TODAY’S STUDY: THE U.S. NEW ENERGY POTENTIAL
Estimating Renewable Energy Economic Potential in the United States: Methodology and Initial Results
Brown, Beiter, et. al., July 2015 (National Renewable Energy Laboratory)
Executive Summary
Economic potential, one measure of renewable generation potential, is a metric that attempts to quantify the amount of economically viable renewable generation that is available at a location or within an area. Economic potential may be defined in several ways. For example, one definition might be expected revenues (based on local market prices) minus generation costs, considered over the expected lifetime of the generation asset. Another definition might be generation costs relative to a benchmark (e.g., a natural gas combined cycle plant) using assumptions of fuel prices, capital cost, and plant efficiency. Economic potential in this report is defined as the subset of the available resource technical potential where the cost required to generate the electricity (which determines the minimum revenue requirements for development of the resource) is below the revenue available in terms of displaced energy and displaced capacity…
This metric can be a useful screening factor for understanding the economic viability of renewable generation technologies at a detailed geospatial resolution as well as for assessing the impact of technology improvements, policies, and other actions that can affect market access. It differs from many common estimates of renewable energy potential in that it does not directly consider market dynamics, customer demand, or most policy drivers that may incentivize renewable energy generation. As such, economic potential cannot be used to predict what technologies will be deployed or when, and should not be expected to match estimates found in deployment scenarios.
Economic potential for a location can be understood in relation to other types of renewable energy potential (Figure ES-1). The largest potential, resource potential, is the amount of energy physically available. Technical potential takes into account real-world geographic constraints and system performance, but not economics. Economic potential is the subset of the technical potential that is available where the cost required to generate the energy (which determines the minimum revenue requirements for development of the resource) is below the revenues available. Lastly, market potential is the amount of energy we expect to be generated through market deployment of renewable technologies after considering the impact of current or future market factors, such as incentives and other policies, regulations, investor response, and the economic competition with other generation sources. The deployment associated with market potential can be estimated through capacity expansion and dispatch modeling—for example, by using NREL’s Regional Energy Deployment System (ReEDS).
Development of a consistent method to estimate economic potential across renewable technologies began following the completion of a 2012 NREL analysis that assessed the technical potential of renewable generation technologies (Lopez et al. 2012). That report applied unifying assumptions and methods to generate comparable estimates across technologies and estimated technical potential to be many times greater than current U.S. electricity demand. Concurrently, sufficient data sets on renewable resources, avoided costs, and other parameters had become available for synthesis. This report describes the resulting geospatial analysis method and its initial application to estimate the economic potential of several renewable resources available for electricity generation in the United States using data available as of 2014. The method employs high-resolution geospatial data, including more than 150,000 technologyspecific sites in the continental United States, to reflect the significant variation in local resources, costs, and revenue potential.
The initial method is applied to several renewable generation technologies under a variety of assumptions—including wind, utility photovoltaics (UPV), distributed photovoltaics (DPV), hydropower, geothermal (hydrothermal resources only), and biopower (dedicated combustion plants only, not including co-firing).
The preliminary results of this application are intended to demonstrate the utility of the method described, and serve as an initial estimate of the range of economic potential, primarily from a 2014 perspective, as well as an exploration of the factors that influence that potential. These estimates are anticipated to change as technology cost and performance, expected revenues for any given location, and other factors change. This work represents an initial effort to develop and apply a method for assessing economic potential; future work may deliver different results as the method is further developed and refined…
Initial Estimates and Observations
The above methodology is applied to several renewable generation technologies, under various assumptions—including land-based wind, utility photovoltaics (UPV), distributed photovoltaics (DPV), hydropower, geothermal (hydrothermal resource only), and biopower (dedicated combustion plants only, not including co-firing), primarily from a 2014 perspective.
For each of the above Primary Cases, an economic potential estimate range is established through varying assumptions of the applied capacity value of renewable generation. A major determinant of the capacity value is the extent to which additional generation capacity is required for the electricity system. In each of the Primary Cases, the low end of the estimated range of economic potential assumes that no additional capacity is required and reflects no credit for the capacity value of renewable generation in the avoided cost calculation. Conversely, the high end of each range assumes that additional capacity is needed on the system and reflects full credit for the capacity value of renewable generation in the avoided cost calculation.
Collectively, these Primary Cases rely on the following major assumptions:
• Construction Date: 2014 – Both the LCOE and LACE components of net value are calculated assuming a renewable generation project is constructed in 2014 (cost and value time streams that make up these components begin in 2014 and are discounted back to 2014). This approach enables a “current” view of economic potential based on existing 2014 marginal generation prices and existing forward projections of those prices. In contrast, as noted below, renewable technology costs for the Primary Cases are referenced to 2020. The combination of these two assumptions provides a blended view of economic potential illustrative of both the current environment and the near-term future. A sensitivity analysis explores a case with 2014 renewable costs and a 2014 construction date, as well as a case with 2020 renewable costs and a 2020 construction date.
• Renewable Technology Cost: 2020 mid-projection – The 2020 timeframe reflects additional technology improvement for most technologies assessed. The mid-case projected cost from NREL Annual Technology Baseline (ATB) (NREL 2015) is a central estimate.
• Renewable Technology Incentives: Permanent 10% ITC for UPV, DPV; Accelerated Depreciation (MACRS) – The inclusion of this level of ITC is intended to reflect a representation of existing federal law. As the current 30% ITC for solar technologies is scheduled to revert to the 10% level at the end of 2016, the “permanent” 10% level is used. The PTC is not included for wind as it required plant construction to begin by the end of 2013. Accelerated depreciation (MACRS) is assumed for all applicable technologies.
• Project Life: 20 years – Renewable generation plants are assumed to have a financial life of 20 years for the purposes of calculating LCOEs. LACE is estimated from marginal generation prices over this assumed 20-year asset life.
• Avoided Cost Method for Central Generation: MP – The MP method, based on a synthesis of locational marginal price data, is applied as a proxy for the revenue a centralized renewable project might receive in a given market. The capacity value component of avoided cost assumes a NGCT capital cost of $682/kW (consistent with AEO 2015).8 For DPV, local retail rates, together with full net metering where the customer is credited for any excess hourly generation at the applicable retail rate, are used as a basis for comparison to generation cost.
• Value of Avoided Health Costs: Not Included – Estimates of this type of external cost are not included in the primary cases as this impact of avoided cost was deemed secondary to consideration of the value of avoided CO2 emissions. Avoided heath costs are considered in a sensitivity case.
The following variables are differentially applied among the three Primary Cases:
• Value of Avoided CO2 Emissions (SCC): IWG (2013) Average SCC using a 3% discount rate – The value of avoided CO2 emissions is included in Primary Cases 2 and 3.
• Declining Value of Variable Generation: Included for Wind, UPV – Declining value is applied in the net value framework in Primary Case 3 that was designed to more broadly consider market effects. The application is made only to estimates for wind and UPV potential to reflect the possible impact of high levels of variable generation on project economics. This adjustment is not included for any DPV cases (no assumed change in value of solar with increasing DPV generation), given that the topic is an active area of research.
The sum of U.S. economic annual generation potential (excluding Alaska and Hawaii) for the six technologies assessed ranges from nearly 1,500 to 42,000 TWh in excess of 2013 generation for the Primary Cases. This range of aggregate potential represents from nearly three to nearly 80 times total U.S. renewable generation in 2013, or one-third to over ten times 2013 total U.S. generation from all sources, and is a small fraction of the aggregate annual technical generation potential of over 320,000 TWh for these technologies. These estimates simply sum the potentials of the individual technologies.
As such, they do not consider any potential competition among the technologies for available land or in economic terms. Further, they do not reflect any impact of the interaction of variable wind and PV generation upon the value of either technology. More specifically, the following are ranges of aggregate annual generation potential for each the Primary Cases (see Table ES-1):
• Primary Case 1 - LACE Only: 3,200 – 7,100 TWh. UPV contributes the bulk of the economic potential under this formulation.
• Primary Case 2 - LACE including Value of Avoided External Costs (related to CO2 emissions): 13,000 – 42,000 TWh. Under this formulation, UPV contributes the bulk of the economic potential, particularly at the high end of the range. Wind economic potential is also significant, representing at least the equivalent of total U.S. generation from all sources in 2013.
• Primary Case 3 - LACE including Value of Avoided External Costs and Declining Value of Variable Generation: 1,500 – 2,000 TWh. While the total economic potential in this formulation is much lower than in Primary Case 2, all of the technologies except biomass contribute significant potential. The potential shown represents 35 – 50% of total U.S. generation from all sources in 2013. Figure ES-3 illustrates this economic potential is additive to existing (2013) generation. Figure ES-4 displays the distribution of economic potential for this Primary Case by state.
Individual technologies make the following contributions to aggregate Primary Case 3 results (see Figure ES-5 for potential by Census division):
• Wind is estimated to provide 550 – 870 TWh of annual potential in these cases, concentrated in the central part of the country (West South Central Census division). Significant amounts of existing generation also appear in the Pacific region.
• UPV is estimated to provide 430 to nearly 610 TWh of annual potential, which appears in Nevada and Texas (currently small in existing generation), Arizona, and along the Eastern seaboard, including South Carolina.
• Distributed PV (residential and commercial) is estimated to provide 190 to nearly 290 TWh of annual potential, which appears in the southwest (Pacific and Mountain Census division) and along the Eastern seaboard, consistent with existing generation.
• Hydropower is estimated to provide 64 to 76 TWh of annual potential, which appears in every Census division.
• Geothermal (hydrothermal resources only) is estimated to provide 130 – 150 TWh of annual potential, which appears only in the West (Pacific and Mountain Census divisions), consistent with the location of existing generation.
Biopower, specifically dedicated combustion plants with co-firing not included, shows no economic potential under this formulation.
The following general findings and trends are observed based on the above initial estimates and in the sensitivity analysis reported in the full text:
• The specific formulation of the economic potential metric is extremely important. Across the three distinct formulations of the definition used in this analysis, economic potential estimates varied by almost 30-fold. As with all metrics, care should be applied in definition and supporting details to avoid misleading conclusions.
• Estimates of economic potential are highly sensitive to the specific assumptions used related to both renewable generation supply and avoided cost. The capacity value of renewable generation, external costs and associated discount rates, and the declining value of variable generation with increased penetration have a major impact on estimates. The reference year for project construction, renewable technology costs, and the method and assumptions associated with the avoided cost of generation are other variables that have a significant effect on estimates.
• Economic potential appears in all states for at least one of the renewable generation technologies assessed, depending on the specific formulation of economic potential considered.
• Technology costs are a significant driver for economic potential, as seen in the sensitivity cases in Primary Case 3. Annual generation potential, assuming full credit for the capacity value for renewable generation, is the following for the corresponding assumed costs (highest to lowest costs): 250 TWh (2010), 820 TWh (2014), 2,000 TWh (2020 mid), and 3,100 TWh (2030 mid). Cost reductions already realized for renewable generation technologies between 2010 and 2014, particularly for wind and solar PV technologies, increase aggregate potential under this formulation by more than 200%.
• Despite recent growth, total renewable energy deployed overall remains small compared to the total technical potential, except for the relatively developed technologies of hydropower, geothermal, and biopower. For wind and distributed solar photovoltaics (DPV), a small amount of technical potential has been developed, and economic potential is significantly more than what has been deployed to date. For utility-scale photovoltaics UPV, technical potential is extremely large (greater than all other renewables together), and deployed and economic potential are small in comparison.
The spreadsheet-based model used to conduct this analysis is expected to be updated and refined to reflect new data and analysis as they become available. In particular, the use of wholesale market price data as a basis for a geospatial representation of avoided costs is an emerging area of analysis. Several improvement opportunities for the methodology, underlying data, and scenario analysis have been identified, which can be developed and applied in future updates…
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