Distributed power generation and energy storage : potential effects of extending tax incentives

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DISTRIBUTED POWER GENERATION AND ENERGY STORAGE: POTENTIAL EFFECTS OF EXTENDING TAX INCENTIVES

by Omar 0. Sabir

B.S. Electrical Engineering with a minor in Project Management University of Maryland, College Park, 2011

Submitted to the Systems Design and Management Program in Partial Fulfillment of the Requirements for the Degree of

Master of Science in Engineering and Management

at the

Massachusetts Institute of Technology

June 2019

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.2 . .,.2 ..9 Francis O'Sullivan Director of Research, MIT Energy Initiative Thesis Supervisor

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DISTRIBUTED POWER GENERATION AND ENERGY STORAGE: POTENTIAL EFFECTS OF EXTENDING TAX INCENTIVES

by

Omar 0. Sabir

Submitted to the System Design and Management Program on May 21, 2019 in Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering and Management

Abstract

Solar PV penetration has been increasing rapidly in the U.S. in recent years. This growth can be attributed to multiple factors; one of which is financial incentives in the form of tax credit programs. One of the most effective tax credit programs in the U.S. is a federal tax program known as the Investment Tax Credit (ITC). The ITC program has been extended in recent years, and is currently set to expire in the early 2020s.

This work conducts scenario analysis to evaluate the effects extending the ITC will have on the Levelized Cost of Energy (LCOE) as opposed to allowing it to expire as it is currently set to. Particular attention is paid to the effects on LCOE as this helps evaluate whether solar PV will stay economically competitive compared to other sources of electricity and thus provides some guidance on the role of the ITC in accelerating the adoption of solar PV.

Thesis Supervisor: Francis O'Sullivan

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To my wife, Ghadeer, who sacrificed a lot to support me in chasing my dreams and making them become reality. You provide me the strength and the inspiration to keep going even when I struggle to see the light at the end of the tunnel.

To my father, for his continuous support throughout the years in every step I've taken to achieve my goals leading me to where I am today.

To my uncle Dr. Sami Habib who planted the seed of the dream of an MIT education. To my friend & colleague Malik Alyousef who changed my perception and made the dream seem touchable.

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Acknowledgements

Before proceeding onto this work, I would like to thank several individuals. First and foremost is my wife, Ghadeer, who has been supportive of me throughout the journey of an MIT graduate program. She has consistently uplifted my hopes and sense of self-worth when I needed it most. Next, I would like to thank Dr. Emre Gencer, a research scientist at the MIT Energy Initiative. He has taught me a great deal about how to approach the problem, how to think critically about it, and how to present it to an audience. His guidance, support, and enthusiasm for my work has been of great help and is much appreciated.

Thanks also goes to Dr. Francis O'Sullivan, for agreeing to serve as my advisor despite not knowing me too well. I can only hope that this thesis proves worthy of his trust.

I'm grateful to the SDM 2017 cohort who have become a second family to me and were very supportive throughout my journey during my time on the MIT campus.

Finally, I would like to thank the System Design & Management (SDM) program on all their support throughout the program.

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List of Figures

Figure 1-1 US. Electricity generation by energy source, from [22]...12

Figure 1-2 U S. Electricity generation from renewable energy sources, from [22]...13

Figure 1-3 Sources of 2018 US. electricity generation, from [22] ... 14

Figure 2-1 2016 Cost and Performance Summary Table for the Mid Cost Scenario (R&D + M a rket), fro m [2 6] ... 19

Figure 2-2 2018 ATB LCOE range by technology for 2016 based on R&D + Market financial assu m p tio ns, fro m [2 6] ... 2 0 Figure 3-1 Levels of Potential, copiedfrom [38]... 23

Figure 3-2 2018 A TB LCOE range by technology for 2016 based on R&D Only financial assum p tio ns, fro m [2 6] ... 4 0 Figure 3-3 Public support for expanding solar power, copied

from

[53]...41

Figure 6-1 Base Scenario for Utility Solar PV ... 52

Figure 6-2 Base Scenario for Commercial Solar PV ... 53

Figure 6-3 ITC Extension Scenario for Utility Solar P V... 54

Figure 6-4 ITC Extension Scenario for Commercial Solar PV... 55

Figure 6-5 ITC Termination Scenario for Utility Solar PV... 56

Figure 6-6 ITC Termination Scenario for Commercial Solar PV... 57

Figure A-0-1 Utility Scale Solar PV CAPEX ($/kW)...62

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List of Tables

Table 3-1 Technical Potential for Urban Utility PV by State, from [38]... 24

Table 3-2 Summary of the Most Important RE Federal Tax Incentives Programs... 25

Table 3-3 Samples of California's State and Local Incentives Programs for Solar PV... 31

Table 5-1 Current Solar ITC O utlook... 48

Table 5-2 ITC Extension Scenario... 49

Table 5-3 ITC Term ination Scenario... 49

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AC AEO ATB CAPEX CapRegMult CC CCS CF CoFinFactor CRF CSP CT DOE DSIRE EIA FCR FOM GCC GF GW GWh IGCC ITC kW kWh LCOE MIT MITei MW MWh NREL OCC OffSpurCost OnSpurCost O&M PC ProFinFactor PTC PV PVD R&D ReEDS RE

List of Acronyms and Initialisms

Alternating Current Annual Energy Outlook Annual Technology Baseline Capital Expenditures

Capital Regional Multiplier Combined Cycle

Carbon Capture and Storage Capacity Factor

Construction Finance Factor Capital Recovery Factor Concentrating Solar Power Combustion Turbine

U.S. Department of Energy

Database of State Incentives for Renewables and Efficiency

U.S. Energy Information Administration

Fixed Charge Rate

Fixed Operation and Maintenance Expenses Grid Connection Costs

Grid Feature Gigawatt Gigawatt-hour

Integrated Gasification Combined Cycle Investment Tax Credit

Kilowatt Kilowatt-hour

Levelized Cost of Energy

Massachusetts Institute of Technology MIT Energy Initiative

Megawatt Megawatt-hour

National Renewable Energy Laboratory Overnight Capital Costs

Offshore Spur Line Costs Onshore Spur Line Costs Operation & Maintenance Pulverized Coal

Project Finance Factor Production Tax Credit Photovoltaics

Present Value of Depreciation Research and Development

NREL's Regional Energy Deployment System Renewable Energy

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RPS Renewables Portfolio Standard

SDM System Design and Management

SEIA Solar Energy Industries Association

TES Thermal Energy Storage

TR Tax Rate

U.S. The United States

VOM Variable Operation and Maintenance Expenses

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Chapter 1: Introduction

The topic of this thesis is about the potential effects of extending existing renewable energy incentives; namely tax credit programs. This chapter lays out the motivation, scope, and contributions of the work, as well as specifying the structure of the rest of the thesis.

1.1 Renewable Energy Sources in Power Generation in the U.S. (Wind & Solar)

Energy sources in the U.S. Electricity sector have been sourced mainly from coal, petroleum, natural gas, nuclear, and renewable energy sources. Figure 1-1 below shows how each of those

sources have contributed to the overhll U.S. power generation and how those contributions evolved since the 1950s.

Figure 1-1 U.S. Electricity generation by energy source, from [22]

U.S. electricity generation by major energy source, 1950-2018 billion kilowatthours 4,500 4,000 3,500 3,000 2,500

2 petroleum and other

2,000 a renewables 2nuclear a natural gas 1,500 scoal 1,000 500 0 1950 19u 19O 70 1980 1990 2000 2010 Note: Electricity generation from utility-scale facilities.

Source: U. S. Energy Information Administration, Monthly Energy Review, Table 7.2a,

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Figure 1-1 shows the trend of the U.S. electricity generation by major energy source type over the past 68 years. It can be seen from this figure that the electricity generation from renewable energy has seen considerable growth in the last decade. Now, let's focus only on renewable energy sources throughout the same period as in the above graph since some particular sources have witnessed recent rapid growth.

Figure 1-2 U.S. Electricity generation from renewable energy sources, from 1221

U.S. electricity generation from renewable energy sources,

1950-2018

billion kilowatthours 750 700 650 600 550 500 450 400 350 300 250 200 150 100 50 1950 1960 1970 1980 1990 2000 2010

Note: Electricity generation from utility-scale facilities. Hydroelectric is conventional hydropower.

Source: U.S. Energy Information Administration, Monthly Energy Review, Table

solar Uwind ageothermal abiornass *hydroelectric

eil

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By examining the above graph, it can be seen that electricity generation from Wind has only

started picking up in the U.S. after the year 2000 and it has seen tremendous growth since then. Similarly, electricity generation from Solar has started going through rapid growth only after the year 2010. Now let's look at a snapshot of electricity generation sources for the most recent year,

2018.

Figure 1-3 Sources of 2018 U.S. electricity generation, from 1221

Sources

of

U.S.

electricity generation, 2018

Total = 4.18 trillion kilowatthours

renewables 17%

nuclear

19%

coal 27%

natural gas 35%

40! J~tUVR:IJUI I 10

Note: Electricity generation from utilty-scale facitie*.

Source: U.S. Energy Information Administration, Electric Power Monthly February 2019, preliminary data

eta

The above graph shows that in 2018 wind power accounted for 6% of the U.S. electricity generation while solar power accounted for only 1.6% of the U.S. electricity generation. This thesis seeks to address the ecosystem that enabled solar energy to grow rapidly as an electricity

wvi

6,

bomas 15%

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generation source and to examine certain aspects of this ecosystem, more specifically financial incentives.

1.2 Why Solar PV

Almost a decade ago, during my undergraduate studies, I remember viewing solar PV as a distant future whenever I encountered it within my classes as I was an Electrical Engineering

student. Even though I have been away from the Electricity industry for a number of years, I got withdrawn to solar PV after coming back to graduate school as I became curious about it and

found an interest in it when I got introduced to it during my graduate studies, almost a decade after my initial encounter. Solar PV is one of two types of solar technologies that dominate the solar energy field. The rapid growth in recent years led me to believe that the future of solar PV is going to make a huge impact on the current decomposition of electricity sources. The reasons behind such growth in solar PV deployment in recent years will be discussed in details in Chapter 3.

1.3 Research Questions

This work was guided by the following central research questions:

1. Is the LCOE for solar PV going to stay at current levels over the next 20 years?

2. What are the potential effects of extending tax credit programs on solar PV penetration?

1.4 Scope

This thesis primarily deals with the topic of existing financial incentives, mainly in the form of tax credit programs, that the U.S. government, both on federal level and on state level, has put in place to stimulate Renewable Energy generating assets penetration in general, and solar PV in

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particular. Additionally, this thesis will examine, through scenario analysis, the potential effects of extending such tax credit programs on the deployment of solar PV as opposed to letting it expire in the foreseeable future.

This thesis does not seek to directly tackle all of the growth contributing factors as well as challenges facing deployment of renewable energy generating assets. Analyzing all those factors and overcoming all of the challenges will require researchers, policymakers, industry partners, municipalities, and federal government to address. While this thesis discusses some of the broader factors, it specifically seeks to contribute findings that will hopefully shed some lights

on insights on the role of tax credit programs on the deployment of solar PV at this particular phase of its lifecycle.

1.5 Thesis Structure

Chapter 1 provides an introduction of the Distributed Renewable Energy space (in particular Solar & Wind) and it covers my personal motivations for choosing to focus on solar PV. Then it goes on to lay out the goals, structure, and contributions of this work. Chapter 2 provides an overview of the current landscape of solar PV and its growth in the past decade in the U.S. Then it goes on to explain why I focused on Utility-scale and Commercial Solar PV for this work. Chapter 3 explores the factors affecting and/or contributing to solar PV penetration over the past decade; one of which is financial incentives. Chapter 4 introduces the National Renewable Energy Laboratory (NREL)'s Annual Technology Baseline (ATB) and lays out its modeling methodology and the key assumptions that go into it. 0 explains the scenarios used in the

scenario analysis and the rationale behind choosing those scenarios and the general set up for the scenario analysis. Chapter 6 discusses the results of the scenario analysis, the interpretations and

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the significance of those results. Chapter 7 recaps the research findings, revisits the research questions, and discusses potential future work.

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Chapter 2: Assessment of current landscape & past growth of Solar

PV in the U.S.

2.1 How Solar PVfits into the larger RE landscape

Solar PV can be found in 3 different contexts/scales: (1) Utility scale, (2) Commercial, and (3) Residential. Each of those scales have different economics due to various factors; one of which is the difference in scale and therefore the effects of economies of scale come into play.

2.1.1 Utility-scale Solar PV

Solar PV at the utility scale has already reached parity in many places across the U.S. since it has become economically competitive with other sources of electricity. In 2016, for example, the

LCOE for Utility Solar PV in the U.S. ranged from 3 5-63 $/MWh compared to 59-122 $/MWh

for Natural Gas Combustion Turbine, 74-105 $/MWh for Pulverized Coal, 63 $/MWh for Nuclear and 76-219 $/MWh for Geothermal [26]. Utility Solar PV does, however, require a large amount of space and this introduces difficulty for some geographic locations. Figure 2-1 below shows a summary of the LCOE for various technologies as summarized in the 2018 ATB. In the table, the LCOE range is shown in the last two columns on the right, and this takes into consideration the 2016 market conditions including financial incentives programs that were in effect in 2016. Details on assumptions and calculations are covered in more details in Chapter 4.

By looking at the LCOE ranges for the various technologies, it becomes evident that Utility Solar

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Figure 2-1 2016 Cost and Performance Summary Table for the Mid Cost Scenario (R&D + Market), from [261 Dispatchable Coal PC IGCC CCS-30% CCS-90% Natural Gas CT CC Cc-ccs Nuclear Biopower Geothermal C$P with 10-hr TES Wind Land-based Offshore Photovdltaic Utility Commercial 53% 53: 53% 53% 8% 56% 56% N 92% 56% 80% 44% 85% 85% 85% 30% 87% 87% 92% ' 56% 90% 60% $ 3,896 $ 4,80 S 5, 2 $ 898 $ 1,050 $2,192 $ 6,070 $3,942 $5,100 $ 7,842 S 3,896 $ 4.180 $5 ,392 $ 5,962 $ 898 S1,050 $ 2,192 $ 6,070 $ 4,070 $13,601 $7,842 11% 48% $ 1,523 $ 1,744 31% 51% $3,776 $ ,152 15% 27% S 1,774 $ 1,774 12% 20% $ 2,591 $ 2,591 2.1.2 Commercial Solar PV

Solar PV at the commercial scale has seen a wide spread among large corporations as part of corporate sustainability programs among other initiatives to become more green or socially responsible corporations. In its annual report named "Solar Means Business 2017", the Solar Energy Industries Association, also known as SEIA, indicated that they were "tracking 2,562 MW of commercial projects across nearly 7,400 project sites and representing more than 4,000 companies". [34] $19 $ 19 $21 $ 25 $28 $ 19 $22 $7 $39 $0 $0 $0 so $0 $ 0 $33 $54 $69 $80 $ 12 $10 $33 $99 $53 $145 $ 67 $51 $131 $ 14 $18 $5 $8 $ 10 $7 $2 $ 317 34 $0 $0 $0 s0 $ 74 $ 84 $102 $ 117 $5S9 $30 $49 $63 $ 107 $76 $95 $22 $ 69 $ 105 $ 118 $ 145 $ 166 $ 122 $36 $61 $63 $109 $ 219 $ 128 $ 166 $241 $63 $113

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2.1.3 Residential Solar PV

Solar PV at the residential level is still arguably at an expensive level and is most likely not affordable at the masses level. It's still not economically competitive with other technologies as can be illustrated in Figure 2-2 below:

Figure 2-2 2018 ATB LCOE range by technology for 2016 based on R&D + Market financial assumptions, from [261

$400 _

- Range in ATB

- Most representative value for recent or near-future plants S300 ~- -- - -- -" $200 0 $1)00~~~ $50 -.-- -- ~- ~

SO

.. .... .. ... ... ... ... ... T': $0

-Land Offshore Solar - Solar Solar Solar -CSF Geo - Hydra- Coal Coal- CCS Gas -CC Gas- CCS Nudea Blo

based Wind UPV (AC) Dist Corn Dist Res 10TES thermal power power

Wind PV (AC) PV (AC)

2018 ATB LCOE range by technology for 2016 based on R&D + Market financial assumptions Source: National Renewable Energy Laboratory Annual Technology Baseline (2018), http://atb.nrel.gov

Looking at Figure 2-2 above, the 2016 LCOE for Residential Solar PV in the U.S. ranged from

92-153 $/MWh. This range takes into account the market conditions and the tax credits that were

in effect. In comparison, the LCOE, for the same year under the same market conditions, for

Utility Solar PV in the U.S. ranged from 35-63 $/MWh and 69-113 $/MWh for Commercial

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conditions, was 59-122 $/MWh for Natural Gas Combustion Turbine, 74-105 $/MWh for Pulverized Coal, 63 $/MWh for Nuclear and 76-219 $/MWh for Geothermal [26].

2.2 Focusing on Utility & Commercial Solar PV only

Residential Solar PV economics varies a lot from one state to another, and it's still relatively expensive as evident from the data presented in previous sections, so it's still not affordable by the general public. On the other hand, Utility Solar PV is economically competitive and has a great potential due to its scale. Commercial Solar PV, however, is relatively competitive and an

ITC extension could make a big difference in stimulating its growth. Therefore, this work will

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Chapter 3: Factors affecting/contributing to Solar Penetration

(Literature Review)

This chapter looks into the factors that have affected and continue to affect the penetration of solar energy generation assets, with a focus on Solar Photovoltaics (PV). To provide a big picture perspective on the renewable energy deployment in general, in its 2012 Energy

Technology Perspective report, the International Energy Agency (lEA) estimated that 57% of the

world's electricity will be generated from renewables by 2050 [1]. Five years later, the 2017 Energy Technology Perspective report estimated that 74% of the world's electricity will need to be generated from renewables by 2060 in order to achieve the more ambitious decarbonization goals of the Paris Agreement [2]. The purpose of highlighting those global targets is to provide an indicator of where the global power sector is intended to head, and that has been coupled with policy support in many countries around the globe. Since the focus of this work is on Solar PV,

light is shed on the Solar PV penetration in light of those global targets mentioned earlier. On a global scale, the National Renewable Energy Laboratory (NREL) report titled "Q4 2017/QI

2018 Solar Industry Update" shows that in 2017 alone a record of 98 GW-DC in solar PV

capacity was added globally, bringing the total global solar PV capacity to 415 GW-DC [4]. From a local perspective, the same NREL report shows that the U.S. Solar PV installations had an addition of 10.6 GW-DC in 2017 leading to a cumulative solar PV capacity of 51.6 GW. From the literature review, five main contributing factors have been identified and they will be covered in this chapter. Those factors are: geographical location, financial incentives, policy and mandates, technology evolution, and consumers perceptions.

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3.1 Geographical Location

The geographical location affects the potential for solar PV power generation. According to an NREL report [38], there are four levels of potentials for a certain renewable energy technology, solar PV for the purpose of this work, that will help determine its potential for power generation: resource, technical, economic, and market as illustrated below in Figure 3-1:

Figure 3-1 Levels of Potential, copied from [381

Key Assumptions

Potential

Resource potential shows how much solar resources are available in a geographic location. Throughout the U.S., the maximum variation in solar resource levels is estimated to be a factor of 2 [39].What technical potential provides is the maximum achievable energy generation given the characteristics of the system performance, any environmental constraints, topographic

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estimate of potential solar PV development and energy generation within a geographic location

[38]. For example, Table 3-1 below shows the resulting technical potential for Urban Utility PV by State:

Table 3-1 Technical Potential for Urban Utility PV by State, from [38]

Table 2. Total Estimated Technical Potential for Urban Utility-Scale Photovoltaics by Statea

Alabama 426 20 35,8$1 Montana 127 6 11,371

Alaska 2 <1 166 Nebraska 142 7 12,954

Argona 0096 53 121,306 Nevada 225 11 2494

Artaosas 332 16 28,"1 New Hamstne 49 2 3J90

Csdoraa 21321 111 246, New Jersey 527 25 44,307

Colorado 399 19 43,471 New Mex o 646 31 71,356

Connect' ut l01 5 7,717 New Vort 683 33 52,8031

[klaware 190 9 14,856 North Carohna 789 38 69,346

D1ntril of Columbia <1 <1 8 North Dakota $7 3 4,871

florida 530 40 72,787 Oh1, 190 57 26,496

Gcorpa 506 24 43,167 Oklahoma 534 26 50,041j

ittwan 35 2 3,725 Oregon 271 13 2,783

Idaho 251 12 23,195 Penylvana 754 36 56,162

lkMoos 1,325 64 103,552 Rhode island 24 1 1ga,

Indiana 1,274 61 99,815 Soulh Carolna 398 19 33535

Iowa 324 16 27,092 Soulh Dakoa 51 7 4,574

Kansas 31 15 31,706 tennessee 596 29 50243

%#ntutky 339 16 26,515 Texas 3,214 154 294,684

Wuisiaaa 62$ 32 $5,66 Utah 293 14 30,442

Mame 40 2 3,216 Vermont 22 1 1,632

Maryland 379 1 28,551 Sft"*na 326 16 7,451

Massat usetts 228 11 17,470 Washington 402 19 316X

Mkhtan 699 34 50,245 West Virtvsia 42 2 3,024

Mnnesota 419 20 33,370 WIsconsi 726 1 54,91

Misssippi 318 15 , 26- Wyoming 75 4 7,232

Missouri 377 15 30,549 _ l___ US. total 25,369 1,212 212311694

a Non-excluded land was assumed to be available to support development of more than one

technology.

Table 3-1 above shows that there are significant differences in the technical potential for Urban Utility Solar PV between the individual states. Looking at the numbers in the table, it's worth noting that California and Texas have the most technical potential for Urban Utility Solar PV compared to the rest of the states.

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3.2 Financial Incentives

Renewable Energy financial incentives in the U.S. are found on both the federal level and the state level. Some illustrations will be shown for both federal incentive programs and state-level incentive programs.

3.2.1 Federal Incentive Programs

In this section, a summary of the most important federal tax incentives programs for renewable energy (with a focus on programs applicable to solar PV) is provided below in Table 3-2:

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Allows the tax credit to be taken based on the amount invested rather than electricity produced - Solar PV - Other technologies

30% for Solar The expiration

PV dates are based

on when construction begins. For Solar PV: 30% prior to 12/31/2019, 26% prior to 12/31/2020, 22% prior to 12/31/2021, then 10%.

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Under the federal Modified Accelerated Cost-Recovery System (MACRS), businesses may recover investments in certain property through depreciation deductions. The MACRS establishes a set of class lives for various types of property, All ITC-eligible technologies as well as large wind projects (essentially all renewables)

Depends on tax No expiration

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ranging from . three to 50 years, over which the property may be depreciated. A. number of renewable energy technologies are classified as five-year property. Bonus Depreciation has been sporadically available at different levels -during different years. Most recently, The Tax Cuts and Jobs Act of 2017 increased bonus

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Eligibility of - Solar PV 100% of subsidy No expiration

taxpayers to - Other

I exclude from technologies

gross income any subsidy provided, either directly or indirectly, by public utilities for the purchase or installation of an energy

conservation measure for a dwelling unit.

It is worth noting that the ITC was set to decline at the end of 2016. More specifically, the solar

ITC was set to decline from 3 0% to 10% for both Utility-scale and Commercial projects, and

from 30% to 0% for Residential projects after December 31, 2016. These solar ITC schedules reflect a "placed in service" requirement as opposed to the commenced-construction provision for the wind PTC. The Consolidated Appropriations Act of 2016 extended the ITC deadline by

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five years from its prior scheduled expiration date, but included ramp downs in tax credit value during the latter years of the five-year period. The act, also, replaced the "placed in service" provision with "commenced-construction" provision for Utility-scale and Commercial solar PV [20].

The ITC has had a great impact on accelerating the deployment of solar PV in the U.S., but it is set to expire soon as previously mentioned. Therefore, the scenario analysis in this work will focus on examining different future scenarios for the ITC and how extending the ITC could affect the LCOE in the future.

3.2.2 State Incentive Programs

On the state and local level, it is a more complicated process to keep an exhaustive list that has every incentive program in each state. For the purpose of this work, California has been selected as a sample state to be examined for some of its incentives programs for solar PV. An important point to mention here is that the individual cities within each state have different incentives and the table below shows some of those incentives as an illustration as opposed to a providing a comprehensive list of all incentives within California as that is not the intent of this work: Table 3-3 Samples of California's State and Local Incentives Programs for Solar PV

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low-income residential, non-profit, or multi-unit residential. Sacramento $300 Municipal Utility District (SMUD) offers an incentive of $300 to residential customers who install grid-connected photovoltaic (PV) systems. ' All systems must be permitted and

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installed by B, C-10, or C-46 contractors. The incentive will be adjusted based on expected system performance, which is affected by factors such as inverter efficiency, orientation, tilt and shading.

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AB 389 of 2017 100% 7/1/2030

created an exemption from the sales and use tax for "qualified tangible personal

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property purchased for use by a qualified person to be used primarily in the generation or production, or storage and distribution, of electric power." The exemption also applies to contractors who purchase the equipment in the service of a contract with a qualified person. California

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Table 3-3 above shows an example of how the individual states have come up with creative incentives programs for solar PV, and such incentives programs have been an important contributor for the rapid growth in solar PV deployment in recent years.

3.3 Policy & Mandates (Renewables Portfolio Standard for Individual States)

In an NREL report named "The Effectiveness of State-Level Policies on Solar Market

Development in Different State Contexts", it has been concluded that about 70% of the variation among states in new solar PV capacity is explained by implementation of interconnection

standards and policy related to the valuation of excess electricity such as net metering, along with indicators of long-term government support for a solar PV market (e.g., renewable portfolio

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Since this section is dedicated for policy and mandates as a contributing factor to the deployment of solar PV, an illustrative example is provided for the Renewables Portfolio Standard to provide a general picture of its contributions to the deployment of solar PV. California's Renewables Portfolio Standard (RPS) was originally established by legislation enacted in 2002. Subsequent amendments to the law have resulted in a requirement for California's electric utilities to have

50% of their retail sales derived from eligible renewable energy resources in 2030 and all

subsequent years. Solar PV is one of the eligible renewable energy resources among other technologies. The law established interim targets for the utilities. In September 2018, the overall requirement was increased from 50% to 60% by 2030. The legislation also adopted an additional goal of 100% of all retail sales by 2045 come from renewable energy resources and zero-carbon resources [52].

3.4 Technology Evolution and Declining Costs

The speed and rapid growth in solar PV deployment in recent years along with their steeply declining costs "have surprised even the most optimistic industry players and observers". "Ahead of projections and despite lingering perceptions to the contrary", solar PV have become

competitive with conventional energy generation technologies with and without subsidies [4]. To illustrate such cost comparisons, the 2016 subsidized LCOE ranges for the various technologies can be seen in Figure 2-2 which was presented in section 2.1.3. and the 2016 unsubsidized

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Figure 3-2 2018 ATB LCOE range by technology for 2016 based on R&D Only financial assumptions, from 1261 ,$400I $350 $250 S200 0 UO 2 Range in AT8

- Most represertative value for recent or

near-future plants

$50

--Land- Offhore Solar- Solar- WoIar- 15 - (j eo - ydr o- Cnal CoaI-CCS Ga .-CC G ( -NCd ar in

-bafad Wind 1iPV (AC) I)t Conm it R" 101s thormal pawor ptw

Wind PV (AQ PV(AQ

2018 ATB LCOE range by technology for 2016 based on R&D financial assumptions

Source: National Renewable Energy Laboratory Annual Technology Baseline (2018), http://atb.nreLgov

As can be seen from Figure 3-2 above, the LCOE for solar PV have become competitive with conventional energy generation technologies even without subsidies especially at the Utility-scale (represented on the graph as Solar - UPV).

3.5 Customer/Consumer Perceptions

In recent years, there has been a strong public support for expanding Solar power as the public become more aware abut climate change concerns. This can be seen in the results of a study done

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Figure 3-3 Public support for expanding solar power, copied from [53]

Strong

public support for expanding wind, solar power

%

of

U.S. adults who say they favor or oppose expanding each energy source

Moppose a Favor

Solar panel farms 9 89

Wind turbine farms Offshore drilling Nuclear power plants Fracking Coal mining 14 52 54 53 57 I 83 45 43 42 41

PEW RESEARCH CENTER

The results shown above in Figure 3-3 is an illustration of the public support for solar power, and this can also be evident from the rapid growth in solar PV deployment in recent years.

Focus on tax credit programs

This work will focus on examining federal tax credit incentive programs (namely the ITC program) and the effects of varying those incentives through scenario analysis as explained in more details throughout Chapters 4 & 5.

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Chapter 4: 2018 ATB Modeling Methodology

The U.S. National Renewable Energy Laboratory (NREL) provides each year a "robust set of modeling input assumptions for energy technologies" under the name of Annual Technology Baseline (ATB). The goal of the ATB is to "help inform electric sector analysis in the U.S" [7]. The reason ATB has a full chapter in this thesis is that it's the basis for the scenario analysis covered in Chapter 5, and it is, therefore, important to cover the 2018 ATB modeling

methodology to lay the ground for the scenario analysis that will follow.

4.1 Critical Assumptions used for future Projections * The base year is 2016.

" All operations and maintenance costs for wind and solar PV technologies are assumed to

have fallen under the Fixed O&M category.

" Cost recovery period (Technical Life) is 30 years for solar PV.

" Two distinct sets of financial assumptions (project finance structures) are available in the

ATB: R&D Only Financial Assumptions and R&D + Market Financial Assumptions.

" While the tax rate has been updated to include the changes in corporate taxes in the R&D + Market case, the federal/state blended tax rate is not assumed to vary by technology; in

practice, depreciation schedules vary by technology based on the tax code. * Current policies and incentives are modeled according to existing law.

" The LCOE values presented in ATB represent busbar costs at the plant gate; regional

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operation costs are not included. Effects of taxes, tax credits, and tariffs are not included in the R&D Only case but are included in the R&D + Market case.

The rest of assumptions can be accessed on the full NREL 2018 ATB [27].

4.2 Formulas Used in the A TB model (variables definitions, inputs, outputs, formulas)

The Levelized Cost of Energy (LCOE) is a measure used for comparing the costs of producing electricity from different sources and technologies and is measured in $/MWh. LCOE is affected

by various factors that are summed up in the following formulas:

Equation 4-1

1000 x (FCR x CAPEX + FOM)

LCOE = + VOM + FUEL

8760 x CF Where:

LCOE is Levelized Cost of Energy [$/MWh]

FCR is Fixed Charge Rate

CAPEX is Capital Expenditures [$/kW]

FOM is Fixed Operating and Maintenance Expenses [$/kW-year]

CF is Capacity Factor [%]

VOM is Variable Operation and Maintenance Expenses [$/MWh]

FUEL is Fuel Costs [$/MWh]

Equation 4-2

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CRF is Capital Recovery Factor [%]

ProFinFactor is Project Finance Factor

Equation 4-3

ProFinFactor = 1 - TR x PVD

1 - TR

Where:

TR is Tax Rate [%]

PVD is Present Value of Depreciation

Equation 4-4

CAPEX = CoFinFactor x (OCC x CapRegMult + GCC)

Where:

CoFinFactor is Construction Finance Factor

OCC is Overnight Capital Costs [$/kW]

CapRegMult is Capital Regional Multiplier

GCC is Grid Connection Costs [$/kW]

Equation 4-5

GCC = GF + OnSpurCost + OffSpurCost

Where:

GF is Grid Feature [$/kW]

OnSpurCost is Onshore Spur Line Costs [$/kW] OffSpurCost is Offshore Spur Line Costs [$/kW]

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It is important to mention that while the above formulas are used for calculating the LCOE for various technologies, some of the variables are not applicable to solar PV and are therefore assigned the value 0. It's also important to highlight that the following variables are inputs to the model: e FOM " Fuel e VOM * CF " CRF * TR " PVD " CoFinFactor " OCC " CapRegMult " GF " OnSpurCost " OffSpurCost

More specifically, inputs for Solar PV were sourced from various sources. For instance, CAPEX for 2016 were adopted from Barbos6 and Dargouth (2017) [28] and Bolinger et al. (2017) [29];

CAPEX for 2017 were adopted from on Fu et al. (2017) [30]. Capacity factors were calculated

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4.3 Future Technology Cost Scenarios

The ATB considers three different future scenarios for each technology. Those scenarios are: a. Constant:

Base Year (or near-term estimates of projects under construction) equivalent through

2050 maintains current relative technology cost differences and assumes no further

advancement in R&D [27].

b. Mid:

Technology advances through continued industry growth, public and private R&D investments, and market conditions relative to current levels that may be characterized as

likely," or " not surprising" [27]. c. Low:

Technology advances that may occur with breakthroughs, increased public and private R&D investments, and/or other market conditions that lead to cost and performance levels that may be characterized as the " limit of surprise," but not necessarily the absolute low bound [27].

4.4 Project Finance Structures

a. R&D Only:

This scenario allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs [27].

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This scenario retains the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and technology-specific tariffs [27]. Some of the highlights are:

i. For wind and solar plants that are eligible to receive the production tax credit (PTC) or investment tax credit (ITC) at present, debt fractions tend to be lower than other electricity generation technologies because tax equity investors are significant project sponsors [27].

ii. This scenario reflects debt interest and return on equity rates observed in today's market, a debt fraction of 40%, and the effect of the PTC or ITC for wind and solar LCOE estimates only [27].

c. ReEDS

ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology

cost scenario [27].

For the purpose of this work, only project finance structure b (R&D Only + Market) is

considered since the purpose is to examine the effects of different scenarios of market conditions (tax credit incentives).

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Chapter

5:

Scenario Analysis

For the purpose of this work, two sample cities have been chosen to carry out this analysis since the geographic location affects a number of factors that contribute to the LCOE. The cities

chosen for this analysis are Los Angeles and Daggett, both in California. The reasons for choosing those cities are (i) availability of data through the 2018 NREL ATB, and (ii) both are sample cities from California, a target state that has been surveyed for existing Tax Credit incentives on the state level as covered in section 3.2.2.

The financial incentives scenarios are considered for both Utility Solar PV and Commercial Solar PV. The modeling methodology is based on the 2018 ATB which is laid out in Chapter 4. From "Future Technology Cost" perspective, all three scenarios (Constant, Mid, and Low) defined in section 4.3 are considered for each of the financial incentives scenarios. To lay the ground for the considered scenarios, Table 5-1 below shows the current policy outlook for the solar ITC incentive:

Table 5-1 Current Solar ITC Outlook

Solar ITC 2017 2018 2019 2020 2021 2022 2023 2024 Future

Utility 30% 30% 3Q% 30% 30% 26% 22% 10% 10%

Commercial 30% 30% 30% 30% 30% 26% 22% 10% 10%

Source: https://www.irs.gov/pub/irs-pdf/i3468.pdf

Three scenarios were chosen: a base scenario, an optimistic scenario, and a pessimistic scenario. The definition of each scenario is explained below:

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5.1 Normal/Base Scenario

For this scenario, the base case is reproduced which assumes that current ITC policy will not change and will be as it is as of March 2019 which is laid out in Table 5-1 above. This case is considered as a "more likely scenario" and it provides the baseline for the analysis since it considers the future outlook for the resulting LCOE of solar PV under current ITC policies.

5.2 ITC Extension (Optimistic) Scenario

For this scenario, the case where the ITC is extended until 2030 and then drops to 10% is considered and this is looked at as an optimistic case. The scenario is illustrated in Table 5-2 below:

Table 5-2 ITC Extension Scenario

Solar ITC 2017 2018 2019 2020 2021 2030 2031 2032 Future

Utility 30% 30% 30% 30% 30% 30% 26% 22% 10%

Commercial 30% 30% 30% 30% 30% 30% 26% 22% 10%

5.3 ITC Termination (Pessimistic) Scenario

For this scenario, the case where ITC is terminated and taken down to 0% instead of 10% from 2024 onward is adopted. This case provides a lower bound for future state of ITC. The scenario is shown in Table 5-3 below:

Table 5-3 ITC Termination Scenario

Solar ITC 2017 2018 2019 2020 2021 2022 2023 2024 Future

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Commercial 30% 30% 30% 30% 30% 26% 22% 0% 0%

The reasoning for the choice of such a scenario is looking at worst-case scenario and how much impact it could have on the LCOE. Also, drawing a best case scenario and a worst case scenario provides boundaries to work within and could lead to a better picture of the effects of changes in the structure of tax credit incentives on the future deployment of solar PV on both Utility and

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Chapter 6: Results

Over the course of Chapter 4 and 0, the methodology of modeling (ATB) was covered to lay the ground for the scenario analysis. Then, the scenarios were defined and explained with the reasoning for each of them and why they were chosen. This chapter presents the results and puts them in perspective.

6.1 Base Scenario Results

It is worth noting that the general shape of the LCOE projection curves largely resemble the curves of the CAPEX projections which are shown in Figure A-0-1, for Utility Solar PV, and in Figure A-0-2, for Commercial Solar PV, both in Appendix A. The main reason for such

resemblance is that CAPEX is a major contributor and the largest component of LCOE. Having said that, there are differences between the curves for the individual scenarios which are

attributed to scenario assumptions and the market conditions including tax credits such as the

ITC.

Another important thing to note is the introduction of tariffs for the years 2018-2021 to represent Section 201 proclamation implementing a tariff on imported PV modules and cells [32], [33]. The effects of the introduction of this tariff is the evident rise of LCOE from 2018-2020 which can be seen on all the LCOE projections throughout this work for both Utility Solar PV & Commercial Solar PV.

6.1.1 Utility Solar PV

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Figure 6-1 Base Scenario for Utility Solar PV

Projections- Utility-Scale Solar PV Levelized Cost of Energy

($/MWh)

$50

$40 "

$30 % ~ .... tiltyn. Lsne s.i a- L...wn Ut inVeo mAel amuman aadm sm

$40 ~ ~ ~ ~ Utlt PVMMW , DaggetM OWt, CA WMM - Mid, UtiWity PV -#UW Daggett, CA WAM - Monstantft

In0 Figure 6-1 above, each cityO isOM represented by three differen cures aorsodigt h

$20 $10 $0

t 0 a' D C 0 M N r Clv n tz r_ W0 M 0 f N en 1; in- u O r_ CO M~ 0 V-.4 r* en '- V1 o 00 W ' a%

C4 NN N~ N~ N1 r- N1 N1 N1 C14N N N Nq ~ N. r-4 " -N1 N~ N1 N N N N N q C1NN 4

.e..Utility PV- Los Angeles Low -Utility PV, Los Angele~s -Mid

- Utility PV -Los Angeles Constant Utility PV- Daggett, CA. Low

-Uti lity PV -Daggett, CA -Mid a-aUtility PV -Oaggett, CA -Constant

In Figure 6-1 above, each city is represented by three different curves corresponding to the three future technology cost scenarios (Constant, Mid, Low) which represent different assumptions as defined in section 4.3. Focusing on the curve for the Mid case, which is the most likely case, the LCOE cu'rve initially goes down from 2016 to 2017, then it goes up due to the tariffs mentioned earlier. Then it starts pointing downward until 2023 when the ITC starts stepping down causing the LCOE to go up, and then it starts trending downward all the way through.

6.1.2 Commercial Solar PV

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Figure 6-2 Base Scenario for Commercial Solar PV

Projections- Commercial Solar PV Levelized Cost of Energy

($/MWh)

S100 $80 $60 $40 $20 $0 m w - m i n inA m WMW - - tm- -w

4NOWW rl~ ~' OM 40"W" 40NIN 4"o" 40"WM ANNN OH 0 NO M' 4;fWW 4"WONOW 001Wf P

(N N (N "N "N N e'1 FN "N CN "N IN CN rJ rN "N rN f4 NI r4 (N N fN CN N tN N I CN r'4 ?N fN

* ** Comm PV -Los Angeles - Low -Comm PV -Los Angeles -Mid

-. Comm PV - Los Angeles -Constant * * * -- Comm PV -Daggett, CA - Low

-Comm PV - Daggett, CA -Mid -- Comm PV -Daggett, CA - Constant

Figure 6-2 above tells a similar story to Figure 6-1 as it follows a similar trajectory but with a higher range for LCOE. Focusing on the curve for the Mid case, the most likely case, the

LCOE curve initially goes down from 2016 to 2017, then it goes up due to the tariffs

explained earlier. Then it starts pointing downward until 2023 when the ITC starts stepping down and thus causing the LCOE to go slightly up, and then it starts trending downward all the way through.

6.2 ITC Extension (Optimistic) Scenario Results

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Figure 6-3 ITC Extension Scenario for Utility Solar PV

($/MWh)

$50

$40$0

* * * # * 9 Utility PV,. Los Angeles - Low Utility PV -Los Angeles- Mid Utility PV- Los Angeles -Constant .... Utility PV Daggett, CA - Low

Utility PV - Daggett, CA - Mid U tility PV - Daggett, CA - Constant

Focusing on the Mid case curve in Figure 6-3 above, which is the most likely case, it can be seen that the LCOE curve initially goes down from 2016 to 2017, then it goes up due to the tariffs as previously mentioned with the base case scenario. Then it starts pointing

downward until 2030 when the ITC starts stepping down causing the LCOE to go up until

2033 where the ITC flattens at 10%, and then it starts trending downward all the way

through 2050.

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Figure 6-4 ITC Extension Scenario for Commercial Solar PV

($/MWh) $100 $80 $40 $20 $0 ?A4~' '- N N r4 N N - CN " (N M M rn M~ M rnMa aL N e1 N N N N N CN N N4 N eN CN CN CN I eN N (N f4 (N fN N N4 rN N (N N-* C, NI N- N fN C r4

Comm PV -Los Angeles -Low Comm PV - Los Angeles -Mid

Comm PV -Los Angeles -Constant Comm PV -Daggett, CA -Low

- Comm PV -Daggett, CA -Mid - Comm PV -Daggett, CA -Constant

Figure 6-4 above tells a similar story to that of Figure 6-3 as it follows a similar trajectory but with different numbers. Focusing on the Mid case curve, which is the most likely case, the LCOE curve initially goes down from 2016 to 2017, then it goes up due to the Section 201 tariffs mentioned previously. Then it starts pointing downward until 2030 when the ITC starts stepping down causing the LCOE to go up until 2033 where the ITC flattens at

10%, and then it starts trending slightly downward all the way through.

6.3 ITC Termination (Pessimistic) Scenario Results

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Figure 6-5 ITC Termination Scenario for Utility Solar PV

($/MWh)

$50 $40 $30 $10 $0 111 4 O- N N r N N e n e e n e n e N N N r C11 N N N N N N N N NI N N- N N NN NI N- N- CN r_ N N

'..- Utility PV Los Angeles Low - Utility PV -Los Angeles- Mid

- Utility PV Los Angeles Constant - - - - * -Utility PV -Daggett, CA -Low

Utility PV -Daggett, CA -Mid - Utility PV- Daggett, CA- Constant

Focusing on the Mid case curve in Figure 6-5 above, which is the most likely case, the

LCOE curve initially goes down from 2016 to 2017, then it goes up due to the tariffs as

previously mentioned in the previous scenarios. Then it starts pointing downward until

2023 when the ITC starts stepping down causing the LCOE to go up sharply until 2024

where the ITC flattens at 0%, and then the curve starts trending downward all the way through.

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Figure 6-6 ITC Termination Scenario for Commercial Solar PV

($/MWh) $100 $40 $20 $0 Wo r- 00 Mn o .1 N, MO rr V)0 Nl 00 M~ 0 v-t M trL O TN 00 C C N Mi O t V1 O N- 00 M 0 r- "V4 r.4 N -N 11 N ~ N q N N N Nq Nq N Cm M MO MO MO MO C M C COC N N- N1 N N1 N4 N N, NN N N, N N* (N f14 N1 N N N' N4 N- N~ N N r4 N' Nq N4 NN4 N IN ?N N1

Comm PV -Los Angeles -Low ame Comm PV -Los Angeles -Mid Comm PV -Los Angeles -Constant - o* Comm PV - Daggett, CA -Low

- Comm PV - Daggett, CA -Mid - Comm PV -Daggett, CA - Constant

Figure 6-6 above tells a similar story to that of Figure 6-5 as it follows a similar trajectory

but with a higher LCOE range. Focusing on the Mid case curve, which is the most likely

case, the LCOE curve initially goes down from 2016 to 2017, then it goes up due to the

tariffs mentioned previously. Then it starts pointing downward until 2023 when the ITC

starts stepping down causing the LCOE to go up sharply until 2024 where the ITC flattens

at 0%, and then it starts trending downward all the way through.

6.4 Summary

Table 6-1 below shows a summary for the resulting LCOE for the Mid case in each of the three scenarios at the years 2016, 2030, and 2050 for both Utility Solar PV and Commercial Solar PV. It is worth mentioning that the Mid case is the case mainly looked at since it is the most likely case whereas the Constant and Low cases are more on the extreme side to provide boundaries. More details on the assumptions for each case are covered in section 4.3.

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Table 6-1 A Summary of resulting LCOE for the Mid case in each ITC Scenario

Looking at the results of each of the three scenarios for both Utility and Commercial Solar PV in addition to Table 6-1 above which summarizes the LCOE for the individual technologies in each of the sample cities in the years 2016, 2030, and 2050, it becomes evident that extending the tax credit program (ITC) will not have much direct effect in the long run (2050) on the LCOE. However, there seems to be a great difference in LCOE on the horizon of 2030 which will help accelerate the deployment of both Utility and Commercial Solar PV for the period starting from the current ITC expiration date until the extended one, 2030 in the optimistic scenario considered in this study. Higher deployment is likely to enrich the industry and lead to further resources funneled into R&D leading to improvement in the solar PV technologies and thus further reduction in future LCOE by either increasing efficiency or decreasing the cost of ownership.

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Chapter 7: Conclusions

This chapter reviews the contributions of this research, discusses its limitations, and plots a course for future work.

7.1 Research Questions and Contributions

As first stated in Section 1.3, this work was guided by the two central research questions. Those research questions are revisited and answered here.

7.1.1 Is the LCOE for Solar PV going to stay at current levels over the next

20 years?

From the scenario analysis conducted in this research, Table 6-1 in Chapter 6 shows that the LCOE for both Commercial and Utility Solar PV will decrease throughout the time horizon of the study which is more than 20 years regardless of whether the ITC is extended or not. For the base scenario, without extending or terminating the ITC, LCOE is projected to drop by an estimate of 37% for Utility Solar PV and 42% for Commercial Solar PV from the base year (2016) until 2030 and it is expected to drop by an estimate of 49% for Utility

Solar PV and 50% for Commercial Solar PV from the base year (2016) until 2050. In the pessimistic scenario where the ITC is terminated, LCOE is projected to drop by an estimate of 30% for Utility Solar PV and 35% for Commercial Solar PV from the base year (2016) until 2030 and it is expected to drop by an estimate of 44% for Utility Solar PV and 45%

for Commercial Solar PV from the base year (2016) until 2050. It is important to note that this analysis is sensitive to the assumptions that went into the modeling which were

Distributed power generation and energy storage : potential effects of extending tax incentives

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7 2019

LIBRARIES

DISCLAIMER NOTICE

Abstract

Acknowledgements

Table of Contents

List of Figures

from

List of Tables

List of Acronyms and Initialisms

Chapter 1: Introduction

1.1 Renewable Energy Sources in Power Generation in the U.S. (Wind & Solar)

U.S. electricity generation from renewable energy sources,

1950-2018

eil

Sources

of

U.S.

electricity generation, 2018

renewables 17%

nuclear

19%

coal 27%

natural gas 35%

eta

6,

Chapter 2: Assessment of current landscape & past growth of Solar

PV in the U.S.

SO

Chapter 3: Factors affecting/contributing to Solar Penetration

(Literature Review)

Key Assumptions

Potential

3.3 Policy & Mandates (Renewables Portfolio Standard for Individual States)

Strong

public support for expanding wind, solar power

of

U.S. adults who say they favor or oppose expanding each energy source

Focus on tax credit programs

Chapter 4: 2018 ATB Modeling Methodology

Chapter

5:

Scenario Analysis

Chapter 6: Results

($/MWh)

6.2 ITC Extension (Optimistic) Scenario Results

($/MWh)

Chapter 7: Conclusions

7.1 Research Questions and Contributions