Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a simple 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 commercial PV 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, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., 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, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term commercial PV plants are associated with Comm (commercial) PV: Kansas City. Data for all the resource categories can be found in the ATB data spreadsheet.

R&D Only | R&D + Market

• R&D Only
• R&D + Market
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R&D Only

The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term commercial PV plants are associated with Comm PV: Kansas City

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

R&D + Market

The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term commercial PV plants are associated with Comm PV: Kansas City

R&D Only + Market Financial Assumptions (dynamic background rates, taxes, and tariffs)

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 Cost Scenario = 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. Three 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 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs.
• 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 AEO 2018, as well as effects of tax reform, tax credits, and technology-specific tariffs. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
• ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.

A constant cost recovery period -over which the initial capital investment is recovered-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 2018 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.

• Modules
  • Increased module efficiencies and increased production-line throughput to decrease CAPEX; overhead costs on a per-kilowatt basis will go down if efficiency and throughput improvement are realized
  • Reduced wafer thickness or the thickness of thin-film semiconductor layers
  • Development of new semiconductor materials
  • Development of larger manufacturing facilities in low-cost regions
• Balance of system (BOS)
  • Increased module efficiency, reducing the size of the installation
  • Development of racking systems that enhance energy production or require less robust engineering
  • Integration of racking or mounting components in modules
  • Reduction of supply chain complexity and cost
  • Creation of standard packaged system design
  • Improvement of supply chains for BOS components in modules
  • Improved power electronics
  • Improvement of inverter prices and performance, possibly by integrating microinverters
  • Decreased installation costs and margins
  • Reduction of supply chain margins (e.g., profit and overhead charged by suppliers, manufacturer, distributors, and retailers); this will likely occur naturally as the U.S. PV industry grows and matures.
  • Streamlining of installation practices through improved workforce development and training and developing standardized PV hardware
  • Expansion of access to a range of innovative financing approaches and business models
  • Development of best practices for permitting interconnection and PV installation such as subdivision regulations, new construction guidelines, and design requirements.

FOM cost reduction represents optimized O&M strategies, reduced component replacement costs, and lower frequency of component replacement.