Geothermal

2023 ATB data for geothermal are shown above. The base year hydrothermal costs are derived from data from actual geothermal power plants. Near-term enhanced geothermal system (EGS) costs are predictions for a package of technologies currently under development, and they have no calibration to actual project deployment, as at this time, no commercial EGS plant exists in the United States. The future cost projections use bottom-up models derived from the analysis and results of the GeoVision: Harnessing the Heat Beneath our Feet report (DOE, 2019). The GeoVision analysis is a collaborative multiyear effort with contributors from industry, academia, national laboratories, and federal agencies. The GeoVision report updated resource potential estimates as well as recently published and projected capital and operation and maintenance (O&M) costs through evaluation of recent industry trends. It also predicted advancements in areas such as drilling efficiency and materials and EGS stimulation success. Anticipated drilling and EGS improvements enable reduced development timelines, CAPEX, and financing rates (DOE, 2019); (Augustine et al., 2023); (Schulz and Livescu, 2023).

The 2021 U.S. Geothermal Power Production and District Heating Market Report published by the National Renewable Energy Laboratory (NREL) confirms many of the industry trends reported in GeoVision (Robins et al., 2021). For example, the base year hydrothermal LCOEs fall within the bounds of other publications and recent geothermal power purchase agreements. In addition, the market report confirms that although EGS is not yet economical, significant technical progress continues to be made on the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. With the addition of new EGS research and demonstration activities under the Bipartisan Infrastructure Law Enhanced Geothermal Systems (EGS) Pilot Demonstrations funding opportunity, as well as the Enhanced Geothermal Shot initiative launched in 2023, EGS technical progress toward economical operations is expected to accelerate. There has also been an increase in private sector investment in EGS development. These efforts have led to recent signings of power purchase agreements (PPAs) between EGS developers and public utilities for electricity from EGS-based power plants scheduled to begin power generation by 2026. The market report, along with inputs from industry partners and assumptions from modeling that supported the Enhanced Geothermal Shot, also inform recent updates to the plant capacities, expansions, and retirements that are included in the 2023 ATB. The terms for public geothermal power purchase agreements signed from November 2019 through September 2020 can be found in the table below (Robins et al., 2021).

Recent Public Geothermal Power Purchase Agreement Pricing

The three scenarios for technology innovation are:

• Conservative Technology Innovation Scenario (Conservative Scenario): Continuation of current industry trends in drilling (e.g., minor efficiency improvements with little to no increase in rate of penetration [ROP]) and EGS (e.g., limited increase in flow rate and stimulation success rate) result in minor CAPEX improvements by 2035.
• Moderate Technology Innovation Scenario (Moderate Scenario): Drilling advancements (e.g., doubled ROP and bit life and reduced number of casing intervals and associated drilling materials) detailed as part of the GeoVision report (DOE, 2019) and EGS stimulation successes from the EGS Collab project (Kneafsey et al., 2022) and industry demonstration projects (Norbeck et al., 2023) result in cost improvements that are fully achieved industry-wide by 2035.
• Advanced Technology Innovation Scenario (Advanced Scenario): substantial drilling and EGS advancements (e.g., significantly increased ROP, bit life, and EGS stimulation success, limited casing intervals, significantly reduced consumption of drilling materials, and reduced timelines) as modeled in the Technology Improvement scenario of the GeoVision report result in cost improvements that are achieved by 2035. Going by the updates made in the 2022 ATB, Advanced Scenario EGS power plants are assumed to be built with 100 MW of capacity to maximize project efficiency. In addition, permitting timelines reflect anticipated permit streamlining effects of a National Renewable Energy Coordination Office, as enacted through the Energy Act of 2020.  

Resource Categorization

Within the 2023 ATB, geothermal resources broadly consist of two main types: hydrothermal and EGS. Although emerging technologies like closed-loop and supercritical hot rock systems fall within the category of geothermal for electricity generation, they are not currently covered within the context of the ATB. Hydrothermal systems are naturally occurring zones of Earth-heated circulating fluid that can be exploited for electricity generation if certain minimum temperatures and flow rates are achieved for a given power plant technology. EGS exhibit naturally occurring zones of heat but lack sufficient fluid flow and require engineering to enhance permeability. These two resource types are subdivided based on site-specific resource characteristics and compatible power plant technology into two types of energy conversion processes used to generate geothermal electricity:

• Binary plants use a heat exchanger and secondary working fluid with a boiling point below that of water to transfer geothermal energy through an organic Rankine cycle. This technology generally applies to lower-temperature systems (<200°C) due to the current maximum operating temperature of pumping technology. These systems have higher CAPEX than flash systems because of the increased number of components, their lower-temperature operation, and a general requirement that a number of wells be drilled for a given power output.
• Flash plants generate steam through a pressure change of the thermal fluid that directly drives a turbine. This technology generally applies to higher-temperature systems. Because of the reduced number of components and higher-temperature operation, these systems generally produce more power per well, thus requiring fewer wells and reducing drilling costs. These systems generally have lower CAPEX than binary systems.

Hybrid plants, or a combination of binary and flash systems are employed in some locations but are not modeled here.

The ATB defines flash resources as those with temperatures at or above 200°C and binary resources as those with temperatures from 110 to <200°C. EGS resources are further subdivided into near-hydrothermal field EGS (NF-EGS) and deep EGS. The resulting geothermal resource supply curves consist of six categories: hydrothermal flash, hydrothermal binary, NF-EGS flash, NF-EGS binary, deep-EGS flash, and deep-EGS binary. For illustration in the ATB, six representative geothermal plants are shown with design parameters based on each resource category. Based on the technology definition for the 2023 ATB, the hydrothermal technologies are considered as mature technologies, while the NF-EGS and deep-EGS technologies are considered as nascent because there are no commercial EGS plants in operation.

Examples using these plant types in each of the three resource categories (hydrothermal, NF-EGS, and deep EGS) are shown in the ATB visualization.

Geothermal Potential Resource and Cost Characteristics

The hydrothermal geothermal resource potential is concentrated in the Western United States. Currently, the potential hydrothermal capacity is 35,599 MW, comprising 5,566 MW of identified and 30,033 MW of undiscovered resources. The potential capacity for the identified resources is based on available reservoir thermal energy information from studies conducted at the sites (USGS, 2008); (Williams et al., 2009), subsequent research on plant additions and retirements conducted for the 2021 market report (Robins et al., 2021), and input from plant operators. Therefore, the identified resource capacity is the capacity available for future deployment and not the mean capacity estimated in the initial 2008 USGS assessment. The undiscovered hydrothermal resource estimate is based on a series of geographic information system statistical models of the spatial correlation of geological factors that facilitate the formation of geothermal systems (Williams et al., 2009). 

Specifically, the USGS resource potential estimates for hydrothermal are used with the following modifications:

• Installed capacity of about 3.7 GW is excluded from the resource potential used in the 2019 GeoVision study (DOE, 2019); (Robins et al., 2021).
• 90 MW of net capacity have been brought online since 2016 and are not included in the 2023 ATB resource potential (Robins et al., 2021).
• Resources on federally protected and U.S. Department of Defense lands, where development is highly restricted, are excluded from the resource potential, as are resources on lands where significant barriers that prevent or inhibit development of geothermal projects were identified by Augustine, Ho, and Blair (Augustine et al., 2019).

The EGS resource potential is concentrated in the Western United States, but technology innovations as described in the Advanced Scenario and in the recent Enhanced Geothermal Shot initiative is anticipated to increase potential beyond the Western United States (Augustine et al., 2023). The total recoverable potential is greater than 100,000 MW: 1,494 MW of NF-EGS and the remainder from deep EGS. The NF-EGS resource potential is based on data from the USGS for EGS potential on the periphery of select identified hydrothermal sites (Augustine et al., 2019). The deep-EGS resource potential ((Roberts, 2018); (Augustine, 2016)) is based on Southern Methodist University Geothermal Lab temperature-at-depth maps and the methodology is from (MIT, 2006). The deep-EGS favorability map above and many other geothermal resource maps can be created with NREL's Renewable Energy Atlas (formerly the Geothermal Prospector tool).

Scenario Descriptions

Summary of Technology Innovation by Scenario (2035)

Scenario Assumptions

For the 2023 ATB, several assumptions are updated for the Conservative, Moderate and Advanced scenarios based on consultations with geothermal industry experts and stakeholders, and an updated literature search (Snyder et al., 2017); (Fukui et al., 2017); (Latimer and Meier, 2017); (Kneafsey et al., 2022);  (Norbeck et al., 2023). Overall, the plant contingency factor for all technologies is reduced from 15% to 10% to ensure consistency with other thermal energy systems (Theis, 2021). This plant-level factor does not include the contingency for the drilling and completions that is already accounted for in the well cost simplified model (Lowry et al., 2017b). The Moderate and Advanced Hydrothermal assumptions are updated over the GeoVision assumptions using actual well productivity and injectivity data from hydrothermal plants in California and Nevada (Snyder et al., 2017). The median injectivity index (14 kg/s-bar or 7,645 lb/hr-psi) from the (Snyder et al., 2017) data is used in the Moderate Scenario (up from 2,500 lb/hr-psi), and  the P75 value (40 kg/s-bar or 21,840 lb/hr-psi) is used in the Advanced Scenario. A 3:2.5 ratio of injectivity to productivity is used to estimate the productivity index for each scenario. This ratio accounts for the effect of thermal stimulation that occurs due to the injection of a relatively cold fluid into a hot reservoir.

Updated Geothermal Electricity Technology Evaluation Model (GETEM) Input Assumptions for Hydrothermal

Several EGS assumptions have also been updated in the GETEM model. These include:

• Successful full-size exploration wells: Decreased from 9 to 5 and 3 for the Conservative and Moderate scenarios respectively. Reduced from 3 to 2 in the Advanced Scenario. These changes are based on consultations with industry stakeholders.
• Exploration drilling success rate: Up from 52.6% to 76% for the NF-EGS Conservative and Moderate scenarios to match current industry trends (Hackett et al., 2020); (Winkler et al., 2021).
• Stimulation success rate: Up from 75% to 81% for the Moderate Scenario due to EGS Collab and FORGE success.
• Flow rate per production well: Updated to 60 kg/s (flash) and 80 kg/s (binary) for the Moderate Scenario based discussions with industry stakeholders. This value was previously 40kg/s.
• Productivity/Injectivity index: Updated injectivity indices from the GeoVision assumptions of 250 lb/hr-psi and 2,500 lb/hr-psi to 1,650 lb/hr-psi and 7,645 lb/hr-psi for the Moderate and Advanced scenarios, respectively. These updated values correspond to the P25 and median values of the (Snyder et al., 2017) data. The 3:2.5 ratio is used to calculate the updated productivity indices.

Updated GETEM Input Assumptions for EGS

Separate learning rates for hydrothermal and EGS technologies were established through an NREL literature review. This literature review examined the application of one-factor, two-factor, and multifactor learning curves in geothermal, unconventional oil and gas drilling, and other renewable energy technologies. A one-factor learning curve, with a learning rate representing industry-wide learning, is used in the ATB cost projections (Fukui et al., 2017). A 13% learning rate is used to create the Moderate hydrothermal cost curve between 2021 and 2035 based on historical learning rates in the unconventional oil and gas industry (Fukui et al., 2017). EGS is likely to have a higher learning rate than hydrothermal systems because it is a novel technology and will likely be implemented in less predictable and more heterogeneous lithology. An 18% learning rate is used in the Moderate EGS cost curves, reflecting the low-end approximation for learning rates found in (Latimer and Meier, 2017). The Advanced EGS and hydrothermal cases use the high-end estimation of learning rates of 30% found in (Latimer and Meier, 2017). This learning rate also falls within the range predicted in a recent report by (Schulz and Livescu, 2023) on the effect of the full extent of oil and gas learning spillover into geothermal. After 2035, the costs in all cases are assumed to decrease annually by 0.5%.

Learning Rate Assumptions by Scenario

The learning curve equation used to determine future costs (between 2022 and 2035) is the single-factor learning equation as described by (Fukui et al., 2017): $$C(x)=C(x_{0})(x/x_{0})^{L}$$ where C(x) is the cost at cumulative capacity x, C(x₀) is the cost at the first deployment capacity x₀ and L is the learning parameter. The learning rate (LR) and L are defined by the following relation: \(LR=1-2^{-L}\). To convert from capacity to time, the relative capacity, x/x₀ at the full deployment year (2035) is first determined using the known 2035 cost and the LR for the specific scenario. Then a simple linear interpolation is applied between 2022 (when x/x₀ = 1) and 2035 to determine the x/x₀ at intermediate time steps. These values are then applied in the learning curve equation to calculate C(x) for the corresponding years.

Note: The learning curve equation is applied between 2022 and 2035 and not between 2021 (the base year) and 2035. This is because 2022 costs are predetermined by applying the 2022 capital cost multiplier to 2021 costs to account for significant inflation and interest rate hikes that ensued in 2022.

Performance Assumptions by Scenario

Representative Technology

Hydrothermal

Hydrothermal geothermal technologies encompass technologies for exploring for the resource, drilling to access the resource, and building power plants to convert geothermal energy to electricity. Technology costs depend heavily on the hydrothermal resource temperature and well productivity and depth, so much so that project costs are site-specific and a "typical" cost applied to any given site would be inaccurate. The 2023 ATB uses scenarios developed by the DOE Geothermal Technologies Office (Mines, 2013) for representative binary and flash hydrothermal power plant technologies.

The first scenario assumes a 175°C resource at a depth of 1.5 km with wells producing an average of 110 kg/s of geothermal brine supplied to a 30-MW_e binary (organic Rankine cycle) power plant. The second scenario assumes a 225°C resource at a depth of 2.5 km with wells producing 80 kg/s of geothermal brine supplied to a 40-MW_e dual-flash plant. These are mid-grade or "typical" temperatures and depths for binary and flash hydrothermal projects.

The 2023 ATB representative technologies fall in the middle to low end of the hydrothermal resources cost estimates typically deployed in Regional Energy Deployment System (ReEDS) model runs.

Enhanced Geothermal Systems (EGS)

As with costs for projects that use hydrothermal resources, EGS resources are similarly site-specific and project costs depend so heavily on the resource temperature, well productivity, and depth. The 2023 ATB uses scenarios developed by the DOE Geothermal Technologies Office (Mines, 2013) for representative binary and flash deep-EGS power plants assuming current (immature) EGS technology performance metrics. NF-EGS representative scenarios mimic the temperature, depth, and plant size of the hydrothermal representative plants, but they include EGS techno-economic assumptions such as flow rate, success rate, and well productivity/injectivity. In the context of the GETEM model, NF-EGS systems are assumed to be brownfield projects with lower exploration cost requirements than greenfield deep-EGS developments.

The first NF-EGS scenario assumes a 175°C resource at a depth of 1.5 km with wells producing an average of 40 kg/s of geothermal brine supplied to a 30-MW_e binary (organic Rankine cycle) power plant. The second NF-EGS scenario assumes a 225°C resource at a depth of 2.5 km with wells producing 40 kg/s of geothermal brine supplied to a 40-MW_e dual-flash plant. These NF-EGS representative scenarios fall close to the average resource cost estimates seen in the NF-EGS supply curves. 

The first deep-EGS scenario assumes a 175°C resource at a depth of 3 km with wells producing an average of 40 kg/s of geothermal brine supplied to a 25-MW_e binary (organic Rankine cycle) power plant. The second deep-EGS scenario assumes a 250°C resource at a depth of 3.5 km with wells producing 40 kg/s of geothermal brine supplied to a 30-MW_e dual-flash plant. These temperatures and depths are at the low-cost end of the EGS supply curve and would be some of the first developed.

Methodology

This section describes the methodology to develop assumptions for CAPEX, O&M, and capacity factor. For standardized assumptions, see labor cost, regional cost variation, materials cost index, scale of industry, policies and regulations, and inflation.

The site-specific nature of geothermal plant cost, the relative maturity of hydrothermal plant technology, and the very early-stage development of EGS technologies make cost projections difficult. The GeoVision scenarios are based on bottom-up analysis of potential cost and performance improvements. The inputs for these scenarios were developed by the national laboratories as part of the GeoVision effort and were reviewed by industry experts.

The cost and performance estimates are calculated using the Geothermal Electricity Technology Evaluation Model (GETEM), a bottom-up cost analysis tool that accounts for each phase of development of a geothermal plant as follows:

• Cost and performance data for hydrothermal generation plants are estimated for each potential site using GETEM. Model results are based on resource attributes (e.g., estimated reservoir temperature, depth, and potential) of each site.
• Site attribute values are from (USGS, 2008) for identified resource potential and from capacity-weighted averages of site attribute values of nearby identified resources for undiscovered resource potential.
• GETEM is used to estimate CAPEX, O&M, and parasitic plant losses that affect net energy production for the three technology innovation scenarios.

Capital Expenditures (CAPEX)

Definition: For the ATB—and based on (EIA, 2016) and GETEM component cost calculations—the geothermal plant envelope is defined to include:

• Geothermal generation plant
  • Exploration, confirmation drilling, well-field development, reservoir stimulation (EGS), plant equipment, and plant construction
  • Power plant equipment, well-field equipment, and components for wells (including dry/noncommercial wells)
• Balance of system
  • Installation and electrical infrastructure, such as transformers, switchgear, and electrical system connecting turbines to each other and to the control center
  • 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
  • An updated contingency factor of 10% is included in the overall capital cost calculations (Theis, 2021). This contingency factor is not applied to drilling costs because drilling success rates and contingencies are already incorporated into the GETEM model
  • Electrical interconnection and on-site electrical equipment (e.g., switchyard), a nominal-distance spur line (<1 mile), and necessary upgrades at a transmission substation; distance-based spur line cost (grid connection costs, or GCC) not included in the ATB
  • Interest during construction estimated based on 5-year durations for hydrothermal and EGS for the Advanced Scenario, 7-year durations for hydrothermal and EGS for the Moderate Scenario, and 8-year and 10-year durations for hydrothermal and EGS respectively for the Conservative Scenario, accumulated at different intervals for hydrothermal and EGS based on schedules as outlined by the GeoVision analysis (found at www.energy.gov/eere/geothermal/geovision) (ConFinFactor). 

In the 2023 ATB, CAPEX is shown for six representative plants. If all sites are used, the CAPEX estimates for all hydrothermal and NF-EGS potential result in a CAPEX range that is much broader than that shown in the ATB. It is unlikely that the resource potential from all identified sites will be developed because of the high costs for some sites. Effects of regional cost variation and distance-based spur line costs are not estimated.

CAPEX in the ATB does not represent regional cost variants (CapRegMult) associated with labor rates, material costs, or other factors (CapRegMult = 1).

CAPEX in the ATB does not include geographically determined spur line (GCC) costs from plant to transmission grid (GCC = 0).

Base Year: GETEM inputs are derived from the Business-as-Usual scenario from the GeoVision report ((DOE, 2019); (Augustine et al., 2019)). Costs are for new or greenfield hydrothermal projects—not for redrilling or additional development/capacity additions at an existing site. The exception is for NF-EGS, where the brownfield hydrothermal assumptions are used in GETEM. The following chart shows historical CAPEX and LCOE for geothermal, including data from the International Renewable Energy Agency (IRENA, 2022).

Future Years: Projection of future geothermal plant CAPEX for three scenarios are derived from modeled costs in the GeoVision report (DOE, 2019) and on updated learning rates following (Fukui et al., 2017) (Latimer and Meier, 2017):

• Conservative Scenario: Continuation of current industry trends in drilling (e.g., minor efficiency improvements with little to no increase in ROP) and EGS (e.g., subeconomic flow rates and limited stimulation reproducibility) result in a minimum learning rate and minor CAPEX improvements as implemented in the U.S. Energy Information Administration's Annual Energy Outlook 2015 (EIA, 2015): 5% CAPEX reduction by 2030. This corresponds to a 0.5% annual improvement in CAPEX, which is assumed to continue through 2050.
• Moderate Scenario: Drilling advancements, specifically the Intermediate 1 Drilling Curve (e.g., doubled ROP and bit life and reduced number of casing intervals, associated drilling materials, and timelines) detailed as part of the GeoVision report, result in cost improvements that are achieved by 2035. Discussion with industry experts lead to higher flow rates for EGS systems (80 kg/s for binary systems, 60 kg/s for flash systems) and decreased required exploration wells (three successful exploration wells). Stimulation success rates for EGS increase to 81% due to advances in zonal isolation stimulation (Kneafsey et al., 2022) (Norbeck et al., 2023). Well productivity indexes are increased to match values in (Snyder et al., 2017). Costs decrease according to the learning curves described above from present values to the 2035 projected values followed by a 0.5% annual reduction in CAPEX, due to a minimum learning rate, through 2050 .
• Advanced Scenario: Significant drilling and EGS advancements based modeling in the Technology Improvement scenario of the GeoVision report result in cost improvements that are achieved by 2035. Costs decrease according to the learning curves described above from present values to the 2035 projected values and are followed by a 0.5% annual reduction in CAPEX, due to a minimum learning rate, through 2050. Drilling improvements, as part of the GeoVision Ideal Drilling Curve, include significantly increased ROP, bit life, and EGS stimulation success, limited casing intervals, and significantly reduced consumption of drilling materials. In addition, the deployment of 100-MW power plants decreases capital costs and fixed O&M. Well productivity indexes reflect high-end values found in (Snyder et al., 2017). Discussion with industry experts lead to advances in EGS exploration success rate and required exploration well assumptions: 90% and two successful exploration wells respectively. Finally, permitting timelines are reduced to reflect anticipated permit streamlining effects of a National Renewable Energy Coordination Office, as enacted through the Energy Act of 2020.

Use the following table to view the components of CAPEX.

Components of CAPEX

Operation and Maintenance (O&M) Costs

Definition: Fixed O&M (FOM) costs represent average annual fixed expenditures (and depend on rated capacity) required to operate and maintain a hydrothermal plant over its lifetime of 30 years (plant and reservoir), including:

• Insurance, taxes, land lease payments, and other fixed costs
• Present value and annualized large component overhaul or replacement costs over technical life (e.g., downhole pumps)
• Scheduled and unscheduled maintenance of geothermal plant components and well-field components over the technical lifetime of the plant and reservoir.

Base Year: GETEM is used to estimate FOM for each of the six representative plants. FOM for NF-EGS and EGS are equivalent. For the 2022 ATB, base year FOM costs were decreased by 23%. This change is carried over to the 2023 ATB and is supported by proprietary geothermal industry FOM data.

Future Years: Future FOM cost reductions are based on results from the GeoVision Technology Improvement scenario (DOE, 2019) and are described in detail by Augustine, Ho, and Blair (Augustine et al., 2019).

Use the following table to view the components of operating expenditures.

Components of Operating Expenditures

Capacity Factor

Definition: Geothermal plant capacity factor is influenced by diurnal and seasonal air temperature variation (for air-cooled plants), technology (e.g., binary or flash), downtime, and internal plant energy losses.

Estimates of capacity factor for geothermal plants in the ATB represent typical operation.

Base Year: The capacity factor estimates are developed using GETEM at typical design air temperature and are based on design plant capacity net losses. An additional reduction is applied to approximate potential variability that is due to seasonal temperature effects.

Some geothermal plants have experienced year-on-year reductions in energy production, but this is not consistent across all plants. No approximation of long-term degradation of energy output is assumed.

Future Years: Capacity factors remain unchanged from the base year through 2050. Technology improvements focus on CAPEX costs. The dispatch characteristics of these systems can be 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 geothermal plants to manage grid services. However, a constant dispatch profile is modeled in the ATB and no change over time is assumed.

References

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