s RPS and help create a framework of how to effectively research a particular state’s RPS; and Schelly (2014) finishes with a strong example of how to compare RPSs and their success across states.

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This wealth of research, however, still neglects to provide readers with a succinct, easily accessible resource that expresses current RPS solar energy policy. Therefore, this paper attempts to better understand the extent to which solar energy polices exist within states’ RPSs, as well as investigate any possible patterns that may exist within this field.

Methods: When creating the inventory for this paper, I had to make two key decisions: what states to include and what policies to include. DSIRE’s map of renewable portfolio standard provided the background information necessary to make these decisions (DSIRE, 2018). I also read several renewable portfolio standards to help me better grasp what was located within their legislative language. After gathering this data, I decided not to include states which have only passed renewable portfolio goals, as opposed to renewable portfolio standards. A renewable portfolio goal is a piece of legislation passed by a state to express its renewable energy goals.

These goals are non-binding and states have no way of ensuring their targets are met. This is problematic because voluntary targets mean states can pass whatever energy goal they want without worrying about economic or political ramifications. This could lead states to pass goals that are not realistic based on their state’s renewable energy operating capacity, resulting in skewed observations and inaccurate inventory data. States also sometimes pass a renewable portfolio goal after already having a renewable portfolio standard. These goals are also nonbinding, and therefore not included in the inventory.

Next, I had to decide what solar friendly polices would be included in the inventory.

Once again, DSIRE provided the background information necessary for this step, because its website has a series of literature that lay out the different types of solar friendly policies that

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exist. I decided to include solar carve-outs, banding, and multipliers. My initial research and literature review revealed that these three solar friendly policies combined to encompass effectively all possible ways that a state government could try to increase its solar energy utilization, within the context of a RPS. As stated before, solar carve-outs work as a mandate, multipliers work as a financial incentive, and banding provides government with a way to directly regulate energy.

For each column, either “yes” or “no” will be recorded depending on if a state has that particular solar friendly policy. Also, after the solar carve-out and multipliers columns, the inventory has a column to indicate the extent of that policy. Doing this allows for more in-depth analysis than just presence-absence. Instead, I want to be able to look at the spread of these polices, their averages, and a variety of other topics. A column on the year the solar carve-out has to be fulfilled by is also included. Doing this helps to a common point of comparison between solar carve-outs, because 3% solar by 2019 is very different than 3% solar by 2050, a distinction one would not be able to see if the year was not included. Finally, backward looking multipliers are not included in this inventory. This means that if a multiplier was passed that does not allow future installations to be counted or included, it will not be included in any calculations. This is an important distinction, because a backward looking multiplier does not incentivize the building of future solar installations.

In the desire to create as encompassing of an inventory as possible, I turned to DSIRE to better understand the ways in which solar energy can be harnessed, and quickly realized a column on just solar carve-outs and multipliers was not going to be sufficient. Instead, I discovered that there were three main categories for which legislators create carve-outs and

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multipliers: solar electric, photovoltaic (PV), and distributed generation. Solar electric is a term used to describe all types of solar energy generation that create electricity. Effectively, solar electric is everything except solar water heating, which is a way of harnessing solar energy to heat water. Solar water heating is not included in the inventory, because it does not produce electricity, and so trying to compare it to forms of solar energy that do create electricity is unnatural. Solar photovoltaic, commonly referred to as solar PV, is a way of harnessing solar energy through solar panels that convert the sun’s electrical energy from DC to AC. Distributed generation is not necessarily specific to solar energy, but in the context of this paper it is referencing a decentralized power system, in which solar energy is harnessed by either a local utility company or an individual. These are much smaller operations that provide power to areas very close to them and usually don’t exceed 20 MW. These three methods encompass the full scale of solar generation within a state, including both the ways in which solar energy can be harnessed and the scale at which it can be harnessed at. I also included a column for customersited carve-outs. These occur in New York and Colorado. Customer-sited is effectively the same thing as distributed generation, but on a slightly larger scale. Customer-sited solar harnessing can occur across a few locations, as opposed to one like distributed generation, but it still has to be owned and operated by one individual or utility and it cannot exceed a predetermined MW.

Finally, the inventory has one column for solar technical potential and one column for solar technical used. Solar technical potential represents the technological capacity each state can use to capture and utilize solar power. Including solar technical potential is important, because it allows for investigation into to the relationship between sunlight and solar friendly policies. In laymen’s terms, solar technical potential allows us to better understand if sunnier states really do have more solar friendly policies. It may seem like an elementary question, but it could have

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substantial ramifications for policymakers, particularly with regards to how they go about attempting to increase solar friendly policies in their state. Solar technical potential is not the same as total solar potential, though. Total solar potential gauges just how much solar energy a state could capture if it were to build the necessary infrastructure. Choosing solar technical potential instead of total solar potential allows for more unique data comparison. For example, Arizona will always have a greater total solar potential than Illinois or New Jersey, but that does not mean Arizona necessarily has a greater solar technical potential. The data is presented in Lopez et al. (2011), though I combine the data the authors provide separately for utility-scale, rural-scale, and rooftop solar potentials. Combined, these three calculations represent each state’s total solar technical potential measured in gigawatt hours (GWh).

Solar technical used is the actual amount of gigawatt hours that a state produces. This is an important data point, because it quantifies how good states are at utilizing the solar energy capacity that is already present in their state. This information was gathered from the U.S. Energy Information Administration (2017). I also added in a column after these two called “Percent (Used/Potential).� Doing this creates an easily understood metric to compare states to one another with, and eliminates the problem of states having different solar technical potentials.

Finally, links to the actual renewable portfolio standards can be found in the inventory citations section of the paper. Most of the links are to the actual pieces of legislation. However a few states are linked to DSIRE, because I had to examine a few different pieces of legislation for these states and linking to DSIRE was more efficient than including several links.

Overall, the methods stated above attempted to create a comprehensive spreadsheet that addressed the many different categories within solar energy in RPS, while still recognizing the limitations of research being conducted in only a few weeks.

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RESULTS: Figure 1 highlights that, of the 29 states that have renewable portfolio standards, 17 states have some form of solar carve-out in place in their RPS. These states require that, on average, 2.54% of electricity production come from solar. However, there is also a large spread for states’ actual solar carve-out policies. North Carolina has the smallest mandate with only .2% of their state’s overall energy production needing to come from solar energy, while Vermont has the largest solar carve-out at 10%—see Appendix A. It is important to note that you cannot make a direct one-to-one comparison between most of these solar carve-outs, because their required date of implementation is very different. For example, North Carolina only requires .2% of their total energy come from solar, but its mandate requires the state to reach this goal by 2018. On the other hand, Vermont’s carve-out requires a much more ambitious 10%, but by 2032.

FIGURE 1: Do States Have Solar Carve-Outs?

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Figure 2 shows that 4 of these solar carve-outs are for PV only, 8 are for solar electric only, 4 are for distributed generation only, and 2 are customer-sited specific—Colorado has a solar carve-out that includes customer-sited and another type of solar carve-out, while New York just has a customer-sited solar carve-out. The PV solar carve-outs have a spread of 0.5% (Pennsylvania) to 3.5% (Delaware) and a mean of 1.75%. The solar electric solar carve-outs have a spread of .2% (North Carolina) to 4.10% (New Jersey) and a mean of 1.725%. The distributed generation solar carve-outs have a spread of .25% (Illinois) to 10.00% (Vermont) and a mean of 4.4375%. The customer sited solar carve-out only have two polices: .58% (New York) and 1.50% (Colorado).

FIGURE 2: Makeup of States’ Solar Carve-Outs

There are seven multipliers present within the 29 RPS in existence in America today— Figure 3. States most commonly use a multiplier of either 2 or 3, which is reflected in the average multiplier of 2.49. Of these seven multipliers, there was little variability between the multipliers for PV, solar electric, or distributed generation. Three states have PV multipliers, two states have solar electric multipliers, and one state has a distributed generation multiplier 14

(Washington)—New Mexico has a multiplier, but the language in its RPS is generic and applies to solar energy production at large within the state.

FIGURE 3: Do States Have Solar Multipliers?

Finally, no state had a provision for banding within their RPS. There was not even language hinting to the possible use of banding within states’ renewable portfolio standards.

ANALYSIS: In order to better understand whether there is a connection between a state’s overall solar utilization and solar friendly policies within its RPS, in Figure 4, I have sorted the inventory based on percent solar/potential. In general, the higher a state’s percent utilized was, the less likely it was to use multipliers. For example, none of the eight states with the highest percent utilization used multipliers. Nevada is the first state to use a multiplier based on this sorting method and it only ranks ninth with 0.0361% of its solar potential being utilized. The correlation between higher percent utilized and lower likelihood of using multipliers is even stronger when examining the actual percent used/potential of those top eight states. All of their values are

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above .0722%, and the top five states all have a higher value than 0.1027%. However, if you look at the values under Nevada, none are higher than 0.0332%.

FIGURE 4: Solar Carve-Out and Solar Multiplier Sorted by Solar Percent (Used/Potential)

Solar Percent State (Used/Potential) 0.5469% Massachusetts 0.2120% Hawaii 0.2042% California 0.1670% New Jersey 0.1027% Vermont 0.0856% Rhode Island 0.0790% North Carolina 0.0722% Connecticut 0.0361% Nevada 0.0332% Maryland 0.0313% Arizona 0.0177% Delaware 0.0118% Pennsylvania 0.0089% New York 0.0052% Colorado 0.0046% New Mexico 0.0019% Texas 0.0018% Ohio 0.0011% Oregon 0.0006% Illinois 0.0006% Missouri 0.0002% Michigan 0.0001% Minnesota 0.0001% Wisconsin 0.0000% Washington 0.0000% Iowa 0.0000% Maine 0.0000% Montana 0.0000% New Hampshire

Solar CarveOut yes no no yes yes no yes no yes yes yes yes yes yes yes yes no yes no yes yes no yes no no no no no yes

Solar CarveOut % 400 MW

By what year 2020

4.10% 10.00%

2028 2032

0.20%

2018

1.50% 2.50% 4.50% 3.50% 0.50% 0.58% 4.50% 4.00%

2025 2020 2025 2026 2021 2015 2020 2020

0.50%

2027

1.75% 0.30%

2026 2021

1.50%

2020

0.70%

2025

Solar Multiplier Multiplier no no no no no no no no yes 2.4 no no yes 3 no no yes 3 yes 3 no no yes 2 no no yes 2 no no yes 2 no no no no

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This leads to the conclusion that as states begin to better utilize their solar potential, they do not need to use multipliers. One possible reason for this is that states who do not utilize a lot of solar power try to lower the “effective” cost of solar power to utility companies by using multipliers. Lowering the effective cost doesn’t change the actual price of solar, but by being able to double and triple count solar towards a renewable mandate, it makes solar cheaper. The gigawatt hour of solar energy the utility company was producing now becomes two—or three— gigawatt hours of solar energy, meaning the utility company does not have to spend the extra resources to produce the extra unit. But as states utilize more solar energy they gain institutional knowledge that lowers the real cost of solar power to their states individual firms, which allows the states to remove the multipliers. The evidence from the inventory appears to support this claim, because once a state has a strong foundation of solar energy, it does not use a multiplier.

However, to reach a more definite conclusion, information on percentage used/potential by year will have to be compared to the year a multiplier is implemented (and removed) from a state’s renewable portfolio standard.

And while there was a pretty clear correlation between percent utilized and multipliers, there was not a similar correlation between percent utilized and solar carve-outs. Of the states with the eight highest percent utilization only four of them had solar carve-outs. There was not even correlation within the type of solar carve-out they used. Two states had solar electric carve outs, one state had a distributed generation carve-out, and one state had a general megawatt specific carve-out. Roughly the same relationship exists in the middle of the rankings—of the eight states that make up the rankings 15-22, five of them have solar carve-outs.

I want to draw attention to New Hampshire, because it is an outlier in this sorting method. New Hampshire has zero solar technical potential used, but a solar carve-out of 0.70%

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by 2025. Initially, I thought this phenomena was a byproduct of New Hampshire adding in a solar carve-out during a recent RPS revision. However, New Hampshire’s most recent revision to solar friendly policies was 2007. New Hampshire also does not have an outline regarding how utility companies have to reach this goal. Therefore, it is likely that utility companies see the declining price of solar and are choosing to wait until closer to 2025 to take advantage of the cheapest possible solar price.

Finally, there is a rather predictable correlation at the end of the chart. Excluding New Hampshire, the states with the five lowest percent utilization had no solar carve-out. This conclusion is unsurprising because it suggests that the states that do the worst job of utilizing their solar potential (between 0.00005 and 0.0% utilization) do not have a solar carve-out. This makes intuitive sense, because if they had a solar carve-out—which effectively acts as a mandate—then they would be required to have some level of solar energy.

Next, to try and determine if there is a correlation between the actual amount of solar energy a state produces and the likelihood that they have solar friendly policies, I sorted the inventory by “Solar Technical Used (GWh).”

Only two of the six states with the highest solar technical used have multipliers, and three of the top ten have multipliers. Similarly, if we exclude the three states that have zero solar technical used, then of the fives states with the lowest solar technical used only two have multipliers. These both seem to advocate for a pretty loose correlation between multipliers and solar technical used. However, there are two very interesting points within this sorting method that point to the possibility of a stronger relationship than at initial glance

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FIGURE 5: Solar Carve-Out and Solar Multiplier Sorted by Solar Technical Used (GWh)

State California Arizona North Carolina Nevada New Jersey New Mexico Texas Massachusetts Colorado Maryland New York Hawaii Pennsylvania Ohio Vermont Delaware Illinois Oregon Missouri Connecticut Rhode Island Minnesota Michigan Wisconsin Washington Iowa Maine Montana New Hampshire

Solar Technical Used (GWh) 18,806.71 3,765.83

Solar CarveOut no yes

3,421.13 3,124.06 834.88 751.84 730.81 609.28 538.11 208.66 139.61 88.51 74.81 65.56 59.03 51.09 48.81 40.94 32.68 24.52 14.66 10.11 9.24 2.67 0.73 0.15 0.00 0.00

yes yes yes yes no yes yes yes yes no yes yes yes yes yes no yes no no yes no no no no no no

0.00

yes

Solar CarveOut %

By what year

4.50%

2025

0.20% 1.50% 4.10% 4.00%

2018 2025 2028 2020

400 MW 4.50% 2.50% 0.58%

2020 2020 2020 2015

0.50% 0.50% 10.00% 3.50% 1.75%

2021 2027 2032 2026 2026

0.30%

2021

1.50%

2020

0.70%

2025

Solar Multiplier no no no yes no yes no no yes no no no no no no yes no yes no no no no yes no yes no no no

Multiplier

2.4 3

3

3 2

2 2

no

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First, the middle of the distribution—states that occupied the 7th-21st positions— utilized multipliers far less. Only three of these fifteen states have multipliers, and if you narrow the scope even closer to the middle of the distribution than none of the states that occupy the positions 10th to 15th use multipliers. One possible reason for why more multipliers occur at the top of the solar technical used distribution is that the states which occupy the middle of the solar technical used potential already have a market for solar, but unlike the states with higher solar technical used they do not have the political desire to spur on this industry. Similarly, one possible reason for why more multipliers occur at the bottom of the solar technical used distribution is that states at the bottom have very high solar costs because they have such little economic engagement in those industries and they are trying to lower that cost for companies, while the same pricing problem does not exist within these middle-tier states. However, to reach a conclusion on these answers, further research on solar pricing in each state would need to be conducted.

The second point of interest is that of the four states that have solar technical used, also known as solar deployment, over 3,000 GWh, Nevada is the only one with a multiplier.

Depending on when its RPS was passed, this amount of solar deployment could be the result of a boom in solar industry tied to the multiplier or Nevada could be using the multiplier to try and further increase their solar energy prowess. To better understand this, research on when Nevada and the other three states that have solar deployment over 3,000 GWhs passed their most recent RPS would have to be done and then compared to the overall trend in the growth of their solar technical used.

And while the connection between solar technical used and multipliers is not immediately clear, the connection between solar carve-outs and solar technical used is much more obvious. Of

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the ten states that have the highest solar technical used, eight have a solar carve out. Similarly, three of the top six states have a solar carve out of 4% or higher. This correlation extends past just the top though, only 15 of the top 19 states have solar carve-outs. The most likely reason for this relationship is that after legislators pass the solar carve-outs, states begin to utilize more solar energy. This theory is further supported when examining the bottom of the distribution in which only two of the bottom ten states have solar carve-outs.

I then sorted by “Solar Technical Potential (GWh)” to see if the states with the highest potential were more likely to have solar friendly policies, and, unlike before, neither multipliers nor solar carve-outs had a strong correlation to this. States at all points along the solar technical potential (GWh) distribution used solar carve-outs and multipliers. One possible reason is that, in general, states have a pretty high potential for solar energy and American states are still so far from utilizing that potential that at this early junction solar energy potential is not a prominent factor state governments consider.

Finally, I sorted by “Solar Friendly Policies” as a way to see if having solar friendly policies, in general, had any correlation to “Solar Technical Used (GWh)”, “Solar Technical Potential (GWh), or “Percent (Used/Potential.)” However, this sorting method yielded the murkiest data. For example, California utilizes vastly more solar energy than any other state with over five times the solar technical used of the next closest state (Arizona) and it does not have any solar friendly policies within their RPS. Similarly, Texas has the highest solar technical potential and 7th highest solar technical used, but it does not have any solar friendly policies. And yet, New Hampshire has zero solar technical used and the fifth lowest solar technical potential, but it has a solar carve-out. However, Nevada, which has the fourth highest solar technical used, has both a solar carve-out and multiplier. This is in contrast with Arizona and North Carolina,

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which are both within 650 GWh of Nevada and yet do not have multipliers. North Carolina barely even has a solar carve-out—only .2%.

FIGURE 6: Solar Technical Used, Potential, and Solar Percent sorted by Solar Friendly Policies

State Colorado Delaware Nevada New Mexico Michigan Oregon Washington Arizona Illinois Maryland Massachusetts Minnesota Missouri New Hampshire New Jersey North Carolina Ohio Pennsylvania Vermont New York California Connecticut Hawaii Iowa Maine Montana Rhode Island Texas Wisconsin

Solar Friendly Polices both both both both multiplier multiplier multiplier solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out solar carve-out zero zero zero zero zero zero zero zero zero

Solar Technical Used (GWh) 538.11 51.09 3,124.06 751.84 9.24 40.94 0.73 3,765.83 48.81 208.66 609.28 10.11 32.68 0.00 834.88 3,421.13 65.56 74.81 59.03 139.61 18,806.71 24.52 88.51 0.15 0.00 0.00 14.66 730.81 2.67

Solar Technical Potential (GWh) 10,297,717 289,374 8,650,115 16,396,412 5,290,013 3,774,585 1,785,440 12,011,736 8,224,623 629,350 111,398 10,840,506 5,381,978 63,453 499,849 4,329,556 3,742,742 631,733 57,475 1,574,149 9,208,336 33,961 41,758 7,029,897 1,105,986 8,200,906 17,135 39,366,983 5,111,137

Percent (Used/Potential) 0.0052% 0.0177% 0.0361% 0.0046% 0.0002% 0.0011% 0.0000% 0.0313% 0.0006% 0.0332% 0.5469% 0.0001% 0.0006% 0.0000% 0.1670% 0.0790% 0.0018% 0.0118% 0.1027% 0.0089% 0.2042% 0.0722% 0.2120% 0.0000% 0.0000% 0.0000% 0.0856% 0.0019% 0.0001% 22

Overall, it is very difficult to draw clear distinctions about solar friendly policies at large from this data. This is likely a two-pronged problem. First, I do not have data on changes over time. Therefore, I cannot account for whether a state has, at any point, ever had a multiplier or solar carve-out. It is within the realm of possibility to image that a state like California has had a carve-out or multiplier in the past and dropped it at some point in its RPS revision. Second, I can’t track the political ideology in power during the passing of a state’s most recent RPS. This might be able to illuminate whether states with solar friendly policies are more prone to being one party or the other, as well as enlightening us on whether or not particular parties are bigger fans of a certain type of solar policy.

In the process of constructing the inventory, I discovered that the language of these solar friendly policies differed dramatically across state lines. One distinction within solar carve-outs was the “date applicable” distinction made in states’ RPSs. Certain solar carve-outs only count solar energy created by a generator within a specific time frame. For example, New Hampshire will only allow its .7% solar carve-out to be filled by generators that were created on, or after, January 1st, 2006. The most likely reason for this is that states with this provision are trying to incur additional solar growth in their state.

I was also surprised to see a clear distinction in the language of certain states around instate vs. out-of-state solar energy. Pennsylvania’s .5% solar carve-out has some of the most explicit language around this. In the early years of the RPS, Pennsylvania allowed utility companies to outsource their solar energy mandates to out-of-state locations to meet the requirement, but on October 30th, 2017 Pennsylvania no longer allowed solar PV systems located outside of the state to be eligible to meet the solar PV portion of their solar carve-out—solar

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installations that existed outside of the state before this deadline were grandfathered in. This kind of language likely exists, because many of these renewable portfolio standards are actually passed as clean job bills (HB 2607, 2015), and so allowing utilities to out-source their energy installations would be counterintuitive to the goal of bringing clean jobs to a state.

Finally, some states’ solar carve-outs had specific requirements depending on the scale of the utility company. For example, Minnesota requires that for a public utility with more than 200,000 retail electric customers, at least ten percent of the 1.5% goal be met by solar energy generated by or procured from solar PV devices with a nameplate capacity of 20 kilowatts or less, while public utilities with 50,000 and 200,00 retail electric customers are required to provide at least ten percent of the 1.5% goal through solar PV using devices with a nameplate capacity of 40 kilowatts or less. This is a direct contrast to some other states which have effectively no language regarding how different sized utility companies are to respond to the solar carve-out.

There is also a variety of language and implementation differences in states’ multipliers.

Similar to solar carve-outs, different states have different language regarding what types of solar generators the legislation applies to. For example, Delaware passed its RPS in 2010 and it states that all generators established on, or after, January 1st, 2015 are not able to use the multiplier.

This type of language occurs, because states want to lower the cost of solar in their state initially, but that once the initial boom of investment hits, they want to remove the incentive. This type of legislative language is clear evidence supporting the idea that multipliers are a short term policy mechanism meant to lower the effective cost of solar energy and bring in investment. It also shows that multipliers are likely not being used to diversify portfolios in the same way that solar carve-outs are.

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Another policy mechanism certain states use within their RPS to help spur initial investment, while not allowing larger utility companies to take advantage of the multiplier, is to cap the amount of energy that a utility company can use the multiplier on. Oregon has one of the most restrictive multipliers, because its 2 multiplier only applies to utility companies that use a PV installation of between 500 KW and 5 MW and the utility company can only use the multiplier to account for a maximum of 20 MW. Some states also create “add-on” multipliers for utility companies that meet certain employment and manufacturing criteria. Delaware’s RPS is one of the most explicit regarding this. It has a multiplier of 3, but a solar utility company could raise that multiplier to 3.2, if they meet two criteria: additional .1 if at least 50% of the equipment for the generator is made in Delaware, and additional .1 if at least 75% of the company’s employees are in-state workers.

This type of legislation is a clear example of how many of these renewable portfolio standards are a way to spur economic growth in a state and increase jobs.

Finally, its important to understand these findings in the context of other academic research. First, while it is difficult to draw a clear distinction without data that can track change across time, there does seem to be evidence to support Wiser, Barbose, and Holt’s findings that solar incentive programs—multipliers—have encouraged the expansion of solar power. The inventory table highlights this, because every state that has a multiplier has some level of solar power.

However, not all the findings of this paper fall perfectly in-line with current academic research. In Herche’s research, he discovered that states with higher renewable portfolio standards also had higher solar energy production. And while this may be true for renewable portfolio standards, it certainly is not true for solar carve-outs—which work as a mandate in a

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similar fashion as RPSs. Instead, there were several states that worked in total opposition to this idea. For example, California doesn’t have a solar carve-out and is leading the country in solar energy production, while New Hampshire has a solar carve-out and no solar energy production.

Also, these findings paint a much different picture of solar friendly policies in RPSs than Buckman’s 2011 research. Buckman found that in the first decades of RPSs solar energy had no significant place in RPSs and few policy tools to help incentivize it. However nowadays, 20 of the 29 states with RPSs have some form of solar friendly policy.

CONCLUSION: I want to draw attention to two limitations within my research. First, I cannot compare policies, solar technical used, or solar technical potential, across time. Not being able to track across time hinders my study’s ability to comment on how the state of solar friendly policies is changing. Instead, my research is just a snapshot of the present with regards to solar friendly policies. Further research should be conducted comparing states’ first RPS and their most current RPS, because then we can attempt to better understand where the future of solar friendly policies is moving.

The second limitation of my study is that I do not have a column for the political party that was in power when the state’s renewable portfolio standard was passed. The next researcher in this field should include this observation, because it will allow us to better understand which party is more likely to pass solar friendly policies and what kind of solar friendly policies each party favors. I want to caution against assumption making here. It is easy to assume that the Democratic party is more likely to pass such policies, but without research we should careful not to assume.

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While I cannot comment on time or political ideology, my research still has several key takeaways. First, solar technical potential is likely not a strong factor policy makers consider when creating solar policy. I reached this conclusion, because there was effectively no correlation between solar technical potential and the likelihood of having solar policies, but there were correlations between solar technical used and solar friendly policies and percent utilized and solar friendly policies. Therefore, it is likely that arguments based on solar technical potential will not yield pro-solar legislation. Instead, solar advocates should consider using other factors like economic development opportunities to argue for such polices.

Second, there is not one “best� solar friendly policy. Instead, each policy has its pros and cons. This is good for policy makers because it allows them to tailor policy to their state. It is also a limitation, however, because it requires policymakers to actually understand the different solar friendly policies and their effects on land use, jobs, and economic development.

Finally, every state is dramatically underutilizing its solar technical potential. No single state has 1% solar utilization. Therefore, policy makers should consider this underutilization and reexamine what it means within their state, because it is likely that they are missing an opportunity for political and economic gain.

Renewable portfolio standards are long and often hard to decipher. No two RPSs are written in the same way, and they all have their own legislative quirks. As a result, most ordinary Americans never take the time to engage with these comprehensive, but critically important pieces of legislation. Therefore, it is the responsibility of academics to spend our time rigorously deciphering these complex policies, because if we do not, it is likely no one will. This paper is my contribution. I hope it serves as the foundation for research to come on a variety of different solar friendly policies.

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References:

American Wind Energy Association. (2017). Wind energy in Iowa. http://awea.files.cmsplus.com/FileDownloads/pdfs/Iowa.pdf Barbose, G. (2017). U.S. renewables portfolio standards: 2017 annual status report. Lawrence Berkeley National Laboratory. https://emp.lbl.gov/sites/default/files/2017-annual-rpssummary-report.pdf Buckman, G. (2011). The effectiveness of Renewable Portfolio Standard banding and carve-outs in supporting high-cost types of renewable electricity. Energy Policy, 39(7), 4105–4114. http://doi.org/10.1016/j.enpol.2011.03.075 Daim, T. U., Kayakutlu, G., & Cowan, K. (2010). Developing Oregon’s renewable energy portfolio using fuzzy goal programming model. Computers & Industrial Engineering, 59(4), 786–793. https://doi.org/10.1016/j.cie.2010.08.004 DSIRE. (2018). Renewable portfolio standard policies. DSIRE. http://ncsolarcenprod.s3.amazonaws.com/wp-content/uploads/2017/03/Renewable-Portfolio-Standards.pdf HB 2607. (2015). The Illinois clean jobs bill. Illinois House of Representatives. https://ilcleanjobs.org/bill/ Herche, W. (2017). Solar energy strategies in the U.S. utility market. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2017.04.028 IAC 199-15.11. (2007). Alternative energy law. Iowa Legislature. http://programs.dsireusa.org/system/program/detail/265 Li, H., & Yi, H. (2014). Multilevel governance and deployment of solar PV panels in U.S. cities.

Energy Policy, 69, 19–27. http://doi.org/10.1016/j.enpol.2014.03.006 Lopez, A., Roberts, B., Heimiller, D., Blair, & N., Porro. (2011). U.S. renewable energy technical potentials: a GIS-based analysis. National Renewable Energy Laborratory. https://www.nrel.gov/docs/fy12osti/51946.pdf Sarzynski, A., Larrieu, J., & Shrimali, G. (2012). The impact of state financial incentives on market deployment of solar technology. Energy Policy, 46, 550–557. https://doi.org/10.1016/j.enpol.2012.04.032 Schelly, C. (2014). Implementing renewable energy portfolio standards: The good, the bad, and the ugly in a two state comparison. Energy Policy, 67, 543–551. http://doi.org/10.1016/j.enpol.2013.11.075

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U.S. Energy Information Administration. (2017). 1990-2016 net generation by state by type of producer by energy source. U.S. Energy Information Administration. https://www.eia.gov/electricity/data/state/ U.S. Energy Information Administration. (2018). What is U.S. electricity generation by energy source?. U.S. Energy Information Administration. https://www.eia.gov/tools/faqs/faq.php?id=427&t=3 Wiser, R., Barbose, G., & Holt, E. (2011). Supporting solar power in renewables portfolio standards: Experience from the United States. Energy Policy, 39(7), 3894–3905. http://doi.org/10.1016/j.enpol.2010.11.025 Inventory Citations: 1. Arizona: http://apps.azsos.gov/public_services/Title_14/14-02.pdf 2. California: http://www.energy.ca.gov/portfolio/documents/sbx1_2_bill_20110412_chaptered.pdf 3. Colorado: http://programs.dsireusa.org/system/program/detail/133 4. Connecticut: http://search.cga.state.ct.us/2017/ACT/pa/2017PA-00144-R00HB-07036PA.htm 5. Delaware: http://regulations.delaware.gov/AdminCode/title26/3000/3008.shtml#TopOfPage 6. Hawaii: https://www.capitol.hawaii.gov/session2015/bills/HB623_CD1_.htm 7. Illinois: http://programs.dsireusa.org/system/program/detail/584 8. Iowa: http://programs.dsireusa.org/system/program/detail/265 9. Maine: http://www.mainelegislature.org/legis/statutes/35-A/title35-Asec3210.html 10. Maryland: http://mgaleg.maryland.gov/2016RS/bills/hb/hb1106e.pdf 11. Massachusetts: https://malegislature.gov/Laws/SessionLaws/Acts/2008/Chapter169 12. Michigan: https://www.legislature.mi.gov/documents/2015-2016/publicact/pdf/2016-PA0342.pdf

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13. Minnesota: https://www.revisor.mn.gov/statutes/?id=216b.1691 14. Missouri: http://programs.dsireusa.org/system/program/detail/2622 15. Montana: http://leg.mt.gov/bills/mca_toc/69_3_20.htm 16. Nevada: https://www.leg.state.nv.us/Nrs/NRS-704.html#NRS704Sec7801 17. New Hampshire: http://www.gencourt.state.nh.us/bill_status/billText.aspx?id=957&txtFormat=html&sy=2 017 18. New Jersey: http://www.njleg.state.nj.us/2010/Bills/S2500/2036_R2.PDF 19. New Mexico: http://164.64.110.239/nmac/parts/title17/17.009.0572.htm 20. New York: http://programs.dsireusa.org/system/program/detail/93 21. North Carolina: https://www.ncleg.net/Sessions/2007/Bills/Senate/PDF/S3v6.pdf 22. Ohio: http://codes.ohio.gov/orc/4928.64 23. Oregon: https://olis.leg.state.or.us/liz/2016R1/Downloads/MeasureDocument/SB1547/Enrolled 24. Pennsylvania: http://programs.dsireusa.org/system/program/detail/262 25. Rhode Island: http://webserver.rilin.state.ri.us/BillText/BillText16/HouseText16/H7413A.pdf 26. Texas: http://www.statutes.legis.state.tx.us/Docs/UT/htm/UT.39.htm#39.904 27. Vermont: http://programs.dsireusa.org/system/program/detail/5786 28. Washington: http://apps.leg.wa.gov/RCW/default.aspx?cite=19.285 29. Wisconsin: http://docs.legis.wisconsin.gov/statutes/statutes/196/378

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APPENDIX A. FULL INVENTORY:

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B. INVENTORY PART 1 (State to Solar Carve-Out Customer Sited

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C. INVENTORY PART 2 (State to Solar Friendly Policies)

** Oregon’s multiplier only applies to certain utilities—this is discussed more in-depth in the paper

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