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2019 ATB

For each electricity generation technology in the ATB, this website provides:

  • Capital expenditures (CAPEX): the definition of CAPEX used in the ATB and the historical trends, current estimates, and future projections of CAPEX used in the ATB
  • Operations and maintenance (O&M) costs: the definition of O&M and the current estimates and future projections of O&M used in the ATB
  • Capacity factor (CF): the definition of CF and the historical trends, current estimates, and future projections of CF used in the ATB
  • Future cost and performance methods: an outline of the methodology used to make the projections of future cost and performance in the ATB for Constant, Mid, and Low technology cost cases
  • Levelized cost of energy (LCOE): metric that combines CAPEX, O&M, CF, and projections for Constant, Mid, and Low technology cost cases for illustration of the combined effect of the primary cost and performance components and discussion of technology advances that yield future projections
  • Financing assumptions: development of technology-specific interest rate on debt, return on equity, and debt-to-equity ratios and their impact on LCOE are documented in each technology section, where applicable, and summarized here.

Electricity generation technologies are selected on the left side of the screen, and the topics highlighted above can be selected using the drop-down menu at the top right of the screen.

Guidelines for using and interpreting ATB content and comparisons to other literature are provided. LCOE accounts for many variables important to determining the competitiveness of building and operating a specific technology (e.g., upfront capital costs, capacity factor, and cost of financing); however, it does not necessarily demonstrate which technology in a given place and time would provide the lowest cost option for the electricity grid. Such analysis is performed using electric sector models such as the Regional Energy Deployment Systems (ReEDS) model and corresponding analysis results such as the NREL Standard Scenarios.

The NREL Standard Scenarios, a companion product to the ATB, provides a suite of electric sector scenarios and associated assumptions, including technology cost and performance assumptions from the ATB.

ATB data sources and references are also provided for each technology. All dollar values are presented in 2017 U.S. dollars, unless noted otherwise.

Additional information is available here: About the 2019 ATB.

Concentrating Solar Power

Representative Technology

Concentrating solar power (CSP) technology is currently assumed to be molten-salt power towers. Thermal energy storage (TES) is accomplished by storing hot molten salt in a two-tank system, which includes a hot-salt tank and a cold-salt tank. Stored hot salt can be dispatched to the power block as needed, regardless of solar conditions, to continue power generation and allow for electricity generation after sunlight hours. In the ATB, CSP plants with 10 hours of TES are illustrated. Ten hours is the amount of storage at the Crescent Dunes CSP plant in Nevada, which is representative of most new molten-salt power tower projects.

Molten-salt power towers (with 10 hours of storage) were selected as the representative technology over parabolic trough with synthetic oil-heat transfer fluid for two main reasons. First, most new global capacity of CSP plants in development or under construction are molten-salt power towers; in 2015, 3.7 GWe of molten-salt power towers were in development or under construction ((IRENA 2018), (SolarReserve n.d.)) – compared to 1.3 GWe of parabolic trough (IRENA 2018). Second, current indications are that molten-salt power towers have the greatest cost reduction potential, in terms of both CAPEX and LCOE ((IRENA 2016), (Mehos et al. 2017)). And they are part of the DOE Generation 3 (Gen3) road map for the next generation of commercial CSP plants (Mehos et al. 2017).

Crescent Dunes (110 MWe with 10 hours of storage) was the first large molten-salt power tower plant in the United States. It was commissioned in 2015 with a reported installed CAPEX of $8.96/WAC ((Danko 2015), (Taylor 2016)). No new molten salt storage CSP plants were commissioned in the United States in 2018 or 2019. Molten-salt power tower plants are being bid and built in Chile and Dubai (NREL and SolarPaces n.d.).

Resource Potential

Solar resource is prevalent throughout the United States, but the Southwest is particularly suited to CSP plants. The direct normal irradiance (DNI) resource across the Southwest, which is some of the best in the world, ranges from 6.0 to more than 7.5 kWh/m2/day (Roberts 2018). The raw resource technical potential of seven western states (Arizona, California, Colorado, Nevada, New Mexico, Utah, and Texas) exceeds 11,000 GWe, which is almost tenfold current total U.S. electricity generation capacity-considering regions in these states with an annual average resource > 6.0 kWh/m2/day. After accounting for exclusions such as land slope (> 1%), urban areas, water features, and parks, preserves, and wilderness areas (Mehos, Kabel, and Smithers 2009).

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Map of mean solar resource available to CSP systems in the United States (Roberts 2018)

Renewable energy technical potential, as defined by Lopez et al. (2012), represents the achievable energy generation of a particular technology given system performance, topographic limitations, and environmental and land-use constraints. The primary benefit of assessing technical potential is that it establishes an upper-boundary estimate of development potential. It is important to understand that there are multiple types of potential – resource, technical, economic, and market (see NREL: "Renewable Energy Technical Potential").

The Solar Programmatic Environmental Impact Statement identified 17 solar energy zones for priority development of utility-scale solar facilities in six western states. These zones total 285,000 acres and are estimated to accommodate up to 24 GWe of solar potential. The program also allows development, subject to a more rigorous review, on an additional 19 million acres of public land. Development is prohibited on approximately 79 million acres.

According to NREL's Concentrating Solar Power Projects website and the CSP Today Global Projects Tracker ("CSP Today Global Tracker" n.d.), 12 of the 14 currently operational CSP plants greater than 5 MWe in the United States use parabolic trough technology, and two are power tower facilities – Ivanpah (392 MWe, utilizing direct steam generation in the towers) and Crescent Dunes (110 MWe, as highlighted, utilizing molten-salt in the tower).

Base Year and Future Year Projections Overview

For the ATB, various factors are used to demonstrate the range of LCOE and performance across the United States. These include:

  • CAPEX is determined using manufacturing cost models and is benchmarked with industry data. CSP performance and cost are based on the molten-salt power tower technology with dry-cooling to reduce water consumption.
  • O&M cost is benchmarked against industry data.
  • Capacity factor varies with inclusion of TES and solar irradiance. The listed resource classes assume power towers with 10 hours of TES at three types of locations:
    • Fair resource (e.g., Abilene Regional Airport, Texas 6.16 kWh/m2/day based on the National Solar Radiation Database [NSRDB] site 2017 Physical Solar Model [PSM] TMY file)
    • Good resource (e.g., Phoenix, Arizona 7.26 kWh/m2/day based on the site TMY3 file)
    • Excellent resource (e.g., Daggett, California 7.65 kWh/m2/day based on the site TMY3 file)
  • Representative CSP plant size is net 100 MWe.

The CSP costs originated from: (1) a NREL survey leading to updated cost estimates in the System Advisor Model (SAM) 2017.09.05; and (2) further cost estimates for CSP components which are now present in SAM 2018.11.11 (Craig Turchi et al. 2019). These SAM 2018 CSP costs were deflated to the ATB Base Year of 2017 via the consumer price index. The SAM 2018 costs translate to ATB costs in 2021 due to the three-year construction period. (SAM costs are based on the project announcement year, while the ATB is based on the plant commissioning year).

Future year projections are informed by a variety of published literature, NREL expertise and technology pathway assessments for CAPEX and O&M cost reductions. Three different projections were developed for scenario modeling as bounding levels:

  • Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from current estimates (2021 for CSP) to 2050; consistent across all renewable energy technologies in the ATB
  • The Mid Technology Cost Scenario is based on recently published literature projections and NREL judgment of U.S. costs for future CAPEX at 2025, 2030, 2040 and 2050 ((IRENA 2016), (Breyer et al. 2017), (Feldman et al. 2016), and (World Bank 2014)). It is anticipated that CSP costs could fall by approximately 25% from the ATB CSP 2021 costs of $6,450/kWe to approximately $4,800/kWe by 2030. From 2030 to 2050, CSP CAPEX is projected to fall to approximately $3,380/kWe.
  • The Low Technology Cost Scenario is based on the lower bound of the literature sample, and on the Power to Change report (IRENA 2016).

Capital Expenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. These expenditures include the generation plant, the balance of system (e.g., site preparation, installation, and electrical infrastructure), and financial costs (e.g., development costs, and interest during construction) and are detailed in CAPEX Definition. In the ATB, CAPEX reflects typical plants and does not include differences in regional costs associated with labor, materials, taxes, or system requirements. The related Standard Scenarios product uses Regional CAPEX Adjustments. The range of CAPEX demonstrates variation with resource in the contiguous United States.

The following figure shows the Base Year estimate and future year projections for CAPEX costs. Three cost scenarios are represented: Constant, Mid, and Low. The estimate for a given year represents CAPEX of a new plant that reaches commercial operation in that year (i.e., SAM 2018 CSP costs are reflected in the ATB in 2021).

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R&D Only Financial Assumptions (constant background rates, no tax changes)

Base Year Estimates

CAPEX is unchanged for resource class because the same plant is assumed to be built in each location. The capacity factor will change with resource.

TES increases plant CAPEX but also increases capacity factor and annual efficiency. TES generally lowers LCOE for power towers.

The CAPEX estimate (with a base year of 2017) is approximately $7,730/kWe in 2017$. It is for a representative power tower with 10 hours of storage and a solar multiple of 2.4. Based on recent assessment of the industry in 2017 and updated CSP systems costs reflected in SAM 2018.11.11 (Craig Turchi et al. 2019), the CAPEX estimate for 2021 is $6,450/kWe in 2017$.

Future Year Projections

Three cost projections are developed for CSP technologies:

  • Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from current estimates (2021 for CSP) to 2050; consistent across all renewable energy technologies in the ATB
  • The Mid Technology Cost Scenario is based on recently published literature projections and NREL judgment of U.S. costs for future CAPEX at 2025, 2030, 2040 and 2050 ((IRENA 2016), (Breyer et al. 2017), (Murphy et al. 2019), (Feldman et al. 2016), and (World Bank 2014)). It is anticipated that CSP costs could fall by approximately 25% from the ATB CSP 2021 costs of $6,450/kWe to approximately $4,800/kWe by 2030. From 2030 to 2050, CSP CAPEX is projected to fall to approximately $3,380/kWe.
  • The Low Technology Cost Scenariois based on the lower bound of the literature sample, and on the Power to Change report (IRENA 2016).

Relative to today's reported CAPEX for plants either announced or in construction, $6,450/kWe in the ATB in 2021 and $4,800/kWe in 2030 is possible. For example, Noor III (150 MWe molten salt power tower with 7.5 hours of storage and operational in 2018), had an estimated CAPEX of $6,500/kWe in 2017$ (Kistner 2016). The Dubai Electricity and Water Authority (DEWA) 700-MWe CSP portion (600-MWe parabolic trough and 100-MWe molten salt tower, each with 12-15 hours of storage), which is in construction had an estimated bundled CAPEX of $5,500/kWe ( (Shemer 2018), (Craig Turchi et al. 2019)).

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.

The ATB represents the year in which a plant starts commercial operation. Accordingly, for plants whose construction duration exceeds one year, CAPEX costs will represent technology costs that are lagging current-year estimates by at least one year. For CSP plants, the construction period is typically three years.

For the ATB – and based on key sources ((EIA 2016), (C. Turchi 2010), and (Craig Turchi and Heath 2013)) – the CSP generation plant envelope is defined to include:

  • CSP generation plant
  • Solar collectors
  • Solar receiver
  • Piping and heat-transfer fluid system
  • Power block (heat exchangers, power turbine, generator, and cooling system)
  • Thermal energy storage system
  • Installation
  • Balance of system, including installation, land acquisition, electrical infrastructure, and project indirect costs
  • Land acquisition, site preparation, and installation of underground utilities, access roads, fencing, and buildings for operations and maintenance
  • Electrical infrastructure, such as transformers, switchgear, and electrical system connecting modules to each other and to control the center; the generator voltage is 13.8 kV, the step-up transformer is 13.8/230kV, and the transmission tie line is 230 kV
  • Project indirect costs, including costs related to engineering, distributable labor and materials, construction management start up and commissioning, and contractor overhead costs, fees, and profit
  • Financial costs
  • Owners' costs, such as development costs, preliminary feasibility and engineering studies, environmental studies and permitting, legal fees, insurance costs, and property taxes during construction
  • Onsite electrical equipment (e.g., switchyard), a nominal-distance spur line (< 1 mile), and necessary upgrades at a transmission substation; distance-based spur line cost (GCC) not included in the ATB
  • Interest during construction estimated based on three-year duration accumulated 80%/10%/10% at half-year intervals and a nominal interest rate (ConFinFactor).

CAPEX can be determined for a plant in a specific geographic location as follows:

CAPEX   =   ConFinFactor × (OCC × CapRegMult + GCC)
(See the Financial Definitions tab in the ATB data spreadsheet)

Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).

In the ATB, CAPEX represents a typical solar-CSP plant with 10 hours of thermal storage and does not vary with resource. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by the U.S. Energy Information Administration (EIA 2016) expand the range of CAPEX. Unique land-based spur line costs based on distance and transmission line costs expand the range of CAPEX even further. The following figure illustrates the ATB representative plant relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.

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R&D Only Financial Assumptions (constant background rates, no tax changes)

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.

CAPEX in the ATB does not represent regional variants (CapRegMult) associated with labor rates, material costs, etc., but the ReEDS model does include 134 regional multipliers (EIA 2016).

The ReEDS model determines the land-based spur line (GCC) uniquely for each potential CSP plant based on distance and transmission line cost.

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a solar CSP plant over its lifetime, including:

  • Operating and administrative labor, insurance, legal and administrative fees, and other fixed costs
  • Utilities (water, power, and natural gas if any) and mirror washing
  • Scheduled and unscheduled maintenance, including replacement parts for solar field and power block components over the technical lifetime of the plant.

The following figure shows the Base Year estimate and future year projections for fixed O&M (FOM) costs. Three cost scenarios are represented. The estimate for a given year represents annual average FOM costs expected over the technical lifetime of a new plant that reaches commercial operation in that year.

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Base Year Estimates

FOM is assumed to be $66/kW-yr until 2021. Variable O&M is approximately $4.1/MWh until 2021 and $3.50/MWh after that (Kurup and Turchi 2015).

Future Year Projections

Future FOM is assumed to decline to $51/kW-yr by 2030 in the Mid cost case (i.e., approximately a 25% drop) and approximately $40/kW-yr by 2030 in the Low cost case based on DOE investments likely to help to lower costs (DOE 2012).

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the expected annual average energy production divided by the annual energy production, assuming the plant operates at rated capacity for every hour of the year. It is intended to represent a long-term average over the lifetime of the plant. It does not represent interannual variation in energy production. Future year estimates represent the estimated annual average capacity factor over the technical lifetime of a new plant installed in a given year.

Capacity factors are influenced by power block technology, storage technology and capacity, the solar resource, expected downtime, and energy losses. The solar multiple is a design choice that influences the capacity factor.

The following figure shows a range of capacity factors based on variation in the resource, for locations where currently CSP plants could be built in the contiguous United States. The range of the Base Year estimates illustrates the effect of locating a CSP plant at a site with Fair, Good, or Excellent solar resource. The future projections for the Constant, Mid, and Low technology cost scenarios are unchanged from the Base Year. Technology improvements are focused on CAPEX and O&M cost elements.

/electricity/2019/images/solar-csp/chart-solar-csp-capacity-factor-2019.png

Base Year Estimates

For illustration in the ATB, a range of capacity factors calculated in SAM 2018.11.11 (NREL n.d.) is associated with three resource locations in the contiguous United States, as represented in the ReEDS model for three classes of insolation:

  • Fair resource: Abilene, Texas: 6.16 kWh/m2/day based on the site TMY3 file, leads to a 50% capacity factor; the 2017 PSM TMY file for a site adjacent to the airport is used, and it was downloaded from the NSRDB (NREL n.d.).
  • Good resource: Phoenix, Arizona: 7.26 kWh/m2/day based on the site TMY3 leads to a 61% capacity factor; the TMY file used is available in SAM 2018.11.11(NREL n.d.), titled "phoenix_az_33.450495_-111.983688_psmv3_60_tmy"..
  • Excellent resource: Daggett, California: 7.65 kWh/m2/day based on the site TMY3 file, leads to a 64% capacity factor; the TMY file used is available in SAM 2018.11.11 (NREL n.d.), titled "daggett_ca_34.865371_-116.783023_psmv3_60_tmy".

A key finding from a recent report is that if future costs of CSP decrease sufficiently, it could be deployed across a greater range of the United States and DNI resources. For example, with aggressive cost decreases and due to the regional market constraints, southeastern states with lower DNI resources (e.g., Florida and South Carolina) could see increased CSP capacity deployments of up to 5 GWe (Murphy et al. 2019).

Future Year Projections

The CSP technologies highlighted in the ATB are assumed to be power towers but with different power cycles and operating conditions as time passes:

  • 2017: a molten-salt (sodium nitrate/potassium nitrate; aka, solar salt) power tower with direct two-tank TES combined with a steam-Rankine power cycle running at 574° C and 41.2% gross efficiency
  • 2021: a similar design to that of 2017 with identified near-term reductions in heliostat and power system costs
  • 2030 Mid Technology Cost Scenario: longer-term cost reductions (e.g., in the heliostats and power system)
  • 2030 Low Technology Cost Scenario: In the ATB, the Low projection is based on molten-salt power tower with direct two-tank TES combined with a power cycle running at 700° C and 55% gross efficiency.

While an advanced molten salt projection is used for the ATB Low Cost scenario, lower costs for baseload CSP are being investigated via different technology options (i.e. Solid Particle and Gas phase towers) and as defined by the CSP Gen3 program ((EERE n.d.), (Mehos et al. 2017)).

Over time, CSP plant output may decline. Capacity factor degradation due to mirror and other component degradation is not accounted for in ATB estimates of capacity factor or LCOE.

The ATB capacity factors are generated from Constant, Mid and Low technology cost plant simulations in SAM 2018.11.11 (NREL n.d.).

Estimates of capacity factors for CSP in the ATB represent typical operation. The dispatch characteristics of these systems are valuable to the electric system to manage changes in net electricity demand. Actual capacity factors will be influenced by the degree to which system operators call on CSP plants to manage grid services.

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.

CSP plants with TES can be dispatched by grid operators to accommodate diurnal and seasonal load variations and output from variable generation sources (wind and solar PV). Because of this, their annual energy production and the value of that generation are determined by the electric system needs and capacity and ancillary services markets.

Plant Cost and Performance Projections Methodology

A range of literature projections is shown to illustrate the comparison with the ATB. When comparing the ATB projections with other projections, note that there are major differences in technology assumptions, radiation conditions, field sizes, storage configurations, and other factors. As shown in the chart, the ATB 2019 CSP Mid projection is in line with other recently analyzed projections from other organizations. The Low cost ATB projection is based on the lower bound of the literature sample, and on the Power to Change report (IRENA 2016).

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Projections of future utility-scale CSP plant CAPEX and O&M are based on three different technology cost scenarios that were developed for scenario modeling as bounding levels:

  • Constant Technology Cost Scenario
    • Modeled as molten-salt (sodium nitrate/potassium nitrate, aka, solar salt) power tower with direct two-tank TES combined with a steam-Rankine power cycle running at 574°C and 41.2% gross efficiency in 2017
    • Costs stay the same from the 2021 estimate through 2050, consistent with ATB renewable energy technologies
  • Mid Technology Cost Scenario:
    • Based on recently published literature projections and NREL judgment of U.S. costs for future CAPEX in 2025, 2030, 2040 and 2050 ((IRENA 2016), (Breyer et al. 2017), (Murphy et al. 2019), (Feldman et al. 2016), and (World Bank 2014)).
      • It is anticipated that CSP costs could fall by approximately 25% from the ATB CSP 2021 costs of $6,450/kWe to approximately $4,800/kWe by 2030.
      • CSP CAPEX is projected to fall from 2030 to 2050 to approximately $3,380/kWe.
    • The cost reductions are anticipated due to gradual reductions in heliostat and power system cost due to greater deployment volume and learning assumed for 2021 and onwards based on current state of industry ((IRENA 2016), (Lilliestam et al. 2017)).
    • CAPEX and O&M both drop by approximately 25% by 2030, relative to 2021 costs
    • A further 30% overall CAPEX decrease is estimated from 2030 to 2050. All three components of the CSP CAPEX (the turbine, storage, and the solar field), decrease proportionately by approximately 30% from 2030 to 2050.
  • Low Technology Cost Scenario:
    • Significant reductions in heliostat and power system cost due to greater deployment volume and R&D are used for 2021 onwards; the plant was modeled as an advanced molten-salt power tower with direct two-tank TES combined with a power cycle running at 700°C and 55% gross efficiency in 2030 (Mehos et al. 2017).
    • CAPEX and O&M decrease from likely cost reductions including new high-efficiency power cycles and low-cost heliostats.
    • A further 20% overall CAPEX decrease is assumed from 2030 to 2050 based on potential deployment in the United States. The 20% decrease in overall CSP CAPEX is split over the three components: the turbine, storage, and the solar field. It can be expected that greater cost reductions could be achieved for the power block/turbine and the solar field than for the storage.

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a summary metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies such as CSP can provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for power-tower CSP across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs but not in the upfront capital costs (e.g., developer fees and contingencies). An individual technology may receive more favorable financing terms outside the United States, due to less technology and project risk, caused by more project development experience (e.g., offshore wind in Europe) or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, and changing interest rates over time. The R&D + Market LCOE case adds to these financial assumptions: (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform and tax credits. For example, the projected LCOE for most utility scale renewable energy generation technologies could potentially increase from the end of 2020 due to the decreasing levels of the ITC. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term CSP plants are associated with Tower-Excellent Resource. Data for all the resource categories can be found in the ATB Data spreadsheet; for simplicity, not all resource categories are shown in the figures.

Note: the future projection of the "Good resource" (i.e., for a CSP plant built in Phoenix, Arizona) is not shown in the figures to simplify the figures and because the projection lies between the Excellent and the Fair Resource projections.

R&D Only | R&D + Market

R&D Only
/electricity/2019/images/solar-csp/chart-solar-csp-lcoe-RD-2019.png
R&D + Market
/electricity/2019/images/solar-csp/chart-solar-csp-lcoe-market-2019.pngR&amp;D + Market
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term CSP plants are associated with Tower-Excellent Resource.
R&D Only Financial Assumptions (constant background rates, no tax changes)
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term CSP plants are associated with Tower-Excellent Resource.
R&D Only + Market Financial Assumptions (dynamic background rates, taxes)

The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. In general, the degree of adoption of technology innovation distinguishes the Constant, Mid, and Low technology cost scenarios. These projections represent trends that reduce CAPEX and improve performance. Development of these scenarios involves technology-specific application of the following general definitions:

  • Constant Technology: Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
  • Mid Technology Cost Scenario: Technology advances through continued industry growth, public and private R&D investments, and market conditions relative to current levels that may be characterized as "likely" or "not surprising"
  • Low Technology Cost Scenario: Technology advances that may occur with breakthroughs, increased public and private R&D investments, and/or other market conditions that lead to cost and performance levels that may be characterized as the " limit of surprise" but not necessarily the absolute low bound.

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Two project finance structures are used within the ATB:

  • R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2017 values from AEO2019 (EIA 2019) and excludes effects of tax reform and tax credits.
  • R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO2019 (EIA 2019) as well as effects of tax reform and tax credits. For a detailed discussion of these assumptions, see Project Finance Impact on LCOE.

A constant cost recovery period – over which the initial capital investment is recovered – of 30 years is assumed for all technologies throughout this website, and can be varied in the ATB data spreadsheet.

The equations and variables used to estimate LCOE are defined on the Equations and Variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2019 ATB Cost and Performance Summary.

For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2019 ATB Cost and Performance Summary.

In general, differences among the technology cost cases reflect different levels of adoption of innovations. Reductions in technology costs reflect the cost reduction opportunities that are listed below.

  • Power tower improvements
    • Better and longer-lasting selective surface coatings improve receiver efficiency and reduce O&M costs.
    • New salts allow for higher operating temperatures and lower-cost TES.
    • Development of the power cycle running at approximately 700°C and 55% gross efficiency improves cycle efficiency, reduces powerblock cost, and reduces O&M costs.
    • Lower-cost heliostats developed due to design changes and automated and high-volume manufacturing.
  • General and "soft" costs improvements
    • Expansion of world market leads to greater and more efficient supply chains, and reduction of supply chain margins (e.g., profit and overhead charged by suppliers, manufacturer, distributors, and retailers).
    • Expansion of access to a range of innovative financing approaches and business models
  • The LCOE range shown is based on locations with Fair (Abilene, Texas), Good (Phoenix, Arizona), and Excellent (Daggett, California) resources. The CAPEX is the same for each resource as the same plant is used. Future-year LCOE projections for the Good case are not shown to simplify the figure. Using the R&D Only scenario and financials, and with the capacity factor of 64% for Daggett, California (NREL n.d.), in the Mid case by 2030, the LCOE could reach approximately 55$/MWh, and it could potentially reach $47/MWh by 2050.

Nuclear

The ATB includes a single nuclear power plant type. The cost and performance of this plant type is adapted from EIA data rather than derived from original analysis.

Capital Expenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections

Nuclear power plant CAPEX is taken from the AEO2019 Reference Scenario (EIA, 2019a) with the adjustments discussed in the CAPEX definition section. The EIA advanced nuclear option is based on two AP1000 nuclear power plant units built on a brownfield site. The ATB includes only a single CAPEX projection for nuclear plants.

/electricity/2019/images/nuclear/chart-nuclear-capex-RD-2019.png
Current estimates and future projections calculated from AEO2019 (EIA, 2019a) and modified.
R&D Only Financial Assumptions (constant background rates, no tax changes)

Comparison with Other Sources

/electricity/2019/images/nuclear/chart-nuclear-overnight-capital-cost-2019.png
ATB cost numbers are for a brownfield nuclear facility.
Data sources include the ATB, Black & Veatch (2012), Entergy Arkansas (2015),Varro and Ha(2015), and Lazard (2016).
All sources have been normalized to the same dollar year. Costs vary due to differences in system design, methodology, and plant cost definitions.

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.

Overnight capital costs are modified from AEO2019 (EIA, 2019a). The EIA projections were adjusted by removing the material price index. The material price index accounts for projected changes in the price index for metals and metals products, and it is independent of the learning-based cost reductions applied in the EIA projections.

Overnight Capital Cost ($/kW) Construction Financing Factor (ConFinFactor) CAPEX ($/kW)
Nuclear: Advanced nuclear power generation $6,200 1.087 $6,742

CAPEX can be determined for a plant in a specific geographic location as follows:

CAPEX = ConFinFactor × (OCC × CapRegMult + GCC)
See the Financial Definitions tab in the ATB data spreadsheet.

Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).

In the ATB, CAPEX represents each type of nuclear plant with a unique value. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by (EIA, 2016) expand the range of CAPEX (Plant × Region). Unique land-based spur line costs based on distance and transmission line costs are not estimated. The following figure illustrates the ATB representative plant relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.

/electricity/2019/images/nuclear/chart-nuclear-capex-definition-RD-2019.png
R&D Only Financial Assumptions (constant background rates, no tax changes)

Operation and Maintenance (O&M) Costs

Nuclear power plant fixed and variable O&M costs are taken from table 8.2 of the AEO2019, and they are assumed to be constant over time.

/electricity/2019/images/nuclear/chart-nuclear-operation-maintenance-2019.png

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the assumed annual energy production divided by the total possible annual energy production, assuming the plant operates at rated capacity for every hour of the year. For nuclear plants, the capacity factor is typically the same as (or very close to) their availability factor. For the ATB we assign the nuclear capacity factor as the fleet-wide average from 2017.

/electricity/2019/images/nuclear/chart-nuclear-capacity-factor-2019.png
Current estimates and future projections calculated from AEO2019 (EIA, 2019a) and modified.

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a summary metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for nuclear across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs but not in the upfront capital costs (e.g., developer fees and contingencies). An individual technology may receive more favorable financing terms outside the United States, due to less technology and project risk, caused by more project development experience (e.g., offshore wind in Europe) or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, and changing interest rates over time. The R&D + Market LCOE case adds to these financial assumptions: (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform and tax credits.

R&D Only | R&D + Market

R&D Only
/electricity/2019/images/nuclear/chart-nuclear-lcoe-RD-2019.png
R&D + Market
/electricity/2019/images/nuclear/chart-nuclear-lcoe-market-2019.png
R&D Only Financial Assumptions (constant background rates, no tax changes)
R&D Only + Market Financial Assumptions (dynamic background rates, taxes)

The LCOE of nuclear power plants is directly impacted by the cost of uranium, variations in the heat rate, and O&M costs, but the biggest factor is the capital cost (including financing costs) of the plant. The LCOE can also be impacted by the amount of downtime from refueling or maintenance. For a given year, the LCOE assumes that the fuel prices from that year continue throughout the lifetime of the plant.

Fuel prices are based on the AEO2019 (EIA, 2019a).

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Two project finance structures are used within the ATB:

  • R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2017 values from AEO2019 (EIA, 2019a) and excludes effects of tax reform and tax credits. A constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies.
  • R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO2019 (EIA, 2019a) as well as effects of tax reform and tax credits. As in the R&D Only case, a constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies. For a detailed discussion of these assumptions, see Project Finance Impact on LCOE.

The equations and variables used to estimate LCOE are defined on the Equations and Variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2019 ATB Cost and Performance Summary.

Biopower

The ATB includes both dedicated biopower cost options and a biomass cofired with coal option. The cost and performance characteristics of these plants are adapted from EIA data rather than derived from original analysis.

Capital Expenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections

Biopower plant CAPEX is taken from the AEO2019 Reference Scenario (EIA, 2019a) with the adjustments discussed in the CAPEX definition section.

/electricity/2019/images/biomass/chart-biomass-capex-RD-2019.png
Current estimates and future projections calculated from AEO2019 (EIA, 2019a) and modified.
R&D Only Financial Assumptions (constant background rates, no tax changes)

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.

Overnight capital costs are modified from AEO2019 (EIA, 2019a). The EIA projections were adjusted by removing the material price index. The material price index accounts for projected changes in the price index for metals and metals products, and it is independent of the learning-based cost reductions applied in the EIA projections.

Fuel costs are taken from the Billion Ton Update study (DOE et al., 2011).

Overnight Capital Cost ($/kW) Construction Financing Factor (ConFinFactor) CAPEX ($/kW)
Dedicated: Dedicated biopower plant $3,827 1.042 $3,990
CofireOld: Pulverized coal with sulfur dioxide (SO2) scrubbers and biomass co-firing $4,013 1.042 $4,184
CofireNew: Advanced supercritical coal with SO2 and NOx controls and biomass co-firing $4,013 1.042 $4,184

CAPEX can be determined for a plant in a specific geographic location as follows:

CAPEX = ConFinFactor × (OCC × CapRegMult + GCC)
See the Financial Definitions tab in the ATB data spreadsheet.

Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).

In the ATB, CAPEX represents each type of biopower plant with a unique value. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by (EIA, 2016) expand the range of CAPEX. Unique land-based spur line costs based on distance and transmission line costs are not estimated. The following figure illustrates the ATB representative plant relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.

/electricity/2019/images/biomass/chart-biomass-capex-definition-RD-2019.png
R&D Only Financial Assumptions (constant background rates, no tax changes)

Operation and Maintenance (O&M) Costs

Biopower power plant fixed and variable O&M costs are taken from table 8.2 of the AEO2019, and they are assumed to be constant over time.

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the assumed annual energy production divided by the total possible annual energy production, assuming the plant operates at rated capacity for every hour of the year. For biopower plants, the capacity factors are typically lower than their availability factors. Biopower plant availability factors have a wide range depending on system design, fuel type and availability, and maintenance schedules.

Biopower plants are typically baseload plants with steady capacity factors. For the ATB, the biopower capacity factor is taken as the average capacity factor for biomass plants for 2017, as reported by EIA.

Biopower capacity factors are influenced by technology and feedstock supply, expected downtime, and energy losses.

/electricity/2019/images/biomass/chart-biomass-capacity-factor-2019.png
Current estimates and future projections are taken as the 2017 capacity factor from EIA (2019b).

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a summary metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for biomass across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs but not in the upfront capital costs (e.g., developer fees and contingencies). An individual technology may receive more favorable financing terms outside the United States, due to less technology and project risk, caused by more project development experience (e.g., offshore wind in Europe) or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, and changing interest rates over time. The R&D + Market LCOE case adds to these financial assumptions: (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform and tax credits. Data for all the resource categories can be found in the ATB data spreadsheet; for simplicity, not all resource categories are shown in the figures.

R&D Only | R&D + Market

R&D Only
/electricity/2019/images/biomass/chart-biomass-lcoe-RD-2019.png
R&D + Market
/electricity/2019/images/biomass/chart-biomass-lcoe-market-2019.png
R&D Only Financial Assumptions (constant background rates, no tax changes)
R&D Only + Market Financial Assumptions (dynamic background rates, taxes)

The LCOE of biopower plants is directly impacted by the differences in CAPEX (installed capacity costs) as well as by heat rate differences. For a given year, the LCOE assumes that the fuel prices from that year continue throughout the lifetime of the plant.

Regional variations will ultimately impact biomass feedstock costs, but these are not included in the ATB.

The projections do not include any cost of carbon.

Fuel costs are taken from the Billion Ton Update study (DOE et al., 2011).

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Two project finance structures are used within the ATB:

  • R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2017 values from AEO2019 (EIA, 2019a) and excludes effects of tax reform and tax credits. A constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies.
  • R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO2019 (EIA, 2019a) as well as effects of tax reform and tax credits. As in the R&D Only case, a constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies. For a detailed discussion of these assumptions, see Project Finance Impact on LCOE.

The equations and variables used to estimate LCOE are defined on the Equations and Variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2019 ATB Cost and Performance Summary.

References

The following references are specific to this page; for all references in this ATB, see References.

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DOE. (2011). U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry (No. ORNL/TM-2011/224). https://doi.org/10.2172/1023318

DOE. (2012). SunShot Vision Study. Retrieved from https://www1.eere.energy.gov/solar/pdfs/47927.pdf

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Entergy Arkansas. (2015). 2015 Integrated Resource Plan. Retrieved from Entergy Arkansas, Inc. website: http://entergy-arkansas.com/content/transition_plan/IRP_Materials_Compiled.pdf

Feldman, D., Margolis, R., Denholm, P., & Stekli, J. (2016). Exploring the Potential Competitiveness of Utility-Scale Photovoltaics plus Batteries with Concentrating Solar Power, 2015-2030 (No. NREL/TP-6A20-66592). https://doi.org/10.2172/1321487

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Kurup, P., & Turchi, C. (2015). Parabolic Trough Collector Cost Update for the System Advisor Model (SAM) (No. NREL/TP-6A20-65228). https://doi.org/10.2172/1227713

Lazard. (2016). Lazard's Levelized Cost of Energy Analysis: Version 10.0. Retrieved from Lazard website: https://www.lazard.com/media/438038/levelized-cost-of-energy-v100.pdf

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Lopez, A., Roberts, B., Heimiller, D., Blair, N., & Porro, G. (2012). U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis (Technical Report No. NREL/TP-6A20-51946). https://doi.org/10.2172/1219777

Mehos, M., Kabel, D., & Smithers, P. (2009). Planting the Seed: Greening the Grid with Concentrating Solar Power. IEEE Power and Energy Magazine, 7(3), 55–62. https://doi.org/10.1109/MPE.2009.932308

Mehos, M., Turchi, C., Vidal, J., Wagner, M., & Ma, Z. (2017). Concentrating Solar Power Gen3 Demonstration Roadmap (No. NREL/TP-5500-67464). https://doi.org/10.2172/1338899

Murphy, C., Sun, Y., Cole, W., Maclaurin, G., Turchi, C., & Mehos, M. (2019). The Potential Role of Concentrating Solar Power Within the Context of DOE's 2030 Solar Cost Targets (No. NREL/TP-6A20-71912). https://doi.org/10.2172/1491726

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Turchi, Craig, Boyd, M., Kesseli, D., Kurup, P., Mehos, M., Neises, T., … Wendelin, T. (2019). CSP Systems Analysis - Final Project Report (No. NREL/TP-5500-72856). Retrieved from National Renewable Energy Laboratory website: https://www.nrel.gov/docs/fy19osti/72856.pdf

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