Office of Technology, Policy, and Strategy 

Space-Based Solar 

Power 

Erica Rodgers, Ellen Gertsen, Jordan Sotudeh, Carie Mullins, 

Amanda Hernandez, Hanh Nguyen Le, Phil Smith, and 

Nikolai Joseph 

Reviewer(s): A.C. Charania, Tom Colvin, and Roger Meyers 

January 11, 2024

Report ID 20230018600

NASA Headquarters 

300 E Street SW 

Washington, DC 20024 

This report is intended for informational purposes only, and does not indicate a commitment or intention, 

implied or otherwise, by the government to engage in any activity or to enter into any agreement, contract or 

other obligation. The inclusion of information in this report does not constitute endorsement of any entity, or 

any products, services, technologies, activities, or Agency policy. The information contained in this report 

reflects solely the views and opinions of the authors. 
For more information on the NASA Office of Technology, Policy, and Strategy to view this and other 

reports visit https://www.nasa.gov/offices/otps/home/index.html

Executive Summary 

Space-Based Solar Power 

Purpose of the Study 

This study evaluates the potential benefits, challenges, and options for NASA to engage with 

growing global interest in space-based solar power (SBSP). Utilizing SBSP entails in-space 

collection of solar energy, transmission of that energy to one or more stations on Earth, 

conversion to electricity, and delivery to the grid or to batteries for storage. Experts in both the 

aerospace and energy sectors are debating the benefits of SBSP as more organizations globally 

begin SBSP technology development programs. Proponents claim SBSP could deliver large 

amounts of electricity at competitive prices and with fewer greenhouse gas (GHG) emissions than 

terrestrial renewable electricity technologies while accelerating development of the space 

economy. Skeptics say SBSP has no clear development path and would divert billions of dollars 

from known terrestrial solutions while damaging the environment. While it is generally 

understood that SBSP is cost prohibitive and technically infeasible today, this study assesses 

operating SBSP systems in 2050. Part of NASA’s mission is to innovate for the benefit of humanity 

– it is through this lens that the Agency weighs whether and how to support SBSP development. 

The study addresses the following questions: 

• Under what conditions would SBSP be a competitive option to achieving net zero GHG

emissions compared to alternatives?

• If SBSP can be competitive, what role, if any, could NASA have in its development?

To answer these questions, we spoke with more than 30 stakeholders and subject matter experts 

across the aerospace and energy sectors, reviewed over 100 documents relating to SBSP, developed 

a model to characterize and estimate the costs and GHG emissions of SBSP under varying 

technological and economic conditions, and qualitatively assessed challenges to SBSP development. 

Using these data sources, we:

1. Generated first-order lifecycle cost and emissions estimates for first-of-a-kind, utility-scale

SBSP and compared those with current renewable electricity production technologies,

2. Conducted sensitivity analyses to assess whether a competitive SBSP solution is feasible,

3. Conducted qualitative assessments of challenges, opportunities, and NASA’s role,

4. Discussed options for NASA’s engagement, and

5. Made follow-on study recommendations.

January 11, 2024 Report ID 20230018600
ii

Key Findings

Question 1: Under what conditions would SBSP become competitive?

System Designs

We assessed two representative SBSP designs: Innovative Heliostat Swarm (Representative Design 

One, RD1) and Mature Planar Array (Representative Design Two, RD2), based on existing concepts. 

The SBSP designs serve simply as point designs for assessment purposes and should not be viewed 

as endorsements to or by NASA. RD11 and RD22 are broadly derived from historical, publicly 

available designs that include recent updates and provide enough data from which to perform a 

first-order analysis of this kind. RD1 generates power 99% of the year and collects solar radiation by 

autonomously redirecting its reflectors toward a concentrator to focus sunlight throughout each 

day. RD2 uses flat panels, with solar cells facing away from Earth and microwave emitters facing 

toward the Earth. RD2 generates power 60% of the year due to its limited capability to reposition 

itself or redirect solar radiation toward its solar cells. Each SBSP design is normalized to deliver 2

gigawatts (GW) of power to the electric grid to be comparable to very large terrestrial solar power 

plants operating today.3 Therefore, five RD2 systems are needed to deliver roughly the same 

amount of power as one RD1 system. The functional representation of each design is illustrated in 

Figure 1.

Each SBSP design’s size (which is dominated by the area of its solar panels) and mass is significant. 

To provide context, consider two examples of space systems with significant mass and solar panel

area: an aggregated mass, the International Space Station (ISS); and a distributed mass, a 

constellation of 4,000 Starlink v2.0 satellites4. The solar panel area is 11.5km2for RD1 and 19km2for 

RD2. The RD1 solar panel area is more than 3,000 times and 27 times greater than that of the ISS 

and Starlink constellation, respectively. The mass is 5.9Mkg for RD1 and 10Mkg for RD2. The RD1 

1

John C. Mankins “SPS-Alpha Mark-III and an Achievable Roadmap to Space Solar Power,” 72nd International 

Astronautical Congress, October 15, 2021.

2

Susumu Sasaki et al. “A new concept of solar power satellite: Tethered-SPS” Acta Astronautica 60 (2006) 153-165

and Pellegrino et al. "A lightweight space-based solar power generation and transmission satellite." (2022) 

https://doi.org/10.48550/arXiv.2206.08373.

3 Voiland, Adam, “Soaking up Sun in the Thar Desert,” NASA Earth Observatory, January 26, 2022. 

https://earthobservatory.nasa.gov/images/149442/soaking-up-sun-in-the-thar-desert

4 The >4,000 Starlink satellites in orbit today are smaller than the v2 and include 4 different configurations, but 

offer us an example of the kind of upmass that is already approved for this and other existing satellite 

constellations. Other large constellations are comparable, but of existing constellations, Starlink has already 

delivered the most mass into orbit. Assuming a mass of 1250kg and solar array area of 105 m2 per Starlink v2 

satellite. These systems were chosen because at the time of this report’s publication they represent the most 

massive single monolithic system in Earth orbit (ISS), and the most massive single distributed system (Starlink 

constellation).
iii

mass is more than 14 times greater and 1.2 times greater than that of the ISS and Starlink

constellation, respectively. 

This study assessed lifecycle cost and emissions based on the following scenario: SBSP systems are 

developed on the ground in the 2030s and launched to low-Earth orbit (LEO), and then transferred 

to and assembled in geostationary orbit (GEO) in the 2040s. The SBSP systems are operated in GEO 

from 2050-2080, by transmitting energy to one or more stations on Earth. Maintenance, which 

entails developing, launching, and assembling new spacecraft modules, occurs between 2060-2080. 

SBSP systems disposal operations, which entail developing and launching debris removal spacecraft 

to GEO to transfer spacecraft modules to a graveyard orbit, occurs between 2060-2085.

Lifecycle Calculations

We developed a model to calculate the cost and GHG emissions for all aspects of the SBSP 

reference designs across the full lifecycle of development, assembly, operation, maintenance, and 

disposal. Including disposal or decommissioning of a system is a best practice when assessing its full 

lifecycle. The calculated lifecycle cost and GHG emissions are for first-of-a-kind systems delivering 2

GW of power to the electric power grid beginning in 2050. At the end of 2022, according to the 

Energy Information Administration (EIA), the United States had 1,160 GW of total utility-scale 

electricity-generation capacity.5

We calculated the lifecycle cost of electricity and lifecycle GHG emissions intensity for each 

representative SBSP design using common industry expressions: levelized cost of electricity (LCOE) 

and Economic Input Output – Life Cycle Analysis (EIO-LCA). The LCOE is the average cost of 

electricity over a generator’s lifetime and is a mainstay of energy sector analyses. The EIO-LCA is an 

established methodology for estimating first-order emissions intensity of economic activity. LCOE 

has several limitations. For example, it does not consider the variable value of energy at different 

locations or times.6 EIO-LCA also has limitations. This methodology often uses spend-based metrics 

to estimate emissions, which assumes a relationship between cost, efficiency, and emissions that 

may not always align with direct measurements of emissions by economic activity.

All cost estimates are measured in Fiscal Year 2022 (FY22) dollars. EIO-LCA uses measured GHG 

emissions of producing goods and services by mass (like kilograms of steel), area (like square meters 

of solar cells), or cost (like dollars spent on services) by aggregating macroeconomic data. We then 

compared the LCOE and lifecycle GHG emission intensity (EIO-LCA) to alternative terrestrial 

renewable electricity production technologies using data from the National Renewable Energy 

5 EIA, “Electricity explained,” last updated: June 30, 2023

https://www.eia.gov/energyexplained/electricity/electricity-in-the-us-generation-capacity-and-sales.php.

6

For more information on metrics, see NREL, “Competitiveness Metrics for Electricity System Technologies” 2021, 

https://www.nrel.gov/docs/fy21osti/72549.pdf.
iv

Laboratory (NREL) to assess if the representative SBSP designs are competitive. We compared to 

NREL’s 2050 cost projections and NREL’s 2021 GHG emissions for nuclear fission, geothermal, 

hydroelectric, utility-scale solar photovoltaics with storage, and land wind without storage. We use 

2021 emissions data because there are no projections for this data. We include land wind without 

storage for comparison because it has the lowest cost and lowest emission intensity of all electricity 

production technologies tracked by NREL. 
v

Figure 1. Functional Decomposition of SBSP Design Reference Systems. [Left] RD1. [Right] RD2.
vi

Baseline Assessment 

We made assumptions across the full lifecycle of development, assembly, operation, maintenance, 

and disposal to calculate the cost and GHG emissions of first-of-a-kind SBSP designs. The study’s 

baseline assessment and sensitivity analyses (Table 1) incorporate three categories of assumptions 

regarding space capabilities: 1) beyond assumes certain capabilities will be available by 2050, 2) 

comparable uses today’s capabilities as a starting point; and 3) below covers the possibility that an 

existing capability does not perform to previously demonstrated levels when used in a novel SBSP 

system. We do not include novel architectures or recent advances in material science that may alter 

the specifications of a 2 GW SBSP system. These assumptions do not represent NASA’s position on 

the future aerospace industry and serve only as an analytical platform.

Table 1. Key Input Parameters for Multiple Variable Sensitivity Analysis and Baseline Analysis. Green triangles pointing upward 

indicate an assumption beyond what has been achieved to date, yellow bars are achievable today, and red triangles pointing 

downward are below today’s capability (these are assumed given the first-of-a-kind nature of the SBSP systems studied).
vii

Beyond: We assume costs to launch a Starship7 and reuse each Starship, along with operations 

costs, are lower in 2050 than today. This is in part because autonomous capabilities are assumed for 

the representative SBSP designs.

Comparable: We assume solar cell efficiency at the current state of the practice for GEO satellites 

because technological advances are difficult to predict beyond a few years. We assume an orbital 

transfer method leveraging refueling launches to reach GEO at the current state of the practice.8

We assume manufacturing curves and initial hardware costs at approximately the current state of 

the practice as a “starting point” for learning over the multi-decade manufacturing process. 

Manufacturing curves were selected based on analogous industries with similar production levels.

Below: We assume a hardware lifetime below that of the current state of the practice for GEO 

hardware because the SBSP designs are first-of-a-kind systems requiring multiple refurbishment 

cycles. 

Our study found the following: The baseline lifecycle cost of electricity for RD1 is 0.61 $/kWh and 

for RD2 is 1.59 $/kWh. Launch is the largest cost driver (71% of RD1 and 77% of RD2) as 2,3216 

launches are required to deliver 5.9Mkg of mass for RD1 and 3,960 are needed to deliver 10Mkg of 

mass for RD2. Most of these launches (12 of every 13) serve only to refuel payloads in LEO for 

transfer to GEO. Manufacturing is the second largest cost driver (22% for RD1 and 18% RD2) and

includes initial spacecraft hardware development and manufacturing. Learning curves enable cost 

decreases over time as experience is gained through producing 1.5M spacecraft modules for RD1 

and 2M spacecraft modules for RD2. In general, RD2 is more expensive than RD1 because more 

mass is involved; five RD2 systems are needed to generate roughly the same amount of power as 

one RD1 system.

Figure 2 shows the comparison of the lifecycle baseline assessment to terrestrial renewable 

electricity production technologies, whose costs range from 0.02-0.05 $/kWh. The RD1 LCOE and 

RD2 LCOE are 12-31 and 32-80 times higher, respectively, than the 2050 projections for terrestrial 

alternatives. Therefore, our baseline analysis of SBSP designs does not return cost competitive

results relative to terrestrial alternatives. For comparison, the average energy cost of a U.S. 

household in August 2022 was 0.167 $/kWh.9

7 Due to the size and mass of the representative SBSP designs, for purposes of this study, we used available data 

from Space Exploration Technologies Corporation’s (SpaceX’s) Starship launch vehicle. because at this time it is 

anticipated to be the largest super heavy launch vehicle with data available. It is important to note that multiple 

specifications for this vehicle are planned, and cover a range of payload capacities, fuel capacities, and more. The 

study’s use of data from Starship does not indicate any endorsement by NASA. 

8 Blue Origin Fed’n, LLC; Dynetics, Inc.-A Leidos Co., B-419783 et al., July 30, 2021, 2021 CPD ¶ 265 at 27 n.13

9 U.S. Bureau of Labor Statistics (2023), Average energy prices for the United States, 

https://www.bls.gov/regions/midwest/data/averageenergyprices_selectedareas_table.htm.
viii

The baseline lifecycle GHG emissions intensity for RD1 is 26 gCO2eq./kWh and for RD2 is 40 

gCO2eq./kWh. For comparison, the U.S. electric grid in 2021 produced an average of 385 

gCO2/kWh.10 Launch is the largest driver and leads to 64% and 72% of the GHG emissions for RD1 

and RD2, respectively. GHG emissions intensity for both RD1 and RD2 fall within the range of GHG 

emissions intensities (13-43 gCO2eq./kWh) for terrestrial renewable electricity production 

technologies. For comparison, the GHG emissions intensities of coal and natural gas are 486 

gCO2eq./kWh and 1001 gCO2eq./kWh, respectively.11 RD1 and RD2 emissions intensities do not 

include upper atmosphere effects of launch emissions, which are assumed to be worse than 

producing the same emissions on the surface of the Earth, and still under study by NASA and the 

academic community.12 Our baseline analysis indicates our SBSP designs may have similar lifecycle 

GHG emissions intensities to those of terrestrial alternatives, pending further studies launch 

emission effects in the upper atmosphere.

Sensitivity Analyses

We conducted sensitivity analyses on the assumptions that drive the lifecycle cost and GHG 

emissions intensity to evaluate what conditions could allow RD1 and RD2 to be cost competitive 

(Figure 3). We varied the following input parameters one at a time to assess their individual impact 

on lifecycle cost and emissions: launch costs, first unit manufacturing costs, manufacturing learning 

curves, hardware lifetime, solar cell efficiency, and orbital transfer methods. Lower launch costs or

use of electric propulsion to transfer mass from LEO to GEO each resulted in the most significant 

reduction of LCOE to about 0.20 $/kWh for RD1 and to about 0.50 $/kWh for RD2. This decrease is 

not enough to make the representative designs cost competitive with terrestrial alternatives. 

Cost competitiveness can be achieved by varying multiple assumptions (Table 1) at the same time 

to provide a combination of cost and capability improvements beyond the advances already 

assumed in the baseline assessment. This favorable combination reduces the LCOE to 0.03 $/kWh 

for RD1 and 0.08 $/kWh for RD2, figures that are competitive with terrestrial alternatives. This 

combination also reduces the GHG emissions intensities (3.78 gCO2eq./kWh for RD1 and 4.33

gCO2eq./kWh for RD2) to values less than nuclear and wind-without-storage technologies. 

10 EIA, (2022, November 25), How much carbon dioxide is produced per kilowatthour of U.S. electricity generation?

https://www.eia.gov/tools/faqs/faq.php?id=74&t=11.

11 Ibid.

12 National Oceanic and Atmospheric Administration (2022, June 22), Projected increase in space travel may 

damage ozone layer, https://research.noaa.gov/2022/06/21/projected-increase-in-space-travel-may-damageozone-layer/.
ix

The following combination of revised assumptions yields SBSP solutions that are cost competitive 

with terrestrial alternatives, with lower GHG emissions:

• lower launch cost: $50M per launch, or $500/kg; $425/kg with 15% block discount

• electric propulsion orbital transfer from LEO to GEO

• extended hardware lifetimes: 15 years

• cheaper servicer and debris removal vehicles: $100M and $50M, respectively

• efficient manufacturing at scale: learning curves of 85% and below

Our sensitivity analyses highlight the need for advances across a wide range of SBSP enabling 

capabilities. 
x

Figure 2. Comparison of SBSP Systems Cost ($FY22) and GHG Emissions Baseline Assessment with Terrestrial Alternatives
xi

Figure 3. SBSP Systems Cost ($FY22) and GHG Emissions Reduction Sensitivities Results
xii

Question 2: What role, if any, should NASA have?

Question 1 provided a model for understanding the biggest cost drivers for SBSP: launch and 

manufacturing. To understand NASA’s potential role, the study qualitatively assessed challenges 

and opportunities for SBSP development. We reviewed technological, regulatory, and policy 

challenges, as well as technological and economic opportunities. The review found that SBSP 

enabling technologies have broad applicability to a wide suite of future NASA mission needs, from 

power beaming on the Moon, to autonomous operations for science and human exploration, to 

lightweight materials. NASA currently funds research and development activities in each of these 

areas, though some areas receive significantly more funding: In-space servicing, assembly and 

manufacturing received ~$280M in FY22, autonomy received ~$244M in FY22, while wireless power 

transmission investments are today limited to concept studies (<$1M).13

This study provides two main categories of options for NASA leadership to consider without making 

a specific recommendation:

1. Undirected organic development: NASA is working on almost all the enabling technologies 

for SBSP and may want to focus only on its own current and planned missions’ needs, 

limiting further involvement, upon request, to supporting U.S. organizations pursuing SBSP 

and maintaining awareness of SBSP advances around world. NASA could fund these areas 

without adding SBSP as a separate line item in its budget. That said, further study of 

potential benefits of SBSP to planned missions is warranted.

2. Pursue partnership opportunities to advance SBSP: NASA may find mutually beneficial 

returns from supporting external SBSP development given the relevance of enabling 

technologies to other agency missions. Moreover, these technologies, from autonomous 

operations to wireless power transmission, have many use-cases beyond NASA missions, 

and are being pursued by a broad set of public and private actors for many non-SBSP 

applications.

This study also provides follow-on study recommendations regardless of option choice, including:

1. Building on the first order analysis, study cutting-edge SBSP systems using the most rigorous 

lifecycle emissions and cost assessments as performed by NREL on other electricity 

production technologies.

2. Perform a technical design trade evaluation of SBSP technologies for NASA mission 

applications, such as energy infrastructure on the Moon. 

13 Brandon, E. (2019, April 10). Power Beaming for Long Life Venus Surface Missions. Retrieved June 2023, from 

https://www.nasa.gov/directorates/spacetech/niac/2019_Phase_I_Phase_II/Power_Beaming/ and

Lubin, P. (2021, April 2). Moonbeam-Beamed Lunar Power. Retrieved from 

https://www.nasa.gov/directorates/spacetech/strg/lustr/2020/Moonbeam_Beamed_Lunar_Power/.
xiii

Conclusion

We performed a first-order lifecycle study of two representative SBSP designs for 2 GW utility-scale 

power generation that are presumed to begin operating in 2050 to determine 1) the conditions

under which SBSP would be a competitive option to achieving net zero GHG emissions; and 2) 

assuming SBSP can be competitive, the role, if any, NASA could play in its development.

We assumed baseline capabilities to develop, assemble, operate, maintain, and dispose of the SBSP 

systems are a mix of capabilities that are above, below, or comparable to capabilities demonstrated 

to date. We then compared the LCOE and lifecycle GHG emission intensity of the SBSP designs to 

terrestrial renewable electricity production technologies. Our findings indicate the SBSP designs 

may produce lifecycle GHG emissions per unit of electricity that are comparable to terrestrial 

alternatives, pending further studies of upper atmosphere effect of launch emissions. We find the 

SBSP designs are more expensive than terrestrial alternatives and may have lifecycle costs per unit 

of electricity that are 12-80 times higher. However, cost competitiveness may be achieved through

a favorable combination of cost and performance improvements related to launch and 

manufacturing beyond the advancements assumed in the baseline assessment.

NASA is developing technologies and capabilities to meet its future mission needs, such as in-space 

servicing, assembly, and manufacturing (ISAM) and autonomy, which are enablers for SBSP. NASA 

could maintain its focus on core Agency missions and technologies, while documenting their 

relevance to SBSP. NASA may also enhance coordination with U.S. and international partners on

technology development with relevance to SBSP. We recommend regular reviews of global SBSP 

developments and focused analyses of SBSP designs that may enable NASA’s core missions.
xiv

Table of Contents

Executive Summary............................................................................................................. i

Purpose of the Study...................................................................................................................... i

Key Findings...................................................................................................................................ii

Question 1: Under what conditions would SBSP become competitive? ...................................................ii

Question 2: What role, if any, should NASA have?.................................................................................... xii

Conclusion.................................................................................................................................. xiii

Table of Contents ............................................................................................................ xiv

1.0 Introduction................................................................................................................... 1

1.1 Background..............................................................................................................................1

1.2 Study Questions.......................................................................................................................5

2.0 Methodology Overview................................................................................................. 5

2.1 Cost Estimations.......................................................................................................................6

2.1.1 Functional Decomposition of SBSP Systems ...............................................................................................6

2.1.2 Concept of Operations................................................................................................................................6

2.1.3 Levelized Cost of Electricity.......................................................................................................................10

2.2 GHG Emissions Intensity .........................................................................................................12

3.0 Results......................................................................................................................... 13

3.1 Summary of SBSP System Costs and GHG Emissions ................................................................17

4.0 Sensitivity Analyses ................................................................................................... 18

4.1 Launch ...................................................................................................................................18

4.1.1 Direct Launch to GEO................................................................................................................................18

4.1.2 Reduced Launch Costs...............................................................................................................................18

4.1.3 Electric Propulsion Orbital Transfer ..........................................................................................................19

4.1.4 Spacecraft Hardware Life ..........................................................................................................................20

4.2 Manufacturing .......................................................................................................................20

4.2.1 Initial Hardware Costs...............................................................................................................................20

4.2.2 Learning Curve ..........................................................................................................................................21
xv

4.2.3 Solar Cell Efficiency ...................................................................................................................................21

4.3 Combining Sensitivities...........................................................................................................21

4.4 Making SBSP Systems Competitive with Terrestrial Renewables..............................................22

5.0 Challenges and Opportunities................................................................................... 24

5.1 Challenges to Operational System Development .....................................................................24

5.1.1 Large-scale ISAM Capability Challenges....................................................................................................24

5.1.2 Large-scale Autonomous Distributed Systems..........................................................................................25

5.1.3 Power Beaming .........................................................................................................................................25

5.2 Challenges to Reducing System Costs......................................................................................25

5.2.1 Launch costs..............................................................................................................................................25

5.2.3 Manufacturing at scale..............................................................................................................................26

5.2.4 Launch cadence.........................................................................................................................................26

5.3 Regulatory and Other Challenges............................................................................................27

5.3.1 Active Debris Removal ..............................................................................................................................27

5.3.2 Spectrum Allocation..................................................................................................................................27

5.3.3 Orbital Slot Allocation ...............................................................................................................................27

5.3.4 Security......................................................................................................................................................27

5.4 Ongoing Improvements to SBSP Technology Needs.................................................................28

5.4.1 ISAM..........................................................................................................................................................28

5.4.2 Autonomous Distributed Systems.............................................................................................................28

5.4.3 Power Beaming .........................................................................................................................................28

5.5 Ongoing Improvements to SBSP Economic Needs....................................................................29

5.5.1 Electric Propulsion Orbital Transfer ..........................................................................................................29

5.5.2 Alternative Launch ....................................................................................................................................30

5.5.3 Mass Manufacturing .................................................................................................................................30

5.5.4 Advanced Materials ..................................................................................................................................30

5.6 Architecture Opportunities.....................................................................................................30

6.0 Options for NASA to Consider................................................................................... 30

6.1 Option 1: Undirected and Organic Development .....................................................................31

6.2 Option 2: Pursue Partnership Options to Advance SBSP...........................................................31
xvi

7.0 Conclusion and Recommended Further Study ........................................................ 32

Appendix A: Representative Design Details................................................................... 35

Appendix B: Methodology ............................................................................................... 37

Overview.....................................................................................................................................38

Approach to Cost Calculations......................................................................................................40

Functional Decomposition of SBSP Systems......................................................................................................40

ConOps Phases...................................................................................................................................................41

Levelized Cost of Electricity................................................................................................................................55

Results................................................................................................................................................................59

Approach to GHG Emissions Calculations......................................................................................62

GHG Emissions ...................................................................................................................................................62

Climate Comparisons .........................................................................................................................................72

Sensitivity Analyses......................................................................................................................72

Launch................................................................................................................................................................73

Manufacturing....................................................................................................................................................74

Solar Cell Efficiency ............................................................................................................................................75

Multiple Variable Sensitivity Analyses ...............................................................................................................75

Appendix C: Acknowledgements .................................................................................... 78

Appendix D: Acronyms & Key Terms .............................................................................. 79

References ........................................................................................................................ 85
1

1.0 Introduction

This report describes for NASA senior-level consideration the relative costs and greenhouse gas 

(GHG) emissions of space-based solar power (SBSP) systems to assess whether SBSP is a feasible 

option for achieving net-zero GHG emissions compared to alternative renewable sources of 

electricity production. Our assessment considered two reference SBSP system designs operating in 

geostationary orbit (GEO) – the lower technology readiness level (TRL) Innovative Heliostat Swarm, 

(hereafter referred to as Representative Design One, or RD1) and the higher TRL Mature Planar 

Array (Representative Design Two, or RD2) – and compared costs for their development, assembly, 

operation, maintenance, and disposal. We also compared the relative GHG emissions of each 

system by conducting material decompositions for an Economic Input Output – Life Cycle 

Assessment (EIO-LCA). 

1.1 Background 

In response to climate change, organizations around the world are pursuing a range of policies 

called net zero. According to the United Nations (UN), “net zero means cutting greenhouse gas 

emissions to as close to zero as possible, with any remaining emissions re-absorbed from the 

atmosphere, by oceans and forests for instance.” There is growing U.S. and international policy and 

legislation on net zero. As of 2021 over 70 countries had set net-zero targets (United Nations, 

2023). The U.S. submitted a long-term strategy to the UN in November 2021, officially committing 

to net zero emissions by 2050 at the latest (United States Department of State and the United 

States Executive Office of the President, 2021). 

The electric power sector accounted for 25% of U.S. GHG emissions in 2020, according to the U.S. 

Environmental Protection Agency (EPA), as shown in Figure 2 (EPA, 2023). The sector encompasses 

the generation, transmission, and distribution of electricity. Carbon dioxide (CO2) makes up 80% of 

GHG from the U.S. electricity sector. According to the U.S. Energy Information Administration (EIA), 

CO2 emissions by the U.S. electric power sector in 2021 were about 1,545 million metric tons

(MMmt), or about 31% of the 4,970 MMmt of total U.S. energy-related CO2- emissions (EIA, 2023). 

These emissions primarily result from electricity generation using coal and natural gas, which are 

non-renewable energy sources (see Figure 2 inset). In 2021, 40% of U.S. electricity production came 

from renewable and nuclear sources as shown in Figure 3. The International Energy Agency 

estimates that to reach net-zero, the world will need to reduce its use of fossil fuels from 80% of 

the total today to slightly over 20% by 2050 (Bouckaert, et al., 2021). However, the EIA projects that 

by 2050, 44% of U.S. electricity will still come from fossil fuels (EIA, 2022). 
2

Figure 3. Share of U.S. Greenhouse Gas Emission by Economic Sector in 2020, (EPA, 2023). Inset. Share of U.S. CO2 Emissions 

from Electric Power by Technology in 2022 (EIA, 2023).

Some experts have noted that SBSP is a renewable energy alternative that could contribute to netzero goals, though SBSP is not featured in any of the net zero pathways considered by the most 

recent International Panel on Climate Change (P.R. Shukla, 2022). An SBSP system collects solar 

energy in space, converts that to microwave or optical laser energy, and transmits that energy to 

the Earth. A ground station receives the energy, converts it to electricity, and delivers it to the 

power grid for use. The rate and intensity of worldwide research into SBSP has seen significant 

growth: The number of publications on the topic nearly doubled from 2018 to 2022, with most of 

the research concentrated in China, the U.S., the European Union (EU), Japan, and Russia (NASA 

Library, 2023).
3

Figure 4. U.S. Electricity Generation by Technology. [Left] Share of U.S. Electricity Generation by Technology in 2021, (EIA, 2022). 

[Right] Projected share of U.S. Electricity Generation by Technology in 2050, (EIA, 2022).

Many countries have ongoing SBSP studies, design concepts, and technology development activities 

including the U.S., the United Kingdom, the EU, Japan, China, South Korea, and Australia. In the U.S., 

for example, the California Institute of Technology (Caltech) completed the first successful 

electricity beaming demonstration from space to ground in June 2023 (Caltech, 2023). In general, 

this work is funded and conducted by academic, commercial, and government communities 

motivated by economic development, net zero, and national policy goals. Figure 4 displays a map of 

current international SBSP activity. The SBSP concepts described in this report focus on civil 

applications of SBSP to deliver electricity to the power grid. SBSP is being pursued by different 

organizations for different use-cases. The resulting national benefits could extend beyond 

immediate fiscal returns or near-term GHG emissions reductions. 
4

Figure 5. International SBSP Activities. SBSP studies, design concepts, and technology developments are funded around the world for economic development, net-zero goals, and 

national goals. Countries with non-space-based power beaming efforts are not included.
5

1.2 Study Questions

The idea of SBSP is not new to NASA, which conducted feasibility studies first in the 1970s (NASA & 

DoE, 1980) and again in the 1990s (Mankins, A fresh look at space solar power: New architectures, 

concepts and technologies, 1997). These studies found it prohibitively expensive to develop, launch 

and assemble, operate, maintain, and dispose of SBSP systems ($1T estimate in then-year dollars 

for an SBSP technology demonstration in the 1970s and $250B estimate in then-year dollars for the 

first commercial kilowatt (kW) of power in the 1990s). The context of SBSP development has 

changed significantly in the last three decades, however, prompting this study. Public and private 

actors across the international community are motivated to develop SBSP for economic 

development, net-zero goals, and global leadership.

The study seeks to answer two questions:

• Under what conditions would SBSP be a competitive option for achieving net zero GHG

emissions compared to alternatives?

• If SBSP can be competitive, what role, if any, could NASA have in its development?

Alternative renewable electricity production technologies that we compared to SBSP include 

nuclear fission, geothermal, hydroelectric, utility-scale solar photovoltaics with storage, and land 

wind without storage. The study includes nuclear power even though it is not usually grouped with 

renewables because it is considered “non-emitting” by the EPA (EPA, 2023). 

Given increasing investment and attention to SBSP worldwide, this study is intended to inform 

NASA decision-making regarding any potential Agency role in SBSP development. Therefore, we 

present options for consideration for senior leaders.

2.0 Methodology Overview

To determine the feasibility of SBSP we estimated the cradle-to-grave costs and GHG emissions of 

two system designs: RD1 (Innovative Heliostat Swarm) and RD2 (Mature Planar Array) based on 

existing concepts with updated technology assumptions on mass, efficiency, and launch capacity. 

The lifecycle cost estimates were used to calculate the levelized cost of electricity (LCOE) for each 

system for comparison to terrestrial renewable alternatives using data from the National 

Renewable Energy Laboratory (NREL). GHG emissions were estimated using a hybrid mass- and 

spend-based Economic Input Output-Life Cycle Analysis (EIO-LCA) and compared to terrestrial 

alternatives using NREL data.
6

Limitations of the study include:

• This is a first-order assessment of notional systems: Cost and GHG emissions estimates are 

not exhaustive, and outputs are heavily influenced by assumptions about a technology with 

no historical data points built and operated in an unknown future.

• The reference designs assessed are not representative of all proposed SBSP architectures: 

For example, systems in lower orbits have been proposed but are not assessed in this study.

For a detailed methodology, broken out by each step of the analysis and including results, please 

see Appendix B. 

2.1 Cost Estimations

To estimate costs, we: 1) defined SBSP systems based on six key functions, 2) divided the SBSP 

system lifecycle into five concept of operations (ConOps) phases, generating cost estimates for each 

phase, and 3) used ConOps costs to determine the LCOE for comparison to other renewable energy 

technologies. 

2.1.1 Functional Decomposition of SBSP Systems

Generating electricity using SBSP systems involves six functions: collect solar energy in space, 

convert (in space) energy to microwave or optical energy, transmit that energy to Earth, receive

the transmitted energy at one or more ground stations, convert (ground) that energy to electricity, 

and deliver electricity to the grid for consumption or to batteries for storage. 

This study assesses two representative SBSP designs: 1) the RD1 (Innovative Heliostat Swarm) 

concept, which uses a concentrator to improve its capacity factor, and 2) the RD2 (Mature Planar 

Array) concept, a less complex system that collects solar energy on one side and emits this energy 

as microwaves on the other. Figure 5 describes each reference design in terms of the six key 

functions; more detailed information on each concept is presented in Appendix A. 

2.1.2 Concept of Operations

The ConOps for each reference design is broken into five lifecycle phases: develop, assemble, 

operate, maintain, and dispose. Including disposal or decommissioning of a system is a best practice 

when assessing its full lifecycle. Figures 6a and 6b provide a visual summary of each ConOps phase. 

We estimate the cost of each SBSP reference designs by ConOps phase. Appendix A contains a 

detailed breakdown of each phase and all relevant parameters. Appendix B shows the mapping of 

ConOps phases to each functional step.
7

Figure 6a. Functional Decomposition of SBSP Design Reference Systems
8

Figure 6b. ConOps for the Innovative Heliostat Swarm Design Reference One System
9

Figure 6c. ConOps for the Mature Planar Array Design Reference Two System 
10

Baseline assumptions are derived from a mix of current and projected technologies and costs. 

Among the key assumptions in the baseline assessment is that Space Exploration Technologies 

Corporation’s (SpaceX’s) Starship launcher, which is currently in testing, will be commercially 

available at $100M per launch. We make no claim as to the reliability of this assumption given the 

early stages of Starship development, but rather make this assumption because on a per kilogram 

basis, this represents a similar decline in launch prices from today as has occurred in the past 10 

years. We include a 15% block buy discount because of the very large number of launches required 

to deploy an SBSP system. We assume one payload-laden Starship in LEO requires refueling by 12 

separate Starship propellant tankers to reach GEO (Blue Origin Fed’n, LLC; Dynetics, Inc.-A Leidos 

Co., 2021).

14 Based on subject matter experts (SME) input, we also assume 100 reuses of Starships 

used for refueling, and that payload-carrying Starships are single-use. SpaceX has been able to 

conduct two Falcon 9 launches in a week, so we assume this launch cadence for the Assemble 

ConOps phase. The Aerospace Corporation provided estimates of manufacturing learning curves, 

first-unit costs for each hardware element, component and system lifetimes, as well as module 

assembly time, all of which were reviewed, augmented, and incorporated by the study team. 

Finally, literature on SBSP concepts informed system specifications of the RD1 and RD2 designs. 

Estimated time to assemble a fully developed SBSP system in our baseline assessment is 7.4 years 

for RD1 and 12.6 years for RD2. Key input parameters are shown in Table 2. For a complete 

accounting of inputs, assumptions, and calculations, please see Appendix B.

2.1.3 Levelized Cost of Electricity

Using our cost estimates, we calculated the LCOE measured in $/kWh for each reference design to 

compare overall costs to other renewable electricity production technologies. LCOE is commonly 

used by the energy sector for comparative analyses. LCOE is calculated by estimating the lifecycle 

cost (using different units for different categories) of the SBSP system and dividing that by lifecycle 

kWh production by the system. Figure 7 provides an overview of the LCOE calculation.

14 This estimate was derived using publicly available information about the initial human landing system for lunar 

exploration to be developed by SpaceX and modifying that based on the assumption that reaching GEO orbit 

would not require as many refueling launches as would reaching cislunar space. Blue Origins Fed’n, LLC; Dynetics, 

Inc.-A Leidos Co., B-419783 et al., July 30, 2021, 2021 CPD ¶ 265 at 27 n.13. This data was used because the 

Starship launch vehicle is anticipated to be the largest super heavy launch vehicle with available data and should 

not be construed as an endorsement by NASA. It is important to note that multiple specifications for this vehicle 

are planned, and cover a range of payload capacities, fuel capacities, and more.
11

Table 2. Key Input Parameters

Key Input Parameter Value Source and Rationale

Starship launch cost ($) $100M, 

15% block buy discount

2013-2022 36% launch cost decrease, Falcon Heavy cost 

of $1500/kg to 2030s.

Scale of launches may offer discount.

Reuses of launch vehicle

(does not include payload 

Starships traveling to GEO)

100

SpaceX states most components of Falcon 9 may be 

reused 100 times, but some elements must be replaced 

after 10 uses. New Glenn claims 25 reuses. 100 reuses = 4 

times the state of practice.

Orbital transfer method

12 refuel launches in LEO

1 month refuel time

2 months travel to GEO

Blue Origin Fed’n, LLC; Dynetics, Inc.-A Leidos Co., supra..

Does not consider cryogenic boiloff.

First order delta-v.

Launches per year 104 Assuming two launches per week. Falcon 9 currently 

launching about 1.5x/week.

Manufacturing learning 

curves

85% for servicer 

75% for modules

90% for debris vehicles 

The Aerospace Corporation estimates based on aggregate 

manufacturing sector data.

First unit costs ($)

$1B for servicer

$1M for SBSP modules

$500M debris vehicles

The Aerospace Corporation estimates based on satellite 

and solar cell industry and OSAM-1 costs.

Solar cell efficiency 35% NASA assessment of Smallsat technology.

Hardware lifetime (years) 10 The Aerospace Corporation estimates.

System lifetime 30 The Aerospace Corporation estimates.

Initial system upmass (kg), 

number of modules

5.9M (RD1), 1.46M

10M (RD2), 2M Inferred from Mankins, Sasaki, Pellegrino.

Ground rectenna 6km diameter (RD1)

4km diameter, 5 sites (RD2)

The Aerospace Corporation assessed costs of analogs: 

solar power plants and large antenna arrays. 

Operations cost 1.2M/month Assumes autonomous operations capability. Significantly 

less than today ~500k/year per satellite.

Assembly time per module 

(minutes) 40 (RD1), 38 (RD2) The Aerospace Corporation estimates based on Orbital Express and ISS analogs.
12

Figure 7. Cost Calculations for SBSP Systems. Refer to Figure 6 for ConOps Phase activities.

2.2 GHG Emissions Intensity

To estimate GHG emissions in carbon dioxide equivalents (CO2eq), we 1) used material 

decompositions of each reference design, and 2) provided a comparison to other renewable energy 

technologies, drawing from NREL emission data (National Renewable Energy Laboratory, 2023). 

We estimated the GHG emissions of each design in three steps:

1. Estimate the material composition of each design, in kilograms (kg) or square meters (m2)

2. Cite authoritative sources on the emissions intensity of delivering components and 

materials, in kgCO2eq per kg, m2, or thousands of dollars (kUSD).

3. Estimate the lifecycle emissions intensity using a hybrid mass and spend-based Economic 

Input Output-Life Cycle Analysis (EIO-LCA). 

EIO-LCA uses aggregate data on sectors of the U.S. economy to quantify the GHG emissions that can 

be attributed to specific sectors and activities. Our analysis uses the aggregated metrics provided by 

the International Aerospace Environmental Group (IAEG) (International Aerospace Environmental 

Group, 2023), including datasets from Carnegie Mellon University and the U.S. Department of 

Defense (DoD) on the GHG emissions intensity of activities measured in kilograms of carbon 

equivalents (kgCO2eq.) per kUSD, kg, or m2. This spend-based approach is used where material 

decomposition does not provide adequate coverage of post-processing and assembly work. It is 

important to remember that because the EIO-LCA model relies on aggregated economic 

transactions and their recorded GHG emissions, there is an assumed relationship between cost, 
13

efficiency, and reduced emissions, though it is possible to reduce costs without mitigating GHG 

emissions of manufacturing. The resulting GHG emissions estimates were then compared to other 

renewable energy technologies.

Figure 8. Calculations for SBSP GHG Emissions. Refer to Figure 6 for ConOps Phase activities.

Results of the initial baseline cost and emissions estimates were assessed to identify cost and 

climate drivers. We then conducted sensitivity analyses to determine the effect of incremental 

changes in these drivers.

3.0 Results

The study provides rough-order cost and GHG emissions estimates for the RD1 (Innovative Heliostat 

Swarm) and RD2 (Mature Planar Array) SBSP systems broken down by ConOps phase: Develop, 

Assemble, Operate, Maintain, and Dispose. Cost estimates for each ConOps phase by system are 

shown in Figure 9. For a detailed table of costs please see Appendix B. Both systems have a ~2 

gigawatt (GW) capacity. The total estimated cost for each system is: RD1, $276B; and RD2, $434B. 

For both systems Maintain comprises over 50% of the overall cost. Assemble costs comprise about 

25% of total cost for both systems. The most impactful cost element is launch, representing 71% 

and 77% of total cost for RD1 and RD2, respectively. 

Dispose, Develop and Operate are, in descending order, the next most expensive phases, but 

combined are less than Assemble for each reference design. The largest costs in Develop are for 

research and development (R&D), manufacturing and integration of all spacecraft hardware and 

systems, and program support services. Costs in Operate are primarily in the ground system; RD2 

requires five ground rectennas where RD1 requires one. Dispose is unique in that it is the only 

ConOps phase where launch is included but is not the primary cost driver. For Dispose, the 

continuous operation of the Active Debris Removal (ADR) fleet for years is the largest cost. 
14

The total GHG emissions for each system are: RD1, 14B kgCO2eq.; and RD2, 21B kgCO2eq. A 

breakdown of emissions by ConOps phase and cost elements is shown in Figure 10. As is the case

with costs, Maintain, represents over half of each system’s GHG emissions, with Assemble

accounting for one quarter of the total. Similarly, the largest emissions across the SBSP lifecycle are 

attributable to the thousands of launches required, again highlighting launch’s disproportionate 

impact on SBSP systems. Access to space comprises 64% and 72% of total emissions for RD1 and 

RD2, respectively.

In descending order, Develop, Operate, and Dispose produce the most emissions after Maintain 

and Assemble. The largest contributors in these segments is large-scale manufacturing of SBSP 

spacecraft, servicers, and launch vehicles. The activity with the next largest emissions is associated 

with the ground support infrastructure and staff, including R&D and operations.

Figure 11 depicts the LCOE and GHG emissions of the SBSP reference systems alongside other forms 

of renewable energy. The baseline costs, estimated using the assumptions described in the 

methodology overview, are significantly higher than those for current renewables, while GHG 

emissions are comparable. This remains true even when storage requirements to achieve a similar 

“power on demand” – also known as “baseload power” – for solar and wind are taken into account. 

Energy storage must be considered for solar and wind because they cannot deliver power 

consistently throughout the day or year. The LCOE for space-based systems is significantly higher as 

terrestrial systems do not face the high costs of launch and assembly in space, and this first-of-akind system’s costs include R&D. 
15

Figure 9. Cost Estimates Results of ConOps Phases
16

Figure 10. GHG Emissions Estimates Results of ConOps Phases
17

Figure 11. SBSP Systems (Baseline) and Other Renewables

3.1 Summary of SBSP System Costs and GHG Emissions

The total cost for each system is: RD1, $276B; and RD2, $434B. The total GHG emissions for each 

system are: RD1, 14B kgCO2eq.; and RD2, 21B kgCO2eq.

The combined on-orbit mass of the five RD2 satellites necessary to deliver 2 GW of power is nearly 

twice that of the 1-satellite RD1 system (1000 metric tons (MT) versus 585 MT), increasing its 

overall cost. The primary mass-based cost drivers are related to launch and disposal. The ground 

system costs for RD2 are also greater as it requires five ground rectennas to receive the same 2 GW 

of power. The same holds true for GHG emissions, as the increased number of launches leads to 

higher emissions relative to RD1.

The major cost and GHG emissions driver for both systems is launching and manufacturing millions 

of tons of hardware, including robotic servicers for on-orbit assembly.

Our baseline assessment assumes lower costs and better capability in some areas compared to 

today, and status quo in others, as discussed in Section 2, Methodology Overview. Recent analyses 

by Frazer Nash (Frazer Nash Consultancy, 2022) and Roland Berger (GmbH, Roland Berger, 2022)

also make assumptions about the future state of technology and industry supply chains supporting 
18

notional utility-scale SBSP systems and have come out with much lower costs – LCOEs of $50-

70/MWh – than our baseline numbers. Refer to the Methodology section or Appendix B for a full 

accounting of assumed capabilities and costs. Sensitivity analyses of the primary cost drivers show 

how SBSP costs could be reduced to levels more comparable with those found in other studies.

4.0 Sensitivity Analyses

Given that the largest cost drivers for both systems are launch and manufacturing of spacecraft and 

servicers, we conducted sensitivity analyses to assess the impact of reduced launch costs and 

improved manufacturing learning curves. First, we examined individual variables; then we 

conducted a multiple-variable sensitivity analysis. Details of the sensitivity analyses are provided 

below, and in greater detail in Appendix B. Figure 12 shows the difference in total cost from each 

sensitivity analysis to the baseline assessment. 

4.1 Launch

4.1.1 Direct Launch to GEO

The baseline analysis assumes Starship launches 100 MT to LEO and is refueled on orbit to continue 

to GEO for system assembly. A Starship carrying 100 MT requires 12 refueling launches in LEO to 

continue to GEO, based on publicly available information about the initial human landing system to 

be developed by SpaceX and SME assessments. However, some Starship configurations are also 

capable of launching 21 MT direct to GEO. When launching directly to GEO, the number of launches 

drops from 2,321 to 863 for RD1 and from 3,960 to 1,470 for RD2. This decrease drops the LCOE of 

the RD1 and RD2 systems by 42% and 47%, respectively. This is assuming the cost per launch for a 

fully disposable or reusable Starship fleet is the same.

Direct launch to GEO yields only a marginal decrease in emissions, however, as the reduced number 

of launches is offset by the need to manufacture more vehicles because Starship vehicles launched 

to GEO cannot be reused. While all 863 direct-to-GEO missions for RD1 would be on single-use 

vehicles, for example, the 2,321 LEO launches required in the baseline assessment scenario could 

be carried out by just 199 individual vehicles. Direct launch to GEO saves about 2 and 4 gCO2eq. per 

kWh – or 8% and 9% – for RD1 and RD2, respectively.

4.1.2 Reduced Launch Costs

Launches for assembly and maintenance are the biggest driver of SBSP system costs. Baseline 

launch costs for Starship are set at $100M/launch, the current price of Falcon Heavy. If that price is 

dropped to $50M/launch, the LCOE decreases by about 36% and 39% for RD1 and RD2, 

respectively. At $10M/launch the LCOE drops about 64% for the RD1 and 70% for the RD2. The 
19

decrease is higher for the planar array concept because requires more launches to deploy and 

assemble.

Figure 12. Percent Decrease in LCOE from Baseline

4.1.3 Electric Propulsion Orbital Transfer

Scholars have proposed using solar electric propulsion (EP) for orbital transfer from LEO to GEO as a 

cost saving approach. In this sensitivity analysis, 1720kg of propulsion system mass is allocated per 

10,000kg of payload mass. We increased total hardware costs by 17.2% to account for the 

additional manufacturing cost of EP units. This approach takes advantage of launch vehicle 

reusability while eliminating refueling launches, lowering LCOE 63% for RD1 and 69% for RD2. 

Assuming EP specifications in line with NASA’s NEXT-C electric ion thruster (NASA, 2023), travel time 

from LEO to GEO increases from one month to four. 

Conducting orbital transfer with EP significantly reduces GHG emissions due to lower number of 

launches and fewer launch vehicles manufactured. The emissions decrease is about 54% for RD1 

and 63% for RD2, potentially bringing those systems in line with terrestrial wind without storage.
20

4.1.4 Spacecraft Hardware Life

The baseline hardware lifetime is assumed to be 10 years, requiring two refurbishment cycles to 

maintain operations for a 30-year SBSP system lifetime. Extending hardware lifetime to 15 years 

halves the number of maintenance launches, decreasing the cost of both systems by 26%. GHG 

emissions are reduced by 27% and 29% from baseline for RD1 and RD2, respectively, due to the 

reduction in rocket manufacturing and launches.

Figure 13. Percent Change in GHG Emissions Intensity from Baseline

4.2 Manufacturing

4.2.1 Initial Hardware Costs

The baseline cost estimates assume current hardware costs. Given the timeframe of SBSP 

development and deployment, hardware costs are likely to be lower, though we make no claim that 

the following changes represent any kind of prediction. For this sensitivity analysis, first-unit 

hardware costs were decreased 90%: The first SBSP system module’s cost went from $1M to 

$100,000; the first servicer’s cost from $1B to $100M; and the first ADR vehicle’s cost from $500M 

to $50M. These values are in line with The Aerospace Corporation’s survey of current commercial 
21

on-orbit servicers. These reductions in hardware costs reduced LCOE by about 25% for RD1 and 18% 

for RD2.

GHG emissions are decreased about 27% and 20% for RD1 and RD2, respectively, (Figure 13) 

because the EIO-LCA model assumes a relationship between cost, efficiency, and reduced 

emissions.

4.2.2 Learning Curve

Given the size of the systems and millions of modules required for each, manufacturing is one of 

the largest costs represented in the development segment of the ConOps. The baseline learning 

curve used is 75% for units of SBSP system hardware, 85% for servicers, and 90% for ADR vehicles. If 

we improve the learning curve by 5 percentage points for each, LCOE drops by about 10% for RD1 

and 8% for RD2. 

GHG emissions are reduced about 15% for RD1 and 11% for RD2 (Figure 13), again, because the EIOLCA model assumes a relationship between cost, efficiency, and emissions.

4.2.3 Solar Cell Efficiency

Increasing the efficiency of solar cells decreases the size and mass of a space solar power system 

required to create the same output power. This decrease in size affects both hardware 

development and assembly costs. The LCOE reduction achieved by increasing solar cell efficiency 

from 35% to 50% is about a 25% for RD1 and 26% for RD2. The 50% figure represents the highest 

efficiency of terrestrial research cells tracked by NREL today (NREL, 2023).

The size and mass reduction leads to less manufacturing and fewer launches, cutting each system’s 

assessed GHG emissions per kWh by 23% for RD1 and 27% for RD2. This sensitivity analysis does not 

consider the mass changes that would occur from use of different photovoltaic technologies. For 

example, silicon and perovskite cells are made of different materials, and manufactured differently.

4.3 Combining Sensitivities

Combining select conditions from the sensitivity analyses can lead to a cost-competitive SBSP 

system. The rationale for these choices is presented in the following section. In the “combined” 

sensitivity, we modified key input variables accordingly: 

• Launch costs reduced from $100M or $1000/kg (with 15% block buy discount, $85M or 

850/kg) to $50M or $500/kg (with 15% block buy discount, $42.5M or $425/kg)

• Solar cell efficiency increased from 35% to 50%

• Servicer and ADR first-unit cost reduced from $1B to $100M and $500M to $50M,

respectively

• Learning curves improved by 5 percentage points across the board
22

• Hardware lifetime extended from 10 to 15 years

• Instead of the LEO-refueling deployment scenario, ConOps uses EP for orbital transfer, 

adding 17.2% more mass and cost to SBSP system hardware

Under these conditions, total system costs decrease by 95% and 93% for RD1 and RD2, respectively.

GHG emissions decrease by nearly 86% and 89% for RD1 and RD2, respectively. These conditions 

would make SBSP systems highly competitive with any assessed terrestrial renewable electricity 

production technology’s 2050 cost projections and 2021 emissions intensity. The effects of these 

changes to first-order cost and emissions estimates are shown in Table 3.

Table 3. Baseline versus Combined Sensitivities LCOE and GHG Emissions

Sensitivity LCOE ($/kWh) GHG Emissions Intensity

(gCO2eq./kWh)

Baseline

RD1 0.61 26.58

RD2 1.59 40.38

Combined 

Sensitivities

RD1 0.04 3.87

RD2 0.08 4.33

4.4 Making SBSP Systems Competitive with Terrestrial Renewables

As seen in Figure 11, under the baseline assumptions neither SBSP system is cost competitive with 

other renewables. The costs of launch for in-space assembly significantly affect the LCOE of these 

systems, putting them far beyond the costs of terrestrial solutions. SBSB still would not be costcompetitive with alternative renewables even if access to space were free, assuming all else 

remains constant. A cost-competitive SBSP solution does emerge, however, if launch costs drop to 

$50M/launch, solar cells achieve 50% efficiency, costs for a commercial servicer decrease to 

$100M, learning curves improve by 5%, hardware lasts 15 years, and EP is used for the orbital 

transfer of payloads to GEO. Below, we briefly discuss the likelihood of these sensitivities:

• Launch cost: Launch costs per kilogram have decreased 36% over the last 10 years. If that 

continues, they could reach ~$60M per 100 MT (the assumed Starship payload capacity) in 

2040. Note this cost is still 30 times greater than SpaceX’s desired launch cost of $2M per

Starship launch.

• Solar cell efficiency: According to NASA’s assessment (NASA, 2022), the state of the practice 

of solar cell efficiency in space today is 33%, while the state of the art is 70% (based on 

theoretical limits of 6-junction solar cells in laboratories today). Similarly, while state of the 

practice solar cell efficiency on Earth today is about 20%, laboratory solar cells can reach 

efficiencies of 50% (Center for Sustainable Systems, 2022) (NREL, 2023). For comparison, 

the highest recorded solar cell efficiency in 2011 was 27.6% (Radiative efficiency of state-of-
23

the-art photovoltaic cells, 2012). For every alternative solar cell technology however, a full 

design review would be needed to assess lifecycle effects on mass, cost, and emissions.

• Servicer cost: The Aerospace Corporation’s survey of commercial offerings for in-space 

servicing, assembly, and manufacturing (ISAM) capabilities yielded a range of $75M-$750M, 

suggesting $100M may be possible in the next 15 years.

• Learning curve: Manufacturing learning curves in other industries range from 108% to 54%, 

though 80-82% is most common (Aerospace, 2018). For satellite manufacturing, The

Aerospace Corporation estimated learning curves after reviewing manufacturing industries, 

including satellite manufacturing (Meisl & Morales, 1994). 

• Hardware lifetime: The standard lifetime for GEO satellite hardware is currently 15 years.

• EP orbital transfers to GEO: These maneuvers have been conducted for over a decade

(Boeing, 2012), and first order delta v calculations with state-of-the-art performance 

suggest feasibility at scales required, though the mass and configuration may require 

further assessment.

Figure 14. SBSP Systems Sensitivities Compared to Other Renewables
24

Using baseline assumptions, the SBSP systems assessed perform competitively on GHG emissions

when compared to terrestrial forms of renewable electricity production. It is important to note, 

however, that the effects of burning rocket fuel in the upper atmosphere are not yet quantified by 

science (NOAA, 2022), but widely assumed to be much worse than burning these fuels on the 

ground. Given the large number of launches required, we would expect the measurable impacts of 

these systems to rise as we learn more. Manufacturing at scale for these massive systems and 

thousands of launches of rockets using methane-oxygen fuels produce the most GHG emissions. 

Options to reduce GHG emissions: 

1. Reducing the number of launches by using EP for orbital transfer, deploying the system at a 

lower altitude, or using non-combustive launch technologies (e.g. spin launch or magnetic 

launch) would reduce launch related emissions. Fewer launches also would reduce the 

environmental footprint associated with launch vehicle manufacturing, even taking 

reusability into account.

2. Although the baseline assessment assumes autonomy is fully developed, it is important to 

note the significant reduction in emissions this provides during assembly and operations.

3. On-orbit manufacturing of photovoltaic arrays and other components would remove 

manufacturing emissions that would otherwise occur on Earth.

4. Any technologies that reduce the mass of an SBSP system would reduce both the launches 

and manufacturing required to build, assemble, and maintain the system.

5.0 Challenges and Opportunities 

Fielding either of the two SBSP reference designs analyzed in this report will require major 

capability advances in three key areas: 1) ISAM, 2) autonomous distributed systems, and 3) power 

beaming.

5.1 Challenges to Operational System Development

Across all technology areas, the single most distinguishing factor is the sheer scale of operations, 

mass, and coordination required to deploy systems larger and more massive than anything built in 

space before, except perhaps the combined mass and area of very large satellite constellations. 

5.1.1 Large-scale ISAM Capability Challenges

ISAM capabilities required for developing and operating an SBSP system (ConOps Assemble and 

Maintain phases) are not currently available. There are few existing commercial capabilities for 

activities such as assembly, refueling, in-space manufacturing, and formation flying. The market for 

ISAM is unproven, with many proposed technologies as yet untested in space. The ISAM business 

case has development and operational risks that may limit private investment. Unless the 

Government steps in to support this nascent industry, services will be limited and expensive. 
25

Without robust ISAM capabilities, the Assemble, Maintain, and Dispose ConOps phases will be 

significantly slower and more expensive, especially when assembling a solar panel collection area 

measuring 19km2, like that of RD2.

5.1.2 Large-scale Autonomous Distributed Systems

Autonomy is making significant advances today, both terrestrially and in space. On-orbit capability, 

however, is closer to automation (executing preprogrammed actions) than autonomy (independent 

decision-making onboard a system), as seen in the collision avoidance capability of largeconstellation satellites in orbit today. For SBSP, collaboration between multiple autonomous 

systems working across kilometers of space may be required to achieve cost targets. While this 

could theoretically be preprogrammed into automated commands instead of independent decisionmaking on satellites, either approach is still well beyond anything ever attempted. With today’s 

technology, remote operators would be required for at least some operations, making assembly 

labor intensive and more time consuming than is assumed in this study’s baseline assessment.

5.1.3 Power Beaming

Power beaming is a technical challenge that was not discussed as part of the sensitivity analyses. 

Power beaming from space was first demonstrated in June 2023 (Caltech, 2023), though at a scale 

that is orders of magnitude below what is baselined for the systems studied in this report or 

proposed elsewhere. Significant advances are needed before commercial-scale SBSP powerbeaming systems would be technically feasible. 

5.2 Challenges to Reducing System Costs

As discussed in Section 3, Results, the reference design systems are far more expensive than and 

may have comparable GHG emissions to terrestrial renewable alternatives. The sensitivity analysis 

section of this report showed that both costs and emissions may be reduced through advances in 

technology and access to space. However, many of these technologies are still in development as 

described in this section. 

Every element of the SBSP ConOps has significant cost challenges. These challenges are associated 

with the sheer scale of the manufacturing effort as well as the number of launches required. They 

could be mitigated through manufacturing and launch efficiencies, or both.

5.2.1 Launch costs

High space transportation costs are the single most impactful cost barrier. Launch costs affect every 

in-space element, from SBSP system construction and maintenance to ISAM capabilities like 

refueling and assembly. 
26

Analysis shows (BryceTech, 2022) that the average launch price per kilogram of payload dropped by 

36% from 2013 to 2022. Our baseline assessment assumes launches begin around 2040 to assemble 

the SBSP system in orbit. If the current rate of decline continues – today’s lowest price is $1,500/kg 

– launches would cost $615/kg in 2040, or $61.5M for the 100 MT each Starship delivers to LEO. 

This is still higher than the $50M figure we used for our multiple-variable sensitivity analysis. 

As previously noted, the exact climate impact of burning rocket fuel in the upper atmosphere is 

unknown, but widely assumed to be worse than burning an equivalent amount of fuel on the 

ground (NOAA, 2022).

5.2.3 Manufacturing at scale

To lower the manufacturing cost of SBSP infrastructure, it is important to achieve economies of 

scale. Mass production has driven down the cost of mega-constellations, making the services 

offerings of Starlink (SpaceX, 2023) and OneWeb (OneWeb, 2023) price competitive for consumers. 

SpaceX reportedly produced 120 satellites and thousands of terminals per month during 2020, an 

unprecedented rate in the industry (Sheetz, SpaceX is manufacturing 120 Starlink internet satellites 

per month, 2020). In the SBSP Develop phase, to lower module manufacturing costs, scaled 

manufacturing will be required with significant upfront capital expenditure. 

Despite significant advances in mass manufacturing of satellites, learning curves and costs have not 

come down to the level needed for the scale required to support SBSP system development. 

Findings from this report and supporting research suggest the industry needs to reach annual 

production of at least thousands of satellites to reach the learning curves described in this 

assessment. High hardware manufacturing costs therefore remain a barrier in the Develop phase. 

5.2.4 Launch cadence

Launch cadence affects the cost and schedule of SBSP systems. The baseline assessment assumes 

two dedicated SBSP launches per week, or 104 per year. For comparison, global launches in 2022 

set a new record with 186 (BryceTech, 2023). Currently there are no plans to expand launch 

capacity to the degree required to support our assumed SBSP launch cadence. 

It is also important to note that while Starship provides far greater payload capacity than existing 

operational vehicles and is assumed in the baseline assessment to be somewhat cheaper per 

kilogram, it has unique ground system requirements that limit its launch capacity. To meet our 

baseline assumption of 104 launches per year, Starship would require five to 10 times its current 

ground support infrastructure, all dedicated to SBSP. This may not be possible given competing 

needs for Starship from other customers. 
27

5.3 Regulatory and Other Challenges

There are non-technical issues with SBSP that may prove challenging, such as debris remediation, 

spectrum allocation, orbital slots, and security.

5.3.1 Active Debris Removal

SBSP is both vulnerable to space debris and a contributor to space debris. While some debris 

shielding is assumed in this study’s assessment, it is unlikely to provide sufficient protection, and an 

SBSP system is unlikely to have sufficient warning and maneuverability to avoid collisions with space 

objects. This would lead to a risk of cascading debris creation and must be mitigated. Moreover,

there likely are risks associated with moving a retired SBSP system into a super-GEO graveyard 

orbit. Moving the debris closer to Earth for disposal would also present risks and costs. The baseline 

assessment assumes disposal in a graveyard orbit, but this is not necessarily the best course of 

action. On-orbit industrial capabilities that could recycle debris are not available today, nor is their 

future availability assured.

5.3.2 Spectrum Allocation

Radio spectrum is a finite resource that requires coordination with the International 

Telecommunication Union (ITU) and is subject to both international and domestic regulation. SBSP 

transmissions from GEO may cause interference with other systems, especially those operating LEO. 

Uncertainties remain about what frequencies a future commercial-scale SBSP system will operate in 

and what technologies will be available to allocate popular frequency ranges to SBSP operations. 

There are additional concerns about the warehousing of, and competing interests in, radio 

frequencies. Research is required to better understand how SBSP transmissions might affect other 

satellites, particularly those operating in lower orbits. 

5.3.3 Orbital Slot Allocation 

The ITU also allocates orbital positions for GEO satellites. Just like spectrum, orbital slots are 

increasingly contested (Gangestad, 2017). Coordination is required, necessitating prior planning to 

secure orbital slots for SBSP missions. The larger the SBSP system, the greater the challenge. 

5.3.4 Security

While not unique to SBSP systems, security concerns will have to be addressed. Space systems and 

critical infrastructure like power plants have security requirements, and an SBSP system would need 

to consider all of these risks. Cybersecurity may be of particular concern for highly autonomous and 

distributed systems.
28

5.4 Ongoing Improvements to SBSP Technology Needs

Most SBSP challenges and opportunities are shared by the global space sector. There are ongoing 

efforts to leverage emerging opportunities and industry trends to address many of these 

challenges. Below we discuss some representative examples.

5.4.1 ISAM 

Large-scale ISAM capabilities are necessary to achieve the baseline scenario assumed in this study. 

ISAM capabilities not only enable the reference designs reviewed; they also reduce the cost of 

assembly, operations, and maintenance, while also supporting disposal and debris remediation.

In the U.S., the Government and private sector are working to advance ISAM technology. The Office 

of Science and Technology Policy’s (OSTP) National ISAM Strategy and Implementation Plan guides 

interagency objectives (United States National Science and Technology Council, 2022). The baseline 

assessment servicer price and mass are derived from NASA’s On-orbit Servicing Assembly and 

Manufacturing (OSAM)-1 mission and Northrop Grumman’s Mission Extension Vehicle (MEV)

because of the detail of publicly available information. Northrop Grumman (Northrop Grumman, 

2023) provides in-orbit GEO satellite servicing using the MEV. Other commercial actors are also 

offering ISAM services. Servicer price in select sensitivity analyses is derived from alternative 

offerings. OrbitFab (OrbitFab, 2023) is offering hydrazine refueling services in GEO for $20M and KMI 

(Kall Morris Inc., 2023) has offered debris removal services at costs ranging from $4M to $62M. These 

prices are much lower than the baseline assumptions used in this study. Several startups are working 

on SBSP (Kirschner, 2023) concepts that would leverage ISAM technology. For example, in 2023, 

Orbital Composites and Virtus Solis announced a memorandum of understanding (MOU) for 

development of an SBSP system. Many more startups are working on ISAM specifically, as seen in 

the case of the U.S. Air Force Research Laboratory’s SpaceWERX Orbital Prime program, which 

awarded ISAM-related contracts to 124 companies in 2022 (Holt, 2022). 

5.4.2 Autonomous Distributed Systems

ISAM capabilities are, in most cases, leveraging autonomy at the system level. SBSP also requires a 

large number of satellites working together. Autonomous distributed systems and formation flying 

technologies that currently exist for military and aviation applications can be applied to support 

SBSP systems. NASA efforts including the Distributed Spacecraft Autonomy project (NASA, 2020), 

along with the deployment of very large satellite constellations, are advancing this critical SBSP 

technology. 

5.4.3 Power Beaming

Power beaming technology is being pursued by many organizations globally. Like other activities 

benefiting SBSP, power beaming is not only being pursued for SBSP; power beaming on Earth has 
29

been demonstrated many times and in-space power beaming was demonstrated by the Naval 

Research Lab (NRL) in March 2023 (Hamisevicz, 2023). Beaming from space to Earth was first 

demonstrated in June 2023 (Caltech 2023), at a very small experimental scale. 

There is additional active U.S. federal research aimed at developing advanced power beaming 

capabilities. The Defense Advanced Research Projects Agency (DARPA, 2022) Persistent Optical 

Wireless Energy Relay (POWER) program is focused on power beaming for terrestrial applications, 

while the Air Force Research Laboratory (AFRL) is developing an in-space power beaming 

experiment. NASA’s efforts are currently focused on research rather than technology development, 

examples being the NASA Innovative Advanced Concepts (NIAC) Low TRL concept for power 

beaming on Venus (Brandon, et al., 2020) and Lunar Surface Technology Research (LusTR) Beamed 

Lunar Power on the Moon concept (Lubin, 2021). 

Other countries, such as Japan and South Korea, are working on power beaming. Japan (Kawahara, 

2023) plans to test beaming energy from space to Earth in 2025, for example. International 

collaboration could speed up development of key SBSP technologies. 

5.5 Ongoing Improvements to SBSP Economic Needs

It is important to note the significant overlap between technical and economic opportunities as 

they relate to SBSP. These technologies, while not directly required for SBSP operation, would make 

SBSP more cost effective.

5.5.1 Electric Propulsion Orbital Transfer

Using EP to transport SBSP payloads from LEO to GEO will significantly decrease the number of 

launches, in turn decreasing overall system cost as well as GHG emissions. EP for orbital transfers is 

a proven technology in use by GEO satellite operators seeking to reduce launch costs in exchange 

for a longer travel time (de Selding, 2013) (Werner, 2018). However, there is no history of moving 

so much mass from LEO to GEO and this may require EP capabilities that do not exist today. 

Currently, several companies have small space tugs with EP, such as Spaceflight’s Sherpa-LTE Orbital 

Transfer Vehicle (OTV), Starfish Space’s Otter, Momentus’ Vigoride, and Atomos Space’s Proton and 

Quark OTVs. Exolaunch’s Reliant eco-friendly space-tug vehicle has a “Pro” version that combines 

electric and green propulsion. Sherpa-LTE by 2022 had achieved its 300th on-orbit burn. These tugs 

are sized for satellites that have two orders of magnitude less mass than could be launched by a 

single Starship rocket. Hybrid electric and chemical OTVs were not explored in this study but could 

offer a faster solution that is not significantly worse for the environment than conventional 

chemical systems.
30

5.5.2 Alternative Launch

Some alternative launch technologies in development may lead to significant cost reductions. 

Multiple companies are researching kinetic launch, for example. SpinLaunch (SpinLaunch, n.d.) has 

a Space Act Agreement with NASA and Longshot Space (Longshot Space, n.d.) is performing work 

for the Air Force under its Small Business Innovation Research program. Given existing mass 

limitations, these approaches would only apply to modules and not servicers, and it remains to be 

seen whether kinetic launch will be successful and achieve promised cost reductions.

5.5.3 Mass Manufacturing

Advances in mass manufacturing would benefit SBSP, certainly the multi-million-module designs

examined in this study. Mass manufacturing, as seen with Starlink and OneWeb satellites, may 

reduce space hardware production costs in general, potentially benefitting unrelated space 

manufacturing activities, including SBSP. While manufacturing does tend to improve with 

experience, and the scale of SBSP constitutes significant experience, we cannot assume that this will 

be the case until it happens.

5.5.4 Advanced Materials

Advances in materials could lead to significant mass reductions, whether from the material itself or 

new design optimizations. NASA has invested in several relevant projects, such as Lightweight 

Materials and Structures (NASA, 2020) and Superlightweight Aerospace Composites (NASA, 2022). 

Novel materials may be more expensive until production scales, which may limit their applicability.

5.6 Architecture Opportunities

This study did not assess the potential of novel architectures. However, improvements and new 

designs currently being studied may lead to lower costs or higher efficiency. These opportunities 

may change SBSP ConOps and introduce significant cost reduction. In the baseline estimate, launch 

costs represented one third and half of total costs for RD1 and RD2, respectively. Caltech has 

explored deployment of a medium Earth orbit (MEO) constellation of SBSP satellites (Marshall, 

Madonna, & Pellegrino, 2023). Incorporating Caltech’s 2022 analysis of a MEO constellation’s 

efficiency into this study’s cost and climate model would provide a more complete picture of SBSP 

system efficacy. 

6.0 Options for NASA to Consider

In this section, we present options for NASA senior leaders regarding the Agency’s role in the 

worldwide acceleration of SBSP development activity. This data may provide decision-makers with a 

basis to reassess existing policy. The two options discussed below are not mutually exclusive; NASA 

may elect to pursue both paths.
31

Our research indicates NASA is developing technologies with broad applicability to a wide suite of 

future mission needs and enable SBSP as well. However, we view SBSP as a use case for these 

technologies, not a driver for NASA’s development programs. We recommend that NASA stay 

abreast of outside SBSP developments and requirements as it matures the technologies needed for 

its missions. NASA could maintain its awareness in part by repeating this study at different scales of 

effort every three to five years.

6.1 Option 1: Undirected and Organic Development

NASA is currently developing technologies and capabilities that have applicability to SBSP, such as 

ISAM, autonomy for distributed systems, and power beaming, though these investments vary 

greatly. ISAM and autonomy have dedicated technology development programs while NASA-funded 

power beaming work today is limited to paper research. Continuing to invest in these capabilities, 

even while taking no new action, will make SBSP systems more technically feasible in the future. 

NASA should continue to monitor and maintain awareness of ongoing developments in SBSP. This 

option does not require any changes to NASA’s budget allocations.

6.2 Option 2: Pursue Partnership Options to Advance SBSP

Our work has shown there are multiple entities in the U.S. and abroad pursuing capabilities for 

which SBSP is a use case. This presents partnership opportunities. Specifically, NASA could become 

an SBSP technology development partner with other U.S. Government agencies, industry, 

academia, or international organizations. NASA could focus such partnerships on technologies with 

high-impact potential for the Agency’s missions.

We identified several scalable opportunities for NASA to enter into strategic partnerships based on 

the level of technology maturity and funding availability. The list of examples below is not intended 

to be comprehensive, nor are the identified opportunities mutually exclusive.

1. Support other U.S. Government efforts.

a. AFRL and DARPA are advancing power beaming technologies. 

b. DoE has several relevant power and infrastructure programs.

2. Support international efforts.

a. ESA, Japan, Australia, and South Korea are U.S. allies and have ongoing government 

investments to develop SBSP technology.

b. NASA could support ESA’s interest in developing SBSP for net zero.

3. Explore novel public-private partnership opportunities in SBSP.

a. A joint NASA-DoE study is recommended as a first step to inform such public-private 

partnership opportunities.
32

b. Given the existing commercial interest and activity in developing the necessary 

technologies, NASA and DoE could jointly assemble a consortium to support and 

guide maturation of these technologies.

c. Given that many more commercial companies are developing SBSP-relevant

technologies for non-SBSP applications, such as power beaming and solar cell 

advances, we recommend collaboration with DoE and industry. 

d. NASA could hold challenges and workshops to improve designs and develop better 

understanding of the required development paths. 

e. NASA could advocate for the U.S. Government to create public-private entity with 

NASA as one of several Government shareholders to guide the development and 

implementation of SBSP.

7.0 Conclusion and Recommended Further Study

Our first-order assessment has shown that two notional SBSP systems, using existing or near-term 

technology, are very expensive but may produce GHG emissions comparable to existing renewable 

electricity production technologies. Some major drivers of cost and GHG emissions for SBSP include 

launch, space hardware manufacturing, disposal of massive satellites, and in-space assembly of 

large systems. However, our sensitivity analyses demonstrated that there are ways to significantly 

drive down the cost and emissions of SBSP systems. Specific opportunities that could also benefit a 

wide range of future NASA missions include using EP for transfer to the desired orbit, significantly 

decreasing the cost of access to space, improving solar cell efficiency, and improving manufacturing 

learning curves. A combination of such improvements would make SBSP systems competitive with 

other renewable energy systems on both cost and GHG emissions metrics. 

Our work identified several policy and technology challenges that would need to be addressed to

advance SBSP. While these challenges are not unique to SBSP systems, the scale required to fully 

implement an SBSP system requires forethought. We therefore recommend that NASA conduct 

follow-on assessments on the following items:

1. More detailed technical evaluations of SBSP – SBSP would benefit from a more detailed 

analysis of: 1) lifecycle cost and GHG emissions, as performed by NREL on other electricity 

production technologies; and 2) exploration mission applications of SBSP in the form of a

cost benefit analysis and a detailed NASA technical design trade evaluation. The latter may 

also consider emerging partnership efforts for in-situ resource utilization, such as NASAfunded work to produce solar cells on the Moon (NASA, 2023). 

2. Regulatory Challenges – SBSP faces several regulatory hurdles, including spectrum 

allocation, orbital slots, and launch approvals, that will need to be addressed given the 

competition for these limited resources and the complexity of proposed SBSP systems. 
33

Further analysis is required to understand how regulations could impact the feasibility of 

SBSP systems and how NASA should work with the relevant regulatory bodies. 

3. Policy Challenges – Several policy implications could impact SBSP deployment. The most 

notable concern is the safety of power beaming. In addition, the anticipated number of 

launches for assembly and refueling introduce orbital debris concerns at a time when many 

nations are looking to reduce their orbital footprint. Cybersecurity is also a significant 

concern.

4. Industrial Base and Supply Chain – The scale of the SBSP reference designs would aggravate 

industrial base and supply chain hurdles, including raw material and skilled workforce 

availability, that are common to all space missions. Our work did not assess whether the 

aerospace industry can realistically support the level of effort required for SBSP and what 

changes, if any, would be required to support this demand.

5. Launch Cadence – Our study assumed SpaceX’s advertised Starship launch cadence, but how 

realistic that is remains to be seen. Nor is it clear how many of those flights would be 

available to launch an SBSP system. Additional analysis should be done on the feasibility of 

SBSP under multiple launch-cadence scenarios, in part to determine the minimum cadence 

required to deploy a system in the desired timeframe. The analysis may also consider the 

realism of SpaceX's planned launch cadence. 

6. Propulsion – EP is cleaner but slower than chemical propulsion. However, advances are 

being made in EP technologies that may reduce the timeline to assemble an SBSP system. 

We recommend monitoring these advances to determine whether they make EP a more 

feasible option for SBSP.

7. Efficiencies of Scale – Our analysis looked at the costs to get to the first full-scale system in 

place, but did not consider whether efficiencies would be realized over time as additional 

SBSP systems are deployed. Additional analysis should be conducted to assess whether 

there are opportunities to lower the costs of future SBSP systems once the initial capability 

is demonstrated.
34

Figure 15. SBSP System Cost and GHG emissions with Sensitivity Analyses and Terrestrial Alternatives.
35

Appendix A: Representative Design Details

Two design references were assessed in this study: Representative Design One (RD1) or "Innovative 

Heliostat Swarm" and Representative Design Two (RD2) or "Mature Planar Array." Both designs are 

assembled and operate in GEO. The Aerospace Corporation assessed each of the design references 

based on source materials. NASA updated elements of these designs with more recent technical 

data, as seen in the tables below, and scaled the systems to each deliver about 2 GW of power to 

the grid. Both systems operate in geostationary orbit. Details on the concept of operations and 

attendant calculations are provided in Appendix B.

Innovative Heliostat Swarm is broadly derived from the Alpha Mark III concept (Mankins, SPS-Alpha 

Mark-III and an achievable roadmap to space solar power, 2021). This design uses reflectors and a 

concentrator to focus sunlight throughout each day. 

Mature Planar Array is broadly derived from the Japan Aerospace Exploration Agency (JAXA) Tether 

and Caltech SSPP design (Sasaki, A new concept of solar power satellite: Tethered-SPS, 2006), 

(Sasaki, Demonstration Experiment for Tethered-Solar Power Satellite, 2009), (Pellegrino, 2022). 

This design uses flat panels, with solar cells facing away from the Earth and radiofrequency (RF)

emitters facing toward the Earth. This design has a lower capacity factor due to limited capability to 

reposition itself or redirect sunlight toward its solar cells. 

This study did not fully account for the changes in the Sun’s position over the year, or how multiple 

RD2 systems in orbit may increase the capacity factor of the entire architecture. Multiple systems 

would increase the capacity factor; however, landmass on the Earth does not allow for even 

distribution across the day-night cycle, because much of the equator is underwater. This study is 

concerned with comparing representative examples of SBSP. Others may take the model developed 

for this study to further develop their own, more detailed analyses.

The Aerospace Corporation provided data and analysis in the form of interim reports, a

methodology paper, and spreadsheet.
36

Table 4. System Specifications as Applied in this Study

Space-Based Segment

Functional 

Step Parameter RD1 RD2 Source

Collect

Distance to Earth surface (km) 35,786.00 35,786.00 Mankins, Sasaki

Scaling factor 0.77 5

Solar panel size (km2) 11.473 19 Mankins, Sasaki

Solar panel surface area (m2) 11,473,000.00 19,000,000.00 Calculated

Solar Constant (w/m2) 1,367.50 1,367.50 NASA

Incident solar energy (MW) 15,689.33 25,982.50 Calculated

Illumination Secondary reflector 

array ~2-3 suns

No additional optical 

array 1 sun Mankins, Sasaki

Solar Cell Efficiency 0.35 0.35 Rodenbeck et al.

Convert in 

Space

DC to DC Conversion 

Efficiency 0.9 0.9 Rodenbeck et al.

DC to RF Conversion 

Efficiency 0.7 0.7 Rodenbeck et al.

Transmit

Antenna Emission Efficiency 0.9 0.9 Rodenbeck et al.

Atmospheric Travel Efficiency 0.98 0.98 Rodenbeck et al.

Beam Collection Efficiency 0.95 0.95 Rodenbeck et al.

RF frequency (GHz) 2.45 5.8 Mankins, Sasaki

Ground-Based Segment

Functional 

Step Parameter RD1 RD2 Source

Receive

Rectenna Array Reception 

Efficiency 0.78 0.78 Rodenbeck et al.

Diameter ground rectenna 

(km) receptor 6 4

Inferred from 

Mankins, Sasaki

Convert on 

Ground

DC to DC Conversion 

Efficiency 0.9 0.9 Rodenbeck et al.

Deliver

Capacity factor (% of year 

generating power) 0.997 0.6 Mankins, Sasaki

Power delivered (MW) 2028.791344 2021.948467 Rodenbeck et al.
37

Appendix B: Methodology

Figure 16. Cost Calculations for SBSP Systems 

This appendix describes the approach to determining cost calculations for two representative 

space-based solar power designs—Representative Design One (RD1), the Innovative Heliostat 

Swarm, and Representative Design Two (RD2), the Mature Planar Array—and the methods of 

estimating their GHG emissions. 

We describe the methodology in terms of the logical flow of each piece of the analysis. After a brief 

methodology overview, we proceed with sections as follows: 

• Approach to Cost Calculations: This describes the functional decomposition of each system,

details system costs by ConOps phase, and calculates the levelized cost of electricity (LCOE)

for each system using determined capital expenditures and fixed operations and

management costs. This also includes a breakdown of all relevant parameters and outputs,

or results.

• Approach to GHG emissions Calculations: This includes an Economic Input Output Life Cycle

Assessment to estimate emissions and a comparison to other sources of renewable energy

technologies.

• Sensitivity Analyses: This describes alternate considerations that may have significant

effects on lifecycle costs, including modified parameters, rationale, and effects on cost and

GHG emissions.
38

Overview

The Aerospace Corporation was tasked by NASA’s Office of Technology, Policy, and Strategy (OTPS) 

with conducting an Analysis of Alternatives to evaluate SBSP systems and inform NASA leadership 

on their costs and benefits as compared to other sustainable energy sources. Aerospace considered 

two systems — SPS-ALPHA Mark III and the Tethered Solar Powered Satellite — reviewed source 

documentation for each system, considered representative design reference systems for 

comparison, and decomposed each into modular components. To summarize each design reference 

system: 

• The Innovative Heliostat Swarm is broadly derived from the SPS-ALPHA Mark III concept 

(Mankins, SPS-Alpha Mark-III and an achievable roadmap to space solar power, 2021). This 

design reference is a lower TRL modular design that can generate power for 99.7% of the 

year because of its concentrator and reflectors. The Mankins concept proposes that one 

system, with a mass of 7,500 MT, is capable of delivering 2 GW to one ground-based site. 

• The Mature Planar Array is broadly derived from the JAXA Tethered Solar Power Satellite 

design: (Sasaki, A new concept of solar power satellite: Tethered-SPS, 2006), and updated 

with elements of Caltech’s SSPP design: (Pellegrino, 2022). This is a relatively higher TRL 

concept consisting of a large panel and a bus system. One system can generate power for 

60% of the year. The Sasaki concept proposes that each system, with a mass of 20,000 MT, 

is capable of delivering an average of 0.75 GW (and 1.2 GW maximum) to one ground-based 

site, while the 2023 in-space demonstration of Caltech’s technology suggests a design with 

less mass is possible. 

Aerospace assessed overall system specifications and made informed assumptions about 

information that was not available in the source material. Sources describe their systems as 

modular in nature; however, they have different module mass and size assumptions for each 

subsystem. To simplify calculations, Aerospace decomposed the SBSP systems into modular 

hardware units. The mass of one of these modular hardware units is derived by the ratio of each 

SBSP subsystem’s mass to the total SBSP system mass (power, structure, attitude and 

determination control, propulsion, telemetry tracking and command, command and data handling, 

and thermal). Other spacecraft hardware assessed was not divided into modular units, and include 

servicer spacecraft and active debris removal spacecraft. Aerospace assessed the research, 

development, deployment, operation, and disposal of SBSP systems based on NASA cost modeling 

work breakdown structure (WBS) elements. Aerospace then used a combination of proprietary 

models and NASA models to calculate fiscal costs in a combination of statistical and parametric 

methods. Final costs were provided according to the following WBS: space hardware, land use, 

ground receiver of SBSP systems, access to space, orbital assembly, operations of the space 

segment, maintenance of the space segment, and debris mitigation. 
39

These inputs were taken by NASAOTPS and validated with another model using 87 parameters (not 

including separate calculations for manufacturing learning curves, first order delta v, or assembly 

schedule). NASA OTPS applied specific decompositions of SBSP system functions and ConOps 

phases. The six functions are: collect, convert, transmit, receive, convert, and deliver. The five 

ConOps phases are: develop, assemble, operate, maintain, and dispose. NASA OTPS further 

modified, decomposed, and reorganized Aerospace data into these six functions and five phases, 

representing 87 parameters. The functions provided key inputs to electricity generation and 

delivery, while the phases provided key inputs to deriving the cost of SBSP systems. 

To assess the SBSP systems’ GHG emissions, NASA OTPS performed an Economic Input Output Life 

Cycle Assessment (EIO-LCA). This method is based on aggregate sector-level economic data. By 

adding environmental impact data to quantified direct and indirect economic inputs of purchases, 

environmental implications for select economic activity is derived. We use a mix of mass- and 

spend-based assessments, preferring mass wherever possible. The International Aerospace 

Environmental Group compiles EIO-LCA data from various sources (Carnegie Melon, DoD, and 

more). A key limitation of the EIO-LCA method is the assumed relationship between cost, efficiency, 

and GHG emissions; wherever possible, we used mass-based measures.

Aerospace provided data and analysis, including rationales for their methodologies, to NASA OTPS. 

To address the two questions in this study, we (OTPS) leveraged the data provided by Aerospace 

and performed an analysis to independently validate ConOps elements (such as orbital transfer and 

assembly times) and cost outputs for each design reference system and to estimate the GHG 

emissions of developing and operating each system. We also gathered data from authoritative 

sources on other electricity production technologies for comparison with the two design reference 

systems, primarily from NREL. We conclude with sensitivity analyses to explore potential effects on 

SBSP system costs of modifying parameters which could reasonably vary. The following sections 

detail our approach to cost calculations, GHG emissions, and methods to support sensitivity 

analyses. See Table 5 for a summary of our approach to the calculations.
40

Table 5. Analysis and Calculations Flow

Decomposition and

Element Fiscal Costs

ConOps and

Lifecycle Cost 

Calculation

Lifetime Costs to

Generating Electricity

Climate

Impact

Calculations

SBSP system has 6 functions: collect, 

convert, transmit, receive, convert, 

deliver. Aerospace decomposed the 

collection of subsystems that perform 

these six functions, then calculated fiscal 

costs according to a WBS structure. NASA 

OTPS validated the findings with their 

own model following the functional 

decomposition into 89 parameters.

NASA OTPS arranged 

the 87 parameters into 

a ConOps to calculate 

the lifecycle cost to 

develop, assemble, 

operate, maintain, and 

dispose of the SBSP

system.

NASA OTPS calculated 

the lifetime costs to 

generate electricity

using the cost of each 

ConOps phase. This 

data was used to 

estimate LCOEs for the 

baseline and sensitivity 

analyses.

NASA OTPS performed an 

Economic Input Output Life 

Cycle Assessment using a 

mix of mass- and spendbased assessments. This 

data was used to estimate 

CO2 equivalent per kWh for 

the baseline and sensitivity 

analyses.

Approach to Cost Calculations

Functional Decomposition of SBSP Systems

SBSP is assessed as having six functional steps, denoted by applicability to either in-space or 

ground-based segments. 

• Functional steps for the in-space segment encompass each system’s ability to: collect solar 

energy in space, convert solar energy to microwave radiation, and transmit microwave 

radiation to the Earth. 

• Functional steps for the ground-based segment refer to each system’s capacity to: receive 

microwave radiation at ground station rectenna, convert microwave radiation to electricity, 

and deliver electricity to the grid for use.

To describe each functional step, we use a combination of 1) the 89 parameters (including WBS 

elements) developed by NASA OTPS and the Aerospace Corporation, 2) design reference 

parameters provided by or inferred from Mankins (Mankins, SPS-Alpha Mark-III and an achievable 

roadmap to space solar power, 2021), Sasaki (Sasaki, A new concept of solar power satellite: 

Tethered-SPS, 2006), and Pellegrino (Pellegrino, 2022), 3) efficiency losses provided by an 

authoritative public-private study (Rodenbeck, et al., 2020), and 4) independently verified

calculations determined by the study team. The following summarizes determinations for all 

parameters in the six functional steps. For a breakdown of each parameter by its corresponding 

functional step, along with values for both design reference systems, please refer to Tables 6 and 7

below. 

From original panel sizes provided by Mankins and Sasaki, we applied the solar constant, as well as 

authoritative assessments of efficiency losses at each step, estimated by (Rodenbeck, et al., 2020).

We normalized the outputs to 2 GW, which provided a "scaling factor" for each system. We 

evaluated each functional step through the lens of each system’s scaling factor—0.77 and 5 applied 

to the Innovative Heliostat Swarm and Planar Array, respectively. We based system design 
41

parameters off of Mankins and Sasaki (e.g., distance to Earth, solar panel size, illumination, 

radiofrequency, and capacity factor). The practice of scaling total system mass to solar cell 

efficiency comes from earlier literature (Mankins, SPS-ALPHA: The First Practical Solar Power 

Satellite via Arbitrarily Large Phased Array, 2012). Based on the scaling factor and solar panel size 

from Mankins and Sasaki, we calculated the total solar panel surface area. We then applied the 

solar constant (NASA, 2023) to determine the incident solar energy. Based on the power delivered, 

distance, and beam frequency from Mankins and Sasaki, Aerospace inferred the diameter of the 

ground rectenna receptor for each system. Changes to the angle of incident solar energy over the 

year were not evaluated, nor were changes in capacity factor from having multiple systems in space 

for RD2.

The following is a summary of major losses of efficiency for each functional step: 

• Collect: solar cell efficiency (35%)

• Convert in-space: solar energy to microwave radiation (DC-DC 90% and DC-RF 70%)

• Transmit: antenna emission (90%), atmospheric travel (98%), and beam collection (95%)

• Receive: rectenna array reception (78%)

• Convert on-ground: DC-DC (90%)

Taking the scaling factor for each system and inefficiencies into account, and incorporating each 

system’s capacity factor, results in final power delivery of approximately 2 GW (or about 13% of the 

incident solar energy).

ConOps Phases

We further break each system into five ConOps phases to evaluate costs by each phase of the full 

operational lifecycle. Evaluating costs by ConOps phase also allows us to estimate capital 

expenditures (CapEx) and fixed operations and management (FOM) costs, which we use in the next 

section to compare the cost of different renewable energy technologies.

Table 6. Functional Decomposition of Design Reference Systems for the Space-Based Segment

Space-Based Segment

Functional 

Step Parameter RD1 RD2 Source

Collect

Distance to Earth surface (km) 35,786.00 35,786.00 Mankins, Sasaki

Scaling factor 0.77 5 Calculated

Solar panel size (km2) 11.473 19 Mankins, Sasaki

Solar panel surface area (m2) 11,473,000.00 19,000,000.00 Calculated

Solar Constant (w/m2) 1,367.50 1,367.50 NASA

Incident solar energy (MW) 15,689.33 25,982.50 Calculated
42

For a descriptive summary of the full lifecycle of SBSP systems, a description of each ConOps phase 

is described in Table 7. Note that the Develop ConOps phase includes technology development and 

manufacturing of bus hardware for the Planar Array design reference system. 

Table 7. Functional Decomposition of Design Reference Systems for the Ground-Based Segment

Ground-Based Segment

Functional Step Parameter RD1 RD2 Source

Receive

Rectenna Array Reception 

Efficiency 0.78 0.78 Rodenbeck et al.

Diameter ground rectenna (km) 

receptor

6 4

Inferred from 

Mankins, Sasaki

Convert on Ground DC to DC Conversion Efficiency 0.9 0.9 Rodenbeck et al.

Deliver

Capacity factor (% of year 

generating power) 0.997 0.6 Mankins, Sasaki

Power delivered (MW) 2028.791344 2021.948467 Rodenbeck et al.

Table 8. Description of Each ConOps Phase

Space-Based Segment

Illumination Secondary reflector 

array ~2-3 suns

No additional optical 

array 1 sun Mankins, Sasaki

Solar Cell Efficiency 0.35 0.35 Rodenbeck et al.

Convert in 

Space

DC to DC Conversion Efficiency 0.9 0.9 Rodenbeck et al.

DC to RF Conversion Efficiency 0.7 0.7 Rodenbeck et al.

Transmit

Antenna Emission Efficiency 0.9 0.9 Rodenbeck et al.

Atmospheric Travel Efficiency 0.98 0.98 Rodenbeck et al.

Beam Collection Efficiency 0.95 0.95 Rodenbeck et al.

RF frequency (GHz) 2.45 5.8 Mankins, Sasaki

ConOps Phase Description

Develop

Research and develop technologies

Manufacture SBSP module hardware

Perform project management, systems engineering, and mission assurance

Assemble

Manufacture servicers

Launch SBSP modules and servicers to LEO

Refuel launchers in LEO for orbital transfer to GEO
43

The following is a breakdown of: 1) what each phase encompasses, 2) relevant parameters and WBS 

elements, and 3) how the methodology supports cost outputs.

ConOps Phase 1: Develop

Develop Components

• Research and develop technologies

• Manufacture SBSP module hardware

• Perform project management, systems engineering, and mission assurance (PM/SE/MA)

The following is a list of all WBS Elements supporting this phase, including how they compare to 

both design reference systems. Note that WBS Elements map to either the components of this 

phase or to the specifications which serve as inputs to the components. 

Table 9. Summary of all WBS Elements in the Develop ConOps Phase

ConOps Phase Description

Assemble SBSP modules in GEO with servicers 

Perform mission operations and data analysis to assemble

Operate

Construct ground facilities

Perform mission operations and data analysis to operate during service lifetime

Manufacture spacecraft shielding

Maintain

Manufacture replacement SBSP modules and servicers 

Launch replacement SBSP modules and servicers to LEO

Refuel launchers in LEO for orbital transfer to GEO 

Assemble replacement SBSP modules with replacement servicers in GEO

Perform mission operations and data analysis to maintain

Dispose

Manufacture active debris removal spacecraft

Launch active debris removal spacecraft to LEO

Refuel launchers for orbital transfer to GEO

Transfer all SBSP modules from GEO to graveyard orbit with active debris removal spacecraft

Perform mission operations and data analysis to dispose

WBS Elements RD1 RD2 Sources & Notes

Thermal management passive passive Aerospace

Power Mass per Module (kg) 2.00 2.50 Aerospace

Structure Mass per Module (kg) 1.00 1.25 Aerospace
44

WBS Elements RD1 RD2 Sources & Notes

Attitude Determination and Control 

System Mass per Module (kg) 0.20 0.25 Aerospace

Propulsion Mass per Module (kg) 0.00 0.00 Aerospace

Telemetry Tracking and Command Mass 

per Module (kg) 0.20 0.25 Aerospace 

Command and Data Handling Mass per 

Module (kg) 0.20 0.25 Aerospace

Thermal Mass per Module (kg) 0.40 0.50 Aerospace

Module Mass (kg) 4.00 5.00 Aerospace

Estimated number of modules 1,463,000.00 2,000,000.00 Inferred from Mankins, 

Sasaki, Pellegrino

SBSP In-space Mass (kg) 5,852,000.00 10,000,000.00 Inferred from Mankins, 

Sasaki, Pellegrino

Complexity/risk

High 2 elements 

reflector + PV-RF; 

Assembly in space

Low 1 element PV-RF 

sandwich

Aerospace inferred from 

Mankins, Sasaki

Technology Development Cost $2.4B $2.07B

Assuming TRL 4 (35%) for RD1

and TRL 6 (25%) for RD2. 

NASA OTPS modified, 

Aerospace inferred from 

Mankins, Sasaki with Design 

Maturity Factor and (Brunner 

& Jack, 2006)

PV-RF module Modular sandwich

Modular sandwich 

(no wired 

signal/power 

interfaces required

between the 

modules)

Mankins, Sasaki

Illumination Secondary reflector 

array ~2-3 suns

No additional optical 

array 1 sun Mankins, Sasaki

PV array 1 sided bifacial Mankins, Sasaki

Module Initial Cost $1,000,000.00 $1,000,000.00 Analogs of satellite and PV 

industry

Module Manufacturing Learning Rate 0.75 0.75 Aerospace 11/2022

Module Manufacturing Cost ($) $6.9B $8.3B

Crawford model learning 

curve applied to initial cost 

and number of units.

Develop Program Management, 

Systems Engineering, and Mission 

Assurance Cost ($)

$2.3B $2.6B

Aerospace Corporation:

Mission PM/SE/MA costs are 

assumed at 25% of combined 

Hardware and Technology 

Development.

Total Develop Cost ($) $11.6B $12.9B
45

The above data was used to derive the total hardware manufacturing, technology development, 

and mission management costs incurred for each design reference.

Estimating costs for manufacturing SBSP module hardware: Aerospace derived mass by taking the 

total system mass and averaging out components by the number of modules. This “bottoms-up”

approach includes the following hardware subsystems: power, structure, attitude and 

determination control, propulsion, telemetry tracking and command, command and data handling, 

and thermal. As previously mentioned, Aerospace used a combination of cost models for hardware 

costs due to the maturity of both design references and the timeframe for implementation. (Note 

that this is an idealized decomposition of module subsystems for a comparative analysis. Mankins 

proposes separate modules for different functions, including assembly. Sasaki only modularizes the 

array for efficient terrestrial manufacturing.)

We referenced Mankins and Sasaki for number of modules in one system and applied the scaling 

factor to calculate the number of modules needed for 2 GW of output. Using the module mass and 

the number of modules needed, we estimated the total in-space mass, accounting for technology 

advances since Sasaki’s original 2006 concept paper for the Planar Array design reference with 

Pellegrino et al.’s more recent technology demonstration. 

Crawford model learning curve formula: cumulative cost of production = first unit cost * (learning 

rate * (natural log(total number of units produced) / natural log(2)))

We used Aerospace’s learning curve estimate of 75% to account for efficiencies over time due to 

volume, arriving at final module development costs. We use the Crawford model learning curve 

formula instead of the Cumulative Average approach used by Aerospace. There are many other 

learning curve models, such as Stanford-B, Plateau, and Dejong’s, and the study team encourages 

those seeking to repeat this analysis to experiment with alternatives. We assume an initial module 

cost of $1M. To arrive at final module development costs with our updated number of modules 

(taking the scaling factor into account), we developed a python script to apply the learning curve 

and deliver the cost of producing each individual module, a running average cost of all modules, 

and a running cumulative cost of all modules. The module manufacturing cost presented here is the 

cumulative cost of all modules. The following code was used to develop these estimates:

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

# Input variables

learning_rate = 0.75

first_unit_cost = 1000000

units_produced = list(range(1,6000001))
46

# Output variables

this_unit_cost = first_unit_cost * (learning_rate ** (np.log(units_produced) / np.log(2)))

cumulative_cost = np.cumsum(this_unit_cost)

average_cost = cumulative_cost / units_produced

# Graphs and tables

plt.plot(units_produced, cumulative_cost)

plt.xlabel('Units Produced')

plt.ylabel('Cumulative Cost')

plt.show()

df = pd.DataFrame({'Units Produced': units_produced, 'This Unit Cost': this_unit_cost, 

'Cumulative Cost': cumulative_cost, 'Average Cost': average_cost})

print(df)

# Export to CSV

df.to_csv('C:/Users/use/folder/sbsp manufacturing learning curve.csv', index=False)

Estimating costs for technology development: Aerospace inferred technology development costs 

from successful NASA Science Mission Directorate missions, Mankins and Sasaki, and Brunner et al.

(Brunner & Jack, 2006). Aerospace applied the same cost factor to both systems but given the 

recent technology demonstration by Caltech (Caltech, 2023), we adjusted RD2’s TRL level to 6. 

Technology development costs are estimated to be 35% of hardware costs for RD1 (assuming TRL 

4), and 25% of hardware costs for the RD2 (assuming TRL 6).

Estimating costs for mission project management, systems engineering, and mission assurance: 

Aerospace estimated in-space mission operations costs using a proprietary tool, the Mission 

Operations Cost Estimation Tool (MOCET), and a combination of NASA Science and commercial 

constellation mission analogies. Mission PM/SE/MA costs are assumed at 25% of combined 

spacecraft Hardware, Shielding, Maintenance Hardware, and Technology Development.

ConOps Phase 2: Assemble 

Assemble Components

• Manufacture servicers

• Launch SBSP modules and servicers to LEO

• Refuel launchers in LEO for orbital transfer to GEO

• Assemble SBSP modules in GEO with servicers 

• Perform mission operations and data analysis to assemble 

• Perform mission support services of program management, systems engineering, and 

mission assurance
47

The following is a list of all WBS Elements supporting this phase, including how they compare to 

both design reference systems. Note that WBS Elements map to either the components of this 

phase or to the specifications which serve as inputs to the components.

Table 10. Summary of all WBS Elements in the Assemble ConOps Phase

WBS Elements RD1 RD2 Sources

Assembly time per module 

(hours) 0.67 0.63

Aerospace, citing ISS and Orbital 

Express as analogs. Given launch 

vehicle fairing limitations, the Planar 

Array cannot be unfurled and must 

be assembled on orbit.

Modules assembled per 

servicer per month 1095 1152.631579

How many modules a single servicer 

can assemble in one month of 

continuous operation.

Total assembly time (work 

months, 1 servicer) 1336.073059 1735.159817

How many months it would take a 

single servicer to assemble the entire 

system under continuous operation.

Servicer mass (kg) 2,800.00 2,800.00 https://nssdc.gsfc.nasa.gov/nmc/spa

cecraft/display.action?id=2020-056B

First Servicer Cost ($) $1,000,000,000.00 $1,000,000,000.00 Aerospace, citing (Messier, 2020).

Number of servicers 17 15 Aerospace, Mankins, Sasaki, NASA

OTPS amended.

Servicer Manufacturing 

Learning Rate 0.85 0.85 Aerospace assessment of analogs.

Time to assemble SBSP system 

(months) 89 152

Simple model given launch cadence, 

transit times, payload capacity, 

minimizing servicer downtime.

Maximum Modules per 

Starship 25000 20000 Starship payload capacity / module mass

Module: Servicer total ratio 86,058.82 133,333.33 

Total servicers to modules (number 

of servicers determined using 

assembly model to minimize servicer 

downtime)

Assembly time of averaged 

ratio of modules to servicers 

(years)

6.55 9.64 

Number of Servicers per 

Payload 0.288155129 0.149372635

How many servicers there are in a 

single payload, average. Assemble 

ConOps tab assumes earlier payloads 

carry more servicers.

Time to refuel (months) 1 1

Estimate, does not consider 

cryogenic boiloff in orbit.

Orbital transfer time (months) 1 1

Output of first order delta v 

calculation
48

WBS Elements RD1 RD2 Sources

Servicer Manufacturing Cost -

Assemble ($) $10.9B $9.8B Using the Crawford model, 85% learning curve.

Assemble Program 

Management, Systems 

Engineering, and Mission 

Assurance Cost ($)

$2.7B $2.5B 25% of hardware cost.

Assemble Mission Operations 

cost ($/month) $1,200,000.00 $1,200,000.00

4x Aerospace's ADR fleet 300k 

monthly operations cost. Analog of 

Starlink (300 seats 200k each 

estimate), annual operations cost 

https://www.reuters.com/article/usspacex-starlink-insightidUSKCN1N50FC

Total Mission Operations 

Assembly cost not including 

launch ($)

$106M $182M

Aerospace, modified proportional to 

number of servicers; MOCET 

historical average of NASA missions 

used. Aerospace ADR fleet was 

assumed autonomous and had flat 

operations cost; we are applying a 

similar methodology evenly across 

each phase's mission operations 

costs.

Starship payload capacity to 

LEO (kg) 100,000.00 100,000.00 https://www.spacex.com/media/starship_users_guide_v1.pdf

Starship launch cost ($) $100,000,000.00 $100,000,000.00 Aerospace 9/2022 cites (Vorbach, 

2022)

Block buy discounted rate 0.85 0.85 Aerospace

Disposable Starship payload 

capacity to GEO (kg) 21,000.00 21,000.00

For sensitivity analysis

https://www.spacex.com/media/star

ship_users_guide_v1.pdf

Refueled Starship payload 

capacity to GEO (kg) 100,000.00 100,000.00 https://www.spacex.com/media/starship_users_guide_v1.pdf

Refuel launches required per 

Starship LEO to GEO 12.00 12.00 Blue Origins Fed’n, LLC; Dynetics, Inc.-A Leidos Co., supra at 27 n.13.

Reuses of each Starship 100.00 100.00 BryceTech SME for optimistic value, 

SpaceX

Total Develop Upmass (kg) 5,899,600.00 10,042,000.00 

Disposable launches total 281 479

Total Starship Assemble 

hardware launches 59 101 How many Starships are carrying hardware to GEO in this phase.

Refuel launches Assemble 

total 708 1212

How many additional Starship 

launches needed to refuel all 

hardware-carrying Starships to GEO 

in this phase.

Total Launch Costs Assemble 

($) $65.2B $111.6B
49

The above WBS elements were used to derive the cost to launch original hardware, including refuel 

launches, servicer manufacturing costs, and mission operations and data analysis costs for each 

design reference.

Estimating costs for Launch of Original Hardware: Aerospace approached launch costs by estimating 

the total launches needed to deliver the SBSP systems to their operational orbit, which includes 

launches to refuel in LEO. Aerospace conducted a trade study to find the most desirable launch 

vehicle from a mass- and volume-to-orbit standpoint. After evaluating multiple heavy-lift launch 

and transfer vehicles and also considering ability to refuel and reuse, Starship was selected. 

Launch of original hardware includes both launch costs for initial assembly and launch costs to 

refuel in LEO. To find the number of launches for initial assembly, we divide the total upmass (the 

total in-space mass, normalized to 2 GW, plus the total servicer mass) by Starship’s payload capacity 

to LEO. Starship’s capacity to LEO is based on the 2020 users guide published by SpaceX. To find the 

number of launches to refuel in LEO, we assume that for every payload of original hardware 

delivered to LEO, it will require 12 additional Starship launches to refuel for transfer to GEO (Blue 

Origin Fed’n, LLC; Dynetics, Inc.-A Leidos Co., 2021). After finding the total number of launches for 

original hardware and additional fuel, we multiply by Starship’s launch cost and also apply a block 

discount rate of 15%. Starship’s launch cost and the block discount rate were both determined by 

Aerospace. 

Estimating costs for Servicer Manufacturing: Costs for spacecraft servicer manufacturing were 

based on the Mission Extension Vehicle 2 (MEV-2). Aerospace assumed an initial cost of $1B for the 

first servicer unit. Based on a one-year design life for servicers, they estimated a 7-year assembly 

time, with an 85% learning curve. A Crawford Model learning curve formula was applied to estimate 

costs for all servicers.

WBS Elements RD1 RD2 Sources

Number of Starships built 

(reusable) 66 113 Assumes Starships to GEO are never reused.

Starship Capable launch sites 

capacity (launches per annum) 104 104

At present, Starship-capable launch 

sites: Boca Chica (~5/year), LC39A 

(<20/year), new LC40 pad (unknown 

capability), and an unknown number 

of off-shore platforms - we assume 

capability to launch 2 Starships every 

week (average over period of time 

under study). BryceTech SME.

Hardware payloads to GEO 

per annum

8 8

Time to launch all payloads 

(years) 7.375 12.625 Based on first order assembly model

Total Assemble Cost ($) $78.9B $124.1B
50

Estimating assembly time: We assume a launch capacity of two per week or 104 per year. At this 

rate, it takes just over 6 weeks for 13 Starships to reach orbit. We therefore assume it takes 7 to 8 

weeks for one payload-laden Starship to be fully refueled in LEO. We assume that no cryogenic boil 

off occurs in orbit. Given the variable possible conditions of launch sites and orbits, we assume that 

one additional month of travel time to GEO is more than sufficient. We assume 4,200 m/s is more 

than sufficient for a chemical propulsion orbital transfer from LEO to GEO. Applying known inputs to 

delta v and transit time equations (below) yields delta v well in excess of this minimum. For 

Starship, we use 355 s, 14.7 MN, a payload mass of 100 MT, fuel mass of 120 MT, and dry mass of 

100 MT. 

Delta V = specific impulse * standard acceleration due to gravity * natural logarithm (initial 

mass/final mass)

Transit time = (initial mass / thrust) * deltaV / specific impulse

Number of modules in GEO = (this month’s number of payloads in GEO - previous month’s 

number of payloads in GEO) * maximum number of modules on Starship - ((number of 

servicers in GEO this month - number of servicers in GEO last month) * servicer mass) / module 

mass + number of modules in GEO last month

Modules assembled per month = number of servicers in orbit * servicer monthly assembly rate

Finally, the cumulative number of modules assembled was evaluated at each month to maximize 

the efficiency of the servicer fleet by minimizing servicer idle time. We use Aerospace’s assessment 

that servicers will take approximately 40 and 38 minutes to assemble a single RD1 and RD2 module, 

respectively. Our assembly timeline model seeks to minimize servicer downtime during 

construction phases. Our first order model estimates 7.4 and 12.6 years to assemble RD1 and RD2, 

with 17 and 15 servicers, respectively. In both cases, no servicer is idle until the final year of 

assembly operations.

Estimating costs for Mission Operations & Data Analysis – Assembly: Aerospace assessed the 

operation of the ADR fleet as autonomous, common to any fleet size, and at a rate of $300k/month. 

For the more complex task of assembling the SBSP system itself, we assume four times this cost, or 

$1.2M/month. This number is informed by analogs like Starlink (Johnson & Roulette, 2018), 

assuming one sixth of the Starlink workforce (50/300), assuming capital costs for labor 

($18,000/month) and adding the result ($900k/month) to Aerospace assessed cost of operating an 

autonomous fleet.

ConOps Phase 3: Operate 

Operate Components:

• Construct ground facilities

• Perform mission operations and data analysis to operate during service lifetime
51

• Develop spacecraft shielding

• Perform mission support services of program management, systems engineering, and 

mission assurance

The following is a list of all WBS Elements supporting this phase, including how they compare to 

both design reference systems. Note that WBS Elements map to either the components of this 

phase or to the specifications which serve as inputs to the components.

Table 11. Summary of all WBS Elements in the Operate ConOps Phase

The above WBS elements were used to derive the cost of mission operations and data analysis to 

operate during the service lifetime, as well as ground system costs and spacecraft shielding costs for 

each design reference system.

Estimating costs for Mission Operations and Data Analysis – Operations: The above assumption of 

$1.2M/month was applied over the course of the SBSP systems’ assumed 30 years of operation.

Estimating costs for Ground System: Aerospace derived costs for ground systems based on 

analogies of U.S.-based solar array farms. They evaluated 12 solar farms for cost estimates based on 

land use and ground-based large antenna arrays. We applied these results to the Innovative 

Heliostat Swarm without modification, and applied the scaling factor for the Mature Planar Array, 

which requires five receivers. 

WBS Elements RD1 RD2 Sources

RF frequency (GHz) 2.45 5.8 Aerospace

Diameter ground rectenna (km)

receptor

6 4

Aerospace derived from 

Mankins, Sasaki. 

Operational lifetime (years) 30.00 30.00

Capacity factor (% of year generating power) 0.997 0.6 Mankins, Sasaki

Hours in a year 8760 8760

Lifetime kWh 533,166,365,206.45 531,368,057,222.62

Operations cost ($/year) 14,400,000.00 14,400,000.00

Mission Operations & Data Analysis -

Operations Cost ($) $432,000,000.00 $432,000,000.00 Aerospace, NASA OTPSderived

Ground System cost ($) $3.1B $8,27B

Aerospace derived from 

solar farms and very 

large arrays. We 

assume RD2 requires 5 

rectennas.

PM/SE/MA of spacecraft shielding ($) $49,2M $133.25B

Spacecraft Shielding cost ($) $197,000,000.00 $533,000,000.00 Aerospace

Total cost of Operations ($) $3.8B $9.36B
52

Estimating costs for Spacecraft Shielding: Aerospace assessed spacecraft shielding costs as part of 

the broader active debris removal assessment, which also includes remediation. We assess 

spacecraft shielding in the Operations ConOps phase since it is critical to ensuring operations and 

consider remediation as part of the Dispose ConOps phase.

The cost due to spacecraft shielding is the cost of the additional mass needed to protect from 

orbital debris. Aerospace used the same mass increase for both systems (0.74%), supported by the 

Aerospace-developed assessment, “Space Debris: Models and Risk Analysis.”

ConOps Phase 4: Maintain

Maintain Components:

• Manufacture replacement SBSP modules and servicers 

o Assemble replacement SBSP modules with replacement servicers in GEO

• Launch replacement SBSP modules and servicers to LEO

o Refuel launchers in LEO for orbital transfer to GEO 

• Perform mission operations and data analysis to maintain

• Perform mission support services of program management, systems engineering, and 

mission assurance

The following is a list of all WBS Elements supporting this phase, including how they compare to 

both design reference systems. Note that WBS Elements map to either the components of this 

phase or to the specifications which serve as inputs to the components.

Table 12. Summary of all WBS Elements in the Maintain ConOps Phase

WBS Elements RD1 RD2 Sources

All hardware lifetime (years) 10.00 10.00 Aerospace

Number of refurbishment cycles 2 2 Aerospace

Number of refurbishment modules 2,926,000.00 4,000,000.00 Mankins, Sasaki

Number of maintenance servicers 34 30 Mankins, Sasaki

Total Maintain Upmass (kg) 11,799,200.00 20,084,000.00 Sasaki

Disposable launches total 562 957

Total Starship Maintain launches 118 201

Refuel launches Maintain total 1416 2412

Number of Starships built (reusable) 131 224

Assumes 

Starships to GEO 

are not reused

Cost of Maintenance Servicers ($) $15B $13.6B

Cost of Maintenance Modules ($) $6.2B $7.47B
53

The above WBS elements were used to derive cost estimates for all maintenance hardware, 

including launch and orbital assembly.

Estimating costs for Maintenance Hardware: Maintenance hardware includes the cost of 

maintenance modules, including replacements for modules and servicers. Assuming modules have a 

10-year lifetime, thus requiring two refurbishment cycles in a 30-year period, and referencing 

Mankins and Sasaki for the number of maintenance modules, we arrive at the total number of 

maintenance modules. 

We extend our prior application of the SBSP module and servicer spacecraft learning curves to 

determine the cost of two refurbishment cycles for all modules and servicers, respectively. Note 

that for all learning rates, Aerospace uses a model based on cumulative averages. We use the 

Crawford Model, which assumes slower rates of learning and results in higher total costs. 

Estimating costs for Launch of Maintenance Hardware: Launch of maintenance hardware includes 

cost, using Starship, for all maintenance launches. Maintenance launches include launch of 

maintenance servicers and modules. Based on the upmass for the total number of maintenance 

modules, we find the total number of Starship launches needed to launch to LEO. We assume 12 

refueling launches to transfer to GEO are needed for each launch and apply a 15% block buy 

discount rate (as in the Assemble phase). 

Estimating costs for Orbital Assembly of Maintenance Hardware: We use the same methodology as 

we did for the initial assembly of the SBSP system, assuming of $1.2M/month for operations, and 

the same number of servicers, launches, and time to assemble for each refurbishment cycle.

ConOps Phase 5: Dispose 

Dispose Components:

• Manufacture active debris removal spacecraft

• Launch active debris removal spacecraft to LEO

• Refuel launchers for orbital transfer to GEO

• Transfer all SBSP modules from GEO to graveyard orbit with active debris removal 

spacecraft

• Perform mission operations and data analysis to dispose

WBS Elements RD1 RD2 Sources

Maintain Program Management, Systems 

Engineering, and Mission Assurance Cost 

($)

$5.3B $5.27B

Cost of Maintenance Launches ($) $130.4B $222.1B

Cost of Maintenance Operations ($) $213.6M $364.8M

Total Cost Maintain ($) $157.15B $248.85B
54

• Perform mission support services of program management, systems engineering, and 

mission assurance

The following is a list of all WBS Elements supporting this phase, including how they compare to

both design reference systems. Note that WBS Elements map to either the components of this 

phase or to the specifications which serve as inputs to the components.

Table 13. Summary of all WBS Elements in the Dispose ConOps Phase

The above WBS elements were used to derive cost estimates for ADR vehicle manufacturing, 

management, operations, and ground systems costs, as well as associated launches. 

Estimating costs for ADR Vehicle Manufacturing: Aerospace assessed an approach to ADR with ADR 

transfer vehicles acting as space tugs to move modules from GEO to a graveyard orbit. ADR transfer 

vehicles are based on Northrop Grumman’s Mission Extension Vehicle (MEV). They are assumed to 

deliver modules to a graveyard orbit at the end of their design life (every 10 years), or twice during 

the mission lifecycle, and again at the 30-year mark for end of mission disposal. Aerospace did not 

consider launch costs for ADR transfer vehicles in the ADR methodology. For cost estimates, 

Aerospace considers mass estimates using the MEV in addition to in-house costing methodologies. 

For our cost estimates, we leverage the same first-unit cost assessed by Aerospace ($500M/unit) 

and also apply the same 90% learning rate to account for improvement over time with experience 

in production. We determine the number of transfer vehicles needed based on the updated inspace mass using the scaling factor, the ADR transfer vehicle payload capacity, and duration of ADR 

operations. 

WBS Elements RD1 RD2 Sources

Active Debris Removal Vehicle Base Cost ($) $500,000,000.00 $500,000,000.00 Aerospace 11/2022

Active Debris Removal Operations Costs ($/month) $300,000.00 $300,000.00 Aerospace 11/2022

ADR operations duration (months) 180.00 180.00 Aerospace

ADR Vehicle Mass (kg) 2,500.00 2,500.00 Aerospace

ADR Vehicle Payload Capacity (kg) 5,000.00 5,000.00 Aerospace

Active Debris Removal Vehicles Needed 59.00 100.00 Aerospace 11/2022

Active Debris Removal Management Costs ($) $2.77B $4.3B Aerospace 11/2022

Active Debris Removal Hardware Costs ($) $18.5B $29B Aerospace 11/2022

Active Debris Removal Ground Costs ($) $1.85B $2.9B Aerospace 11/2022

Active Debris Removal Operations Costs ($) $54,000,000.00 $54,000,000.00 Aerospace 11/2022

Active Debris Removal Launch Costs ($) $1.5B $2.55B

Active Debris Removal Reserves ($) Removed Removed Aerospace 11/2022

Total Active Debris Removal Costs ($) $24.7B $38.9B Aerospace 11/2022
55

Estimating costs for ADR Vehicle Management, Operations, and Ground Costs: Aerospace evaluated 

ADR management costs by applying a 15% multiplier to the cost of ADR hardware. We leverage this 

approach using updated ADR hardware costs taking the scaling factor into consideration.

ADR operations costs are based off of the operational cost for removal, estimated monthly, and the 

total duration of ADR operations. Aerospace provides an estimate of the monthly cost, assuming

the same cost regardless of fleet size due to the use of autonomous operations. Duration of 

operations assumes that the refurbishment cycles and the end of mission cycle take five years each, 

totaling 15 years of operations.

Estimating costs for Launch Vehicle – Active Debris Removal: We approach launch costs similarly to 

Aerospace, using our normalized values and several updated parameters. Launch vehicle costs for 

ADR vehicles are determined based off the updated number of vehicles needed, the servicer mass 

(which is based off of MEV-2), Starship’s payload capacity to LEO (estimated using the 2020 Starship 

Users Guide), and the number of refuel launches to transfer from LEO to GEO. We also apply a 15% 

block buy discount rate to the cost to launch Starship. 

The following is a detailed list of all ConOps parameters supporting this phase, including a 

comparison of both design reference systems. 

Determining Capital Expenditures and Fixed Operations and Management

Evaluating costs by ConOps phase also allows us to estimate CapEx and FOM costs. We follow 

NREL’s (NREL, 2022) definition of CapEx, "Capital expenditures required to achieve commercial 

operation of the generation plant," and FOM, “Annual expenditures to operate and maintain 

equipment that are not incurred on a per-unit-energy basis.”

Following these definitions, we consider the Develop and Assemble ConOps phases as contributors 

to CapEx costs. This accounts primarily for development and assembly of the in-space hardware, 

including launch. We group all other ConOps phases under FOM, as they are not required to initiate 

the first system. 

CapEx and FOM are key inputs to determining the levelized cost of electricity (LCOE), which is a 

useful method of comparing the costs of different renewable energy technologies. We discuss this 

method in the following section. 

Levelized Cost of Electricity

Overview

In addition to cost estimates evaluated over the lifecycle, we used fiscal cost estimates to perform a 

traditional energy cost analysis. This allows for a comparison of each system’s costs per megawatt 

hour and an additional comparison to other renewable energy technologies, if produced from a 

similar power plant. As described by NREL (NREL, 2023), "Capital expenditures [are] required to 
56

achieve commercial operation of the generation plant" and fixed operations and maintenance 

(FOM) are “[a]nnual expenditures to operate and maintain equipment that are not incurred on a 

per-unit-energy basis.” To restate from the previous section, CapEx costs include the Develop and 

Assemble ConOps phases and FOM costs include the Operate, Maintain, and Dispose ConOps 

phases. 

NREL is the most authoritative USG source for electricity production technology data. NREL’s Annual 

Technology Baseline (ATB) (NREL, 2022) provides assessments of a range of technologies every 

year. We use the data published in 2022 and apply their Levelized Cost of Electricity (LCOE) formula 

to compare electricity production technology costs as uniformly as possible. As described by NREL, 

“The levelized cost of energy (LCOE) calculator provides a simple way to calculate a metric that 

encompasses capital costs, operations and maintenance (O&M), performance, and fuel costs of 

renewable energy technologies.”

Our primary divergences from NREL’s calculator are in the consideration of more refined financing 

inputs. We do not consider the rate on return of equity in our calculations for example, as our 

baseline scenario assumes Government financing. Different activities have different financing 

assumptions in the ATB (construction has a different financing rate for example). We apply the 

same financing rate to each design reference system and all comparison energy technologies. We 

also assume manufacturing of all activities occur in the U.S. and do not consider cost factors for 

different locations of work. Finally, we re-state NREL’s assertion that this is a simplified calculation 

for comparative purposes and that a more detailed analysis to include financing, discounts, and 

other costs would provide a more holistic look.

Calculation

NREL calculates LCOE using the following formula:

LCOE = {(overnight capital cost * capital recovery factor + fixed O&M cost)/(8760 [hours in a

year] * capacity factor)} + (fuel cost * heat rate) + variable O&M cost.

When applied to the two design reference systems, each variable is described as follows:

• Overnight Capital Cost: CapEx Cost / Power Delivered

• Capital Recovery Factor: Capital Recovery Factor,† with a default discount rate of 3%

• Fixed O&M Cost: FOM cost / Power Delivered / Lifetime

• Capacity Factor: Percentage of the year in which power is generated 

• Fuel cost: N/A

• Heat rate: N/A

• Variable O&M cost: N/A††
57

†Capital Recovery Factor = {i(1 + i)^n} / {[(1 + i)^n]-1} where “i” is the interest rate and “n” is the 

number of annuities received (n = 30, or the lifetime in years of each design reference system).

††Variable Operations and Maintenance covers electricity fuel sources, so NREL does not include 

this cost category for any renewable electricity production technology. SBSP does not use fuel as a 

direct input to electricity production.

In applying this calculation to comparative renewable energy technologies, all variables remain the 

same with exception of the removal of power output (~2 GW), stemming from the SBSP design 

reference systems’ scaling factor. A breakdown of the inputs (all variables) is seen in Table 14. 
58

Table 14. LCOE Calculations in detail

Renewable Energy 

Technology

Lifetime 

(Years)

Output 

(kW)

Capacity 

Factor 

(%)

Hours 

in a 

Year

CapEx 

($/kW)

FOM 

($/kWyear)

Variable 

O&M 

($/kWh)

Fuel Cost ($/ 

MMBtu)

Heat Rate 

(Btu/ 

kWh)

CRF (default 

discount rate 

of 3%)

Levelized 

Cost of 

Utility 

Electricity 

1 ($/kWh)

Levelized 

Cost of 

Utility 

Electricity 

2 ($/kWh)

Simple 

Levelized Cost 

of Alternative 

Energy ($/kWh)

$/MWh 

Utility 1

$/MWh 

Utility 2

$/MWh Notes

RD1 Baseline 30.00 2.03E+06 0.997 8760 $53,689.58 $4,823.97 $- $- 0 0.051019259 $0.21 $0.26 $0.61 $210.00 $260.00 $610.07

RD2 Baseline 30.00 2.02E+06 0.6 8760 $75,807.25 $4,680.37 $- $- 0 0.051019259 $0.21 $0.26 $1.59 $214.00 $260.00 $1,590.13 

Land Wind 2050 30 0.47 8760 $760.00 $33.00 $- $- 0 0.051019259 $0.21 $0.26 $0.02 $214.00 $260.00 $17.43 Class 4 wind

PV Utility 2050 30 0.29 8760 $618.00 $13.00 $- $- 0 0.051019259 $0.21 $0.26 $0.02 $214.00 $260.00 $17.53 

Class 5, 4 hrs

Li-ion 50 MW 

capacity

PV Utility + 

Storage 2050

30 0.3 8760 $855.00 $19.00 $- $- 0 0.051019259 $0.21 $0.26 $0.02 $214.00 $260.00 $23.83 Class 5

CSP + TES 2050 30 0.63 8760 $3,894.00 $56.10 $0.00 $- 0 0.051019259 $0.21 $0.26 $0.05 $214.00 $260.00 $49.06 Class 2

Nuclear 2050 60 0.94 8760 $5,892.00 $146.00 $0.00 $0.74 0.01044 0.036132959 $0.30 $0.37 $0.05 $302.00 $367.00 $54.31 AP 1000

Hydro 2050 100 0.34 8760 $2,471.00 $62.00 $- $- 0 0.031646666 $0.45 $0.54 $0.05 $448.00 $544.00 $47.07 NPD 1

Geothermal 2050 30 0.9 8760 $5,080.00 $99.00 $- $- 0 0.051019259 $0.21 $0.26 $0.05 $214.00 $260.00 $45.43 Hydro / Flash
59

Results

Total SBSP Lifecycle Costs

Table 15. Costs by Capital Expenditures and Fixed Operations and Management

SBSP Lifecycle Costs by ConOps Phase

Table 16. SBSP Lifecycle Costs for the Develop ConOps Phase

Table 17. SBSP Lifecycle Costs for the Assemble ConOps Phase

Cost Estimate Results (FY22$) RD1 Baseline ($) RD2Baseline ($)

Launch of Original Hardware 65.19B 111.6B

Servicer Manufacturing 10.89B 9.86B

Mission Program Management, Systems Engineering, and 

Mission Assurance 2.7B 2.46B

ConOps Phase RD1 ($) RD2 ($)

CapEx

Develop 11.65B 12.95B

Assemble 78.9B 124.1B

Total $90.57B $137B

FOM

Operate 3.79B 9.36B

Maintain 157.1B 248.85B

Dispose 24.7B 38.94B

Total $185.65B $297.17B

Total $276.2B $434.2B

Cost Estimate Results (FY22$) RD1 Baseline ($) RD2 Baseline ($)

Mission Program Management, Systems Engineering, and 

Mission Assurance 2.33B 2.59B

Technology Development 2.4B 2B

Spacecraft Hardware 6.9B 8.29B

Develop Total 11.65B 12.95B
60

Cost Estimate Results (FY22$) RD1 Baseline ($) RD2Baseline ($)

Mission Operations & Data Analysis - Assembly 106.8M 182.4M

Assemble Total 78.9B 124.1B

Table 18. SBSP Lifecycle Costs for the Operate ConOps Phase

Cost Estimate Results (FY22$) RD1 Baseline ($) RD2 Baseline ($)

Mission Operations & Data Analysis - Operations 432M 432M

Ground System 3.1B 8.27B

Spacecraft Shielding 246M 666M

Operate Total 3.79B 9.36B

Table 19. SBSP Lifecycle Costs for the Maintain ConOps Phase

Cost Estimate Results (FY22$) RD1 Baseline ($) RD2 Baseline ($)

Maintenance Modules and Servicers 21.2B 21.1B

Mission Program Management, Systems Engineering, and 

Mission Assurance 5.3B 5.27B

Launch of Maintenance Hardware 130.39B 222.1B

Orbital Assembly of Maintenance Hardware 213.6M 364.8M

Maintain Total 157.15B 248.85B

Table 20. SBSP Lifecycle Costs for the Dispose ConOps Phase

Cost Estimate Results (FY22$) RD1 Baseline ($) RD2 Baseline ($)

ADR Vehicle Manufacturing 18.5B 29B

ADR Vehicle Management, Operations, and Ground Costs 4.68B 7.3B
61

Cost Estimate Results (FY22$) RD1 Baseline ($) RD2 Baseline ($)

Launch Vehicle - Active Debris Removal 1.5B 2.55B

Dispose Total 24.7B 38.9B

Table 21. Total SBSP Lifecycle Costs

Levelized Cost of Electricity

Table 22. LCOE Calculation results

Renewable Energy Technology LCOE ($/kWh) LCOE ($/MWh)

RD1 Baseline 0.61 610.07 

RD2 Baseline 1.59 1,590.13 

Land Wind 2050 0.02 17.43 

Offshore Wind 2050 0.04 39.81 

PV Utility 2050 0.02 17.53 

PV Utility + Storage 2050 0.02 23.83 

CSP + TES 2050 0.05 49.06 

Nuclear 2050 0.05 54.31 

Hydro 2050 0.05 47.07 

Geothermal 2050 0.05 45.43

RD1 Baseline ($) RD2 Baseline ($)

Total $ $276B $434B

Total $ / kg (space segment) $47,203.68 $43,423.96 

Total $ / kWh (lifetime) $0.52 $0.82 
62

Approach to GHG Emissions Calculations

Figure 17. SBSP GHG emissions calculations graphical summary

GHG Emissions

gCO2eq./kWh = (Σ total kg * gCO2eq./kg + total m2 * gCO2eq./m2 + total $ * gCO2e.q/$) / 

(system electricity generation * operational years * hours in a year)

The Aerospace Corporation provided expert assessment of the bill of materials for modules, launch 

vehicles, servicers, and the ground segment. This gave us high-level estimates of how much steel, 

circuitry, or other material inputs were required for each hardware element, which in turn allowed 

us to estimate the total materials required. 

However, several factors, such as transportation, processing, assembly, and more were not being 

accounted for. We spoke with an expert at the National Renewable Energy Laboratory (NREL) who 

suggested we consider the Economic Input Output Life Cycle Assessment (EIO-LCA) (Cobas-Flores, 

1998) method. This method is based on aggregate sector-level economic data, such as the North 

American Industry Classification System (NAICS). Input-output analysis, developed by Wassily 

Leontief (Leontif, 1951) is a technique for capturing economy-wide interdependencies. For example, 

automobile manufacturing needs steel, and steel needs iron ore and coal, which in turn need 

automobiles to transport them from mines to factories. This method allows for a far more accurate 

understanding of changes to economic outputs of individual sectors as they ripple across the 

economy.

Data collected on environmental impacts by organizations like the Environmental Protection Agency 

(EPA) may also be organized by the same industry classification codes. By adding environmental 

impact data to quantified direct and indirect economic inputs of purchases, environmental 

implications for economic activities and their dependencies are derived. We use a mix of mass and 

spend-based assessments, preferring mass wherever possible. Carnegie Melon University and DoD 
63

maintain databases with the gCO2eq. of various mass, spend, and area NAICS categories. 

Unfortunately, the Carnegie Melon EIO-LCA website eiolca.org was nonfunctional during the entire 

period of this work. Thankfully, this information was available publicly via the International 

Aerospace Environmental Group (IAEG) (International Aerospace Environmental Group, 2023). 

Table 23. Full list of parameters used for the GHG emissions assessment. Unless otherwise noted, source is IAEG, 2023.

Parameter GHG emissions kqCO2eq., Source

PV area in m2 0.27 / m2 (Liang & You, 2023)

Cost of modules 174 / kUSD, “Propulsion units and parts for space 

vehicles”

Total Prop Needed for Starship (kg) * Prop cost for Starship ($/kg) 

* Total Starship launches

1,290 /kUSD, Basic organic chemicals

LOX is ~$0.16/kg and liquid methane ~$0.4/kg, ~3:1 

ratio for starship fuel

Number of launches * launch vehicle emissions MT 2,683 CO2 + 1.7 NO (*298 for CO2eq.)

Launcher metal mass (kg) * Total Starships manufactured 1.7 /kg Steel, unspecified process

Structure composite mass (kg) * Total Starships manufactured 495.06/kg Composite-based manufactured products

Harness Mass (kg) * Total Starships Manufactured 5.84/kg Copper unspecified process

{[Electronics mass (kg) + electronics structure mass 

(kg)]/0.181437}* 0.064516 * Total Starships Manufactured

606.12 /m2, printed circuit board; printed circuits 

0.181437kg = 0.064516 m2 (Silver Circuits, n.d.) 

Launcher metal mass (kg) * Total Starships manufactured

Structure composite mass (kg) * Total servicers manufactured

Harness Mass (kg) * Total servicers Manufactured

{[Electronics mass (kg) + electronics structure mass 

(kg)]/0.181437}* 0.064516 * Total servicers Manufactured

Spacecraft shielding (kg) 3.75 Glass fibers, high strength, unspecified process 

(kgCO2eq./kg)

Rectenna cost ($)

182.89 /kUSD, Wireless communication equipment; 

assumed 20% of ground segment cost goes to 

rectenna
64

Parameter GHG emissions kqCO2eq., Source

R&D cost ($) 250 Research, development, and testing services 

(kgCO2eq./kUSD)

Mission Program Management, Systems Engineering, and 

Mission Assurance cost ($)

163.11 Marketing, research and other miscellaneous 

professional, scientific, and technical support services 

(kgCO2eq./kUSD)

Concrete building surface area (m2) 825 /m2 Industrial building, concrete and assuming 

similar sized buildings

Total rectenna support structure mass (kg) Assumed steel

system electricity generation * operational years * hours in a 

year

~2,000,000 kWh * 30 * 8760 = 525,600,000,000 kWh

Table 24. Full list of GHG emissions calculations by ConOps phase

Key input parameters RD1 RD2 kgCO2eq. Source

Develop

PV area in m2 11,473,000.00 19,000,000.00 0.27 (Liang & You, 2023)

PV GHG emissions (kgCO2eq.) 3,097,710.00 5,130,000.00

Cost of modules minus PV $3,453,065,585.02 $4,146,166,077.75 

GHG emissions of modules 

minus PV (kgCO2eq.)

600,833,411.79 721,432,897.53 174

Propulsion units and parts 

for space vehicles 

(kgCO2eq./kUSD)

GHG emissions of modules 

with PV (kgCO2eq.)

603,931,121.79 726,562,897.53

R&D GHG emissions

(kgCO2eq.)

604,286,477.38 518,270,759.72 250

Research, development, 

and testing services 

(kgCO2eq./kEU)

Mission Program 

Management, Systems 

Engineering, and Mission 

Assurance GHG emissions

(kgCO2eq.)

380,179,931.11 422,675,718.09 163.11

Marketing, research and 

other miscellaneous 

professional, scientific, and 

technical support services 

(kgCO2eq./kUSD)
65

Key input parameters RD1 RD2 kgCO2eq. EIO-LCA Name

Assemble

Total Prop Needed for 

Starship (kg) 819,539.3301 819,539.3301 1290 /kUSD, Basic organic chemicals

Prop cost for Starship ($/kg) $0.20 $0.20 

Single Starship Launch 

Emissions 3,189,600.00 3,189,600.00

MT 2683 

CO2 + 1.7 

NO (*298 

for CO2eq.)

Launcher metal mass (kg) 61,200.00 61,200.00 1.7 Steel, unspecified process

Structure composite mass 

(kg) 6,800.00 6,800.00 495.06 Composite-based manufactured products

Harness mass (kg) 5,950.00 5,950.00 5.84 Copper unspecified process

Electronics mass (kg) 3,400.00 3,400.00 359.46 /kUSD, Other electronic 

equipment

Electronics Structure mass 

(kg) 7,650.00 7,650.00

Electronics area (m2) 3,929.20 3,929.20 606.12 Printed circuit board

Assemble Starship launches 767.00 1,313.00

Assemble Starships 

manufactured 66.00 113.00

Total Prop needed Assemble 

launches (kg) 628,586,666.21 1,076,055,140.46

Total Prop cost Assemble 

launches ($) $125,717,333.24 $215,211,028.09 

Key input parameters RD1 RD2 kgCO2eq. Source

Total Develop GHG emissions

(kgCO2eq.)

1,588,397,530.28 1,667,509,375.34 
66

Key input parameters RD1 RD2 kgCO2eq. EIO-LCA Name

Total Assemble launcher 

metal mass (kg) 4,039,200.00 6,915,600.00

Total Assemble structure 

composite mass (kg) 448,800.00 768,400.00

Total Assemble launcher 

harness mass (kg) 392,700.00 672,350.00

Total Assemble launcher 

electronics mass (kg) 224,400.00 384,200.00

Total Assemble launcher 

Electronics Structure mass 

(kg)

504,900.00 864,450.00

Total Assemble launcher 

Electronics area (m2) 259,327.03 443,999.31

Total Assemble launch 

impact (kgCO2eq.)

2,997,124,796.83 5,130,771,037.99

Assemble Mission 

Operations and Data Analysis 

(kgCO2eq.)

17,420,148.00 29,751,264.00 163.11

Marketing, research and 

other miscellaneous 

professional, scientific, and 

technical support services 

(kgCO2eq./kUSD)

Quantity of Servicers –

Assemble 17.00 15.00 

Servicer metal mass (kg) 199.48 199.48 

Servicer structure composite 

mass (kg) 85.49 85.49 

Servicer harness mass (kg) 142.49 142.49 

Servicer electronics mass (kg) 698.18 698.18 

Servicer electronics Structure 

mass (kg) 299.22 299.22 

Total Assemble servicer 

metal mass (kg) 3,391.17 2,992.21 
67

Key input parameters RD1 RD2 kgCO2eq. EIO-LCA Name

Total Assemble servicer 

structure composite mass 

(kg)

1,453.36 1,282.37 

Total Assemble servicer 

harness mass (kg) 2,422.26 2,137.29 

Total Assemble servicer 

electronics mass (kg) 11,869.09 10,472.72 

Total Assemble electronics 

Structure mass (kg) 5,086.75 4,488.31 

Total Assemble servicer 

electronics area (m2) 6,029.22 5,319.90 

Total Assemble servicer 

impact (kgCO2eq.)

4,393,838.42 3,876,916.25 

Mission Program 

Management, Systems 

Engineering, and Mission 

Assurance GHG emissions

(kgCO2eq.)

444,381,007.87 402,109,216.48 163.11

Marketing, research and 

other miscellaneous 

professional, scientific, and 

technical support services 

(kgCO2eq./kUSD)

Total Assemble GHG 

emissions (kgCO2eq.)

3,463,319,791.13 5,566,508,434.72

Key input parameters RD1 RD2 kgCO2eq. EIOLCA Name

Operate

Ground segment cost ($) $3,119,000,000.00 $8,270,000,000.00 182.89 /kUSD, Wireless 

communication equipment

Rectenna cost ($) $623,800,000.00 $1,654,000,000.00 

Percent of mass added to 

support rectenna (%) 0.12244898 0.051724138

Total rectenna support 

structure mass (kg) 381918367.3 427758620.7 Assumed steel
68

Key input parameters RD1 RD2 kgCO2eq. EIOLCA Name

Concrete Building surface 

area (m2) 800 4,000 825

/m2 Industrial building, 

concrete and assuming 

similar sized buildings

Total ground physical 

infrastructure impact 

(kgCO2eq.)

764,008,006.49 1,032,989,715.17

Operate Mission Operations 

and Data Analysis (kgCO2eq.)

70,463,520.00 70,463,520.00 163.11

Marketing, research and 

other miscellaneous 

professional, scientific, and 

technical support services 

(kgCO2eq./kUSD)

Mission Program 

Management, Systems 

Engineering, and Mission 

Assurance GHG emissions

(kgCO2eq.)

8,033,167.50 21,734,407.50 163.11

Marketing, research and 

other miscellaneous 

professional, scientific, and 

technical support services 

(kgCO2eq./kUSD)

Spacecraft shielding 

(kgCO2eq.)

162,393.00 277,500.00 3.75

Glass fibers, high strength, 

unspecified process 

(kgCO2eq./kg)

Total Operate GHG emissions 

(kgCO2eq.)

842,667,086.99 1,125,465,142.67 

Key input parameters RD1 RD2 kgCO2eq. EIOLCA Name

Maintain

Maintain Launches 1,534 2,613

Maintain Starships Built 131 224

Total Prop needed Maintain 

launches (kg) 1,257,173,332.42 2,141,456,269.62 

Total Prop cost Maintain 

launches ($) $251,434,666.48 $428,291,253.92 

Total Maintain launcher 

metal mass (kg) 8,017,200.00 13,708,800.00 
69

Key input parameters RD1 RD2 kgCO2eq. EIOLCA Name

Total Maintain structure 

composite mass (kg) 890,800.00 1,523,200.00 

Total Maintain launcher 

harness mass (kg) 779,450.00 1,332,800.00 

Total Maintain launcher 

electronics mass (kg) 445,400.00 761,600.00 

Total Maintain launcher 

Electronics Structure mass 

(kg)

1,002,150.00 1,713,600.00 

Total Maintain launcher 

Electronics area (m2) 514,724.87 880,140.23 

Total Maintain launch impact 

(kgCO2eq.)

5,988,362,832.50 10,205,555,018.74 

Total Maintain Servicers 34 30

Total Maintain servicer metal 

mass (kg) 6,782.34 5,984.41 

Total Maintain servicer 

structure composite mass 

(kg)

2,906.72 2,564.75 

Total Maintain servicer 

harness mass (kg) 4,844.53 4,274.58 

Total Maintain servicer 

electronics mass (kg) 23,738.17 20,945.45 

Total Maintain electronics 

Structure mass (kg) 10,173.50 8,976.62 

Total Maintain servicer 

electronics area (m2) 12,058.43 10,639.79 

Total Maintain servicer 

impact (kgCO2eq.)

8,787,676.84 7,753,832.51 

Total Maintain PV area (m2) 22,946,000.00 38,000,000.00
70

Key input parameters RD1 RD2 kgCO2eq. EIOLCA Name

Maintain PV GHG emissions

(kgCO2eq.)

6,195,420.00 10,260,000.00

Cost of Maintain modules 

minus PV $3,113,493,938.78 $3,738,329,336.52 

GHG emissions of Maintain 

modules minus PV 

(kgCO2eq.)

541,747,945.35 650,469,304.56

GHG emissions of Maintain 

modules with PV (kgCO2eq.)

547,943,365.35 660,729,304.56

Maintain Mission Operations 

and Data Analysis (kgCO2eq.)

34,840,296.00 59,502,528.00 

Mission Program 

Management, Systems 

Engineering, and Mission 

Assurance GHG emissions

(kgCO2eq.)

866,121,037.33 860,859,041.04 163.11

Marketing, research and 

other miscellaneous 

professional, scientific, and 

technical support services 

(kgCO2eq./kUSD)

Total Maintain GHG 

emissions (kgCO2eq.)

7,446,055,208.03 11,794,399,724.84

Key input parameters RD1 RD2

Dispose

ADR Vehicles 59.00 100.00 

Total Dispose servicer metal mass (kg) 11,769.35 19,948.04 

Total Dispose servicer structure composite mass (kg) 5,044.01 8,549.16 

Total Dispose servicer harness mass (kg) 8,406.68 14,248.60 

Total Dispose servicer electronics mass (kg) 41,192.71 69,818.15 

Total Dispose electronics Structure mass (kg) 17,654.02 29,922.07 

Total Dispose servicer electronics area (m2) 20,924.93 35,465.98 
71

Key input parameters RD1 RD2

ADR vehicles GHG emissions 15,249,203.93 25,846,108.35 

ADR Launches 20.00 34.00 

ADR Starships Built 2 3

Total Prop needed Dispose launches (kg) 16,390,786.60 27,864,337.22 

Total Prop cost Dispose launches ($) $3,278,157.32 $5,572,867.44 

Total Dispose launcher metal mass (kg) 122,400.00 183,600.00 

Total Dispose structure composite mass (kg) 13,600.00 20,400.00 

Total Dispose launcher harness mass (kg) 11,900.00 17,850.00 

Total Dispose launcher electronics mass (kg) 6,800.00 10,200.00 

Total Dispose launcher Electronics Structure mass (kg) 15,300.00 22,950.00 

Total Dispose launcher Electronics area (m2) 7,858.39 11,787.59 

Total Dispose launch impact (kgCO2eq.) 79,794,345.28 133,295,682.50 

ADR Operations GHG emissions (kgCO2eq.) 763,952,825.32 1,194,230,666.73 

Total Dispose GHG emissions (kgCO2eq.) 828,497,966.66 1,301,680,240.88

Output RD1 RD2

System Total

Total GHG emissions (kgCO2eq.) 14,168,937,583.09 21,455,562,918.45

GHG emissions per kWh (gCO2eq./kWh) 26.58 40.38
72

Climate Comparisons

We compare SBSP systems to other baseload renewable electricity production technologies, as well 

as nuclear power. Wind power without storage is included for comparison as the lowest cost and 

emissions intensive technology tracked by NREL. GHG emissions comparisons are drawn from 

NREL’s Lifecycle Assessment Harmonization effort (National Renewable Energy Laboratory, 2023).

Table 25. GHG emissions Comparison. Source data from NREL: surveying thousands of publications, NREL documents the range 

of assessed GHG emissions, denoting low, median, and high impact assessment results for each technology. All units are in 

gCO2eq./kWh.

Technology (gCO2eq./kWh) Low Impact Median Impact High Impact

RD1 Baseline 26.58

RD2 Baseline 40.38

Nuclear 5 13 210

Hydropower 4 21 90

Utility-Scale Solar Photovoltaics 25 43 190

Concentrating Solar Power 10 28 90

Onshore Wind 6 13 50

Offshore Wind 6 13 50

Tidal 5 8 12

Geothermal 4 37 230

Natural Gas 350 486 950

Coal 840 1001 1690

Sensitivity Analyses

We performed several sensitivity analyses to assess the necessary conditions for commercially 

viable SBSP systems as compared to 2050 projections for existing renewable electricity production 

technologies. Parameters that could reasonably be expected to vary with uncertainty were 

considered; these relate to launch, manufacturing, and solar cell efficiency. After varying individual 

variables separately, we conclude with a multiple-variable sensitivity analysis which considers 
73

impacts of all manufacturing, launch, and solar cell modifications. To recreate these results, simply 

take the above data and relationships in calculation and modify as described below.

Launch

Sensitivity Analysis 1 - Reduced Launch Costs 1 a) $50M b) $10M

• Summary of modification(s): Reduction of Starship launch costs from $100,000,000 per 

launch to a) $50,000,000 and b) $10,000,000 per launch.

• Rationale: Baseline launch costs per kg take the lowest recorded cost (Falcon Heavy, 2019, 

$1500), and apply the same decrease in launch prices from the previous 10 years. SpaceX

has announced that Starship launches might reduce to $10,000,000 per launch in the 2024-

2025 timeframei. Additionally, launch costs declined 36% in the past 10 years. Based on 

these expectations and assuming launches in 2040, we consider medium and low scenarios 

for launch, which is the main driver of both SBSP system costs (Duffy, 2022).

• Result: For $50M, this results in a 32% total cost savings for the Innovative Heliostat Swarm 

and a 36% total cost savings for the Planar Array. For $10M, this results in a 61% reduction 

in cost for Innovative Heliostat Swarm, and 69% for Mature Planar Array.

Sensitivity Analysis 2 - Launch Direct to GEO

• Summary of modification(s): Starships take payloads directly to GEO, removing refuel 

launches and reusability, and reducing payload capacity to 21 MT.

• Rationale: Starship is able to deliver a fraction of its payload to GEO; this is a test of the 

costs and benefits of this approach.

• Result: While costs are reduced by at least 42% and 47% for RD1 and RD2, respectively, due 

to the reduced number of launches, GHG emissions decrease just 8% and 9%, respectively,

due to the increased number of Starships manufactured.

Sensitivity Analysis 3 - Electric Propulsion for Orbital Transfer

• Summary of modification(s): We added 17.2% of system mass and manufacturing cost 

based on propulsion mass per module, and removed launches to refuel in LEO. This 

modification is based on first order delta v calculations using specifications from NASA’s 

NEXT-C thruster (NASA, 2023), assuming >4,700m/s is needed to reach GEO from LEO.

• Rationale: Though using EP adds upmass, it can significantly reduce the number of launches 

required, as there is no need to refuel in LEO. This makes the most use out of Starship’s 

payload capacity to LEO, but comes at a cost of a longer time (about 4 months) to complete 

the orbital transfer.
74

• Result: This results in a 62% total cost savings for the Innovative Heliostat Swarm and a 69% 

total cost savings for the Mature Planar Array. The travel time from LEO to GEO increased to 

four months as opposed to refueling for one month and traveling for one month under 

chemical propulsion. The additional mass of the propulsion units did not appreciably change

assembly time.

Manufacturing

Sensitivity Analysis 1 - Initial Hardware Costs

• Summary of modification(s): We apply a 10% reduction in initial module costs, first servicer 

costs, and ADR vehicle base cost. The reduction in hardware costs affects all other 

parameters that use these costs as inputs, such as program management and technology 

development.

• Rationale: Original hardware costs for this analysis were based on U.S. Government 

technology demonstration missions. We reduce hardware development costs to levels 

provided by a survey of existing and upcoming commercial offerings performed by 

Aerospace. 

• Result: Combining all reduced costs results in an 19% total cost savings to the Innovative 

Heliostat Swarm and 14% total cost savings to the Mature Planar Array. 

Sensitivity Analysis 2 - Learning Curve Reduction

• Summary of modification(s): learning rate for servicers reduced from 85% to 80%, learning 

rate for modules reduced from 75% to 70%, and learning rate for ADR vehicles reduced 

from 90% to 80%.

• Rationale: Aerospace consistently used a learning curve model based on cumulative 

averages, which results in faster learning when compared to the model used for this 

analysis. This method leverages data from other industries with complex processes and 

production of 100s to 1,000s of units to evaluate learning rate and cost combinations. We 

therefore decrease our learning rates to be on par with this method while still considering 

the units-based Crawford model.

• Result: Considering all updated learning rates results in a 4% total cost savings for the 

Innovative Heliostat Swarm and a 3% total cost savings for the Mature Planar Array.

Sensitivity Analysis 3 - Increased Hardware Lifetime

• Summary of modification(s): Baseline module and servicer lifetime is set to 10 years. Here, 

the lifetime is increased to 15 years.

• Rationale: Today’s GEO hardware is most commonly baselined for a 15-year lifetime.

• Result: The extended lifetime leads to a reduction of one refurbishment cycle, saving 21% in 

fiscal costs for Innovative Heliostat Swarm and 23% in GHG emissions per kWh. For Mature 

Planar Array, the cost reduction was 29% and emissions reduction was 28%.
75

Solar Cell Efficiency

Sensitivity Analysis 1 - Solar Cell Efficiency (15% Increase)

• Summary of modification(s): Efficiency of solar cells is increased by 15 percentage points, 

from 35% to 50%.

• Rationale: NASA noted that the state of the practice for solar cell efficiency is 33%, while the 

state of the art is 70% (NASA, 2022). The best research cell efficiency currently tracked by 

NREL is 47.6% (NREL, n.d.).

• Result: The improvement in solar cell efficiency leads to a reduction in mass to deliver the 

same 2 GW of power, and therefore less manufacturing and fewer launches, resulting in 

19% cost savings for Innovative Heliostat Swarm, 23% for Mature Planar Array, and 25% 

GHG emissions reduction per kWh for Innovative Heliostat Swarm and 28% for Mature

Planar Array.

Multiple Variable Sensitivity Analyses

Sensitivity Analysis 1 – Competitive Solution

• Summary of modification(s): 

o Launch costs are here reduced from $100M to $50M. 

o Efficiency of solar cells is increased by 15%. 

o Initial servicer and ADR vehicle costs are reduced by 90%. 

o Learning curves are lowered by 5 percentage points across the board. 

o 1,720kg of EP (fuel + hardware) for every 10,000kg of system mass for orbital 

transfer; 17.2% additional cost to total module manufacturing cost.

• Rationale: Select sensitivities were combined with modifications to understand what 

conditions may lead the SBSP design references to become economically and 

environmentally competitive with existing renewable electricity technology projections for

2050.

• Result: Costs are reduced by 95% for both systems, and emissions intensity by 86% for 

Innovative Heliostat Swarm and 90% for Mature Planar Array.

Sensitivity Analysis 2 - Present Day Costs Only

• Summary of modification(s): 

o Launch costs are here increased from $100M to $150M. 

o Initial module cost is increased to $5M

o Learning curves are increased to 85% for modules and 95% for servicers and ADR 

vehicles. 

o Operations costs are increased from a flat fee to $500k per 2,800kg of system mass 

annually.

o Starship reuses are reduced from 100 to 50.
76

• Rationale: It is generally understood that SBSP is highly cost prohibitive with today’s costs, 

and technically infeasible with today’s technology. Simply for comparison, we apply more of 

today’s costs and capabilities.

• Result: Fiscal costs are increased 5.3 times for RD1 and 4.5 times for RD2. Emissions per 

kWh for both systems increase by a factor of 10.

Table 26. All Sensitivity Analysis Results

Sensitivity Analysis 

Grouping Technology / Scenario LCOE ($/kWh)

Emissions Intensity

(gCO2eq./kWh)

Baseline

RD1 Baseline 0.6 26.6

RD2 Baseline 1.6 40.4

Launch

RD1 Lower Launch Costs ($50M) 0.4 26.6

RD1 Lower Launch Costs ($10M) 0.2 26.6

RD2 Lower Launch Costs ($50M) 1 40.4

RD2 Lower Launch Costs ($100M) 0.5 40.4

RD1 Direct to GEO 0.3 24.4

RD2 Direct to GEO 0.8 36.6

RD1 Electric Propulsion Orbital Transfer 0.2 11.4

RD2 Electric Propulsion Orbital Transfer 0.5 14.2

Manufacturing

RD1 Extended Component Lifetime 0.5 19.3

RD2 Extended Component Lifetime 1.2 28.8

RD1 Lower Hardware Cost 0.5 19.5

RD2 Lower Hardware Cost 1.3 32.3

RD1 Lower Manufacturing Learning 0.6 22.6
77

Sensitivity Analysis 

Grouping Technology / Scenario LCOE ($/kWh)

Emissions Intensity

(gCO2eq./kWh)

RD2 Lower Manufacturing Learning 0.8 35.8

Solar Cell Efficiency

RD1 Efficient Solar Cells 0.5 20.4

RD2 Efficient Solar Cells 1.2 29.6

Multiple Variables 

RD1 ‘Competitive’ 0.03 3.6

RD2 ‘Competitive’ 0.08 4.2

RD1 ‘Present Day’ 4.18 286

RD2 ‘Present Day’ 10.73 360
Appendix C: Acknowledgements 

This appendix lists individuals and organizations who helped inform this study’s discussion of SBSP, 

whether through interviews, source material, reviews, or informal discussions. The authors of this 

study are extremely grateful for the time provided by the leading experts and institutions willing to 

impart their humbling level of expertise in the performance of this exploratory study. 

John Scott (NASA STMD) 

Heath Garvin (NREL) 

Roger Myers 

Paul Jaffe (NRL/USDR&E) 

James Winter (AFRL) 

John Mankins (Artemis Innovation 

Management Solutions) 

Wes Furnham (Applied Physics Laboratory) 

Murat Okandan (mPower) 

Alfred Nash (NASA JPL) 

Steve Matousek (NASA JPL) 

Matthew Weinzierl and team (Harvard) 

John Bucknell and team (Virtus Solis) 

Sergio Pellegrino and team (CalTech) 

Brent Sherwood (Blue Origin)

Peter Garretson (American Foreign Policy 

Council) 

Olga Spahn (Advanced Research Projects 

Agency-Energy, ARPA-E)

Guilherme Larangueira (ARPA-E)

Igor Cvetkovic (ARPA-E) 

Sanjay Vijendran (ESA) 

Leopold Summerer (ESA) 

Advenit Makaya (ESA) 

Zhiyuan Fan and team member (Columbia 

Center on Global Energy Policy) 

Douglas Hollett (DoE) 

Rima Oueid (DoE) 

Alex Ellery (Carleton University) 

Milo McBride (New York University Tandon 

School of Engineering) 

Gavin Schmidt (NASA Goddard Institute for 

Space Sciences) 

Paul Stackhouse (NASA Science Mission 

Directorate) 

The information contained in this report reflects the views and opinions of the authors and do not necessarily 

represent the views or opinions of, nor should be construed as endorsements by the individuals or 

organizations listed in Appendix C. 
79

Appendix D: Acronyms & Key Terms 

Acronym or Term Definition

ADR Active debris removal

AFRL Air Force Research Laboratory

ATB Annual Technology Baseline

Capacity factor (%) Maximum fractional portion of the year the system is producing 

power

CapEx Capital Expenditures

CapEx ($/kW) Initial capital expenditures to produce the system, per unit of 

energy generation

CO2 Carbon Dioxide

CO2 Carbon Dioxide

ConOps Concept of Operations

DARPA Defense Advanced Research Projects Agency

DC Direct Current

DoD Department of Defense

DoE Department of Energy

DSA Distributed Spacecraft Autonomy
80

Acronym or Term Definition

EIA Energy Information Agency

EIO-LCA Economic Input Output – Lifecycle Analysis

EP Electric Propulsion

EPA Environmental Protection Agency

ESA European Space Agency

EU European Union

Fixed charging rate (%) Annualized cost of a capital for the system (similar to a “discount 

rate”)

FOAK First-of-a-kind

FOM Fixed operations and maintenance

FOM ($/kw-year) Fixed annual expenditures for operations and maintenance per unit 

of generation

gCO2eq. Grams of carbon dioxide equivalent per kilowatt-hour

GEO Geostationary Orbit

GHG Greenhouse gas

GHz Gigahertz

GPIM Green Propellant Infusion Mission
81

Acronym or Term Definition

GTO Geostationary Transfer Orbit

IAEG International Aerospace Environmental Group

ISAM In-Space Assembly Manufacturing

ISS International Space Station

ITU International Telecommunications Union

JAXA Japan Aerospace Exploration Agency

KARI Korean Aerospace Research Institute

KERI Korean Energy Research Institute

kg / Mkg Kilogram / Million kilograms

kUSD Thousands of U.S. dollars

kW / MW / GW Kilowatt / Megawatt / Gigawatt

kWh / MWh Kilowatt-hour / Megawatt-hour

LCOE Levelized Cost of Electricity

LEO Low Earth Orbit

Lifecycle A series of stages through which something passes during its 

lifetime
82

Acronym or Term Definition

Lifecycle A series of stages through which something passes during its 

lifetime.

MEV Mission Extension Vehicle

MMmt Million Metric Tons

MOCET Mission Operations Cost Estimation Tool

MT Metric ton

NAICS North American Industry Classification System

NASA National Aeronautics and Space Administration

NIAC NASA Innovative Advanced Concepts 

NOAA National Oceanic and Atmospheric Administration

NREL National Renewable Energy Laboratory

NRL Naval Research Laboratory

O&M Operations and Maintenance

OGA Other Government Agency

OSAM On-Orbit Servicing, Assembly, and Manufacturing

OSTP Office of Science and Technology Policy

OTPS Office of Technology, Policy, and Strategy
83

Acronym or Term Definition

OTV Orbital Transfer Vehicle

PV Photovoltaic

R&D Research and Development

RD1, RD2 Representative Design 1, Representative Design 2

Renewables Electricity technologies that do not consume fossil fuels (oil, coal, 

gas) as a primary input for production

Renewables Electricity technologies that do not consume fossil fuels (oil, coal, 

gas) as a primary input for production

RF Radio frequency

RFP Request for proposals

RPO Rendezvous and Proximity Operations

SBSP Space-Based Solar Power 

SME Subject Matter Expert

SSPIDR

Space Solar Power Incremental Demonstrations and Research 

Project

STMD Space Technology Mission Directorate

TRL Technology Readiness Level

U.S. United States
84

Acronym or Term Definition

UK United Kingdom

UN United Nations

VOM ($/kWh) Variable operations and maintenance are expenditure per unit of 

generation for operations and maintenance

WBS Work Breakdown Structure
85

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