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Renewable Fuels Module - NEMS Documentation

September 28, 2022


Purpose of this report
This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to producing the Annual Energy Outlook 2022 (AEO2022) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of off-line analyses used in place of RFM modeling components are also described.

This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets EIA’s legal requirement to provide adequate documentation in support of our models [Public Law 93-275, Federal Energy Administration Act of 1974, Section 57(b) (1)]. Third, this documentation facilitates continuity in our model development by providing information sufficient to perform model enhancements and data updates as part of our ongoing mission to provide analytical and forecasting information systems.

Renewable Fuels Module summary
The RFM consists of six submodules that represent major renewable electricity resources: biomass, landfill gas (LFG), solar (thermal and photovoltaic), wind, geothermal, and conventional hydroelectricity energy. The RFM also interacts with the REStore model to estimate the impact of energy storage on the dispatch of generation in each of the modeled electricity regions. The details of the REStore model are provided as an appendix to the Electricity Market Module (EMM) model documentation.

The RFM defines the technology, performance, and renewable resource supply for renewable electricity technologies in the NEMS, which is used by the EMM, along with the renewable cost assumptions that are provided in the EMM model documentation, in projecting grid-connected central-station electricity capacity planning and dispatch decisions. Projected characteristics include:

  • Available generating capacity
  • Location
  • Unit size
  • Capital cost
  • Fixed operating cost
  • Variable operating cost
  • Capacity factor
  • Heat rate
  • Construction lead time
  • Fuel price

Because of the extensive interaction between the RFM, REStore, and EMM, these three modules must be run together.

Renewable electricity technology cost and performance characteristics that are common to all electricity-generating technologies are input directly to the EMM via the input file ECPDAT. Unique characteristics such as renewable resource values for regional, seasonal, and hourly time segments of intermittent renewables are supplied in specific files and subroutines to specific renewable electricity technologies.

Other renewables modeled elsewhere in NEMS include:

  • Biomass in the industrial sector
  • Biofuels in the Liquid Fuels Market Module (LFMM)
  • Wood and solar hot water heating in the residential sector
  • Geothermal heat pumps and distributed (grid-connected) solar photovoltaics in the residential and commercial sectors

In addition, several areas, primarily nonelectric and off-grid electric applications, are not represented in NEMS. They include direct applications of geothermal heat, several types of solar thermal use, and off-grid photovoltaics. For the most part, the expected contributions from these sources are confined to niche markets; however, as these markets develop in importance, they will be considered for representation in NEMS.

The number and purpose of the associated technology and cost characteristics vary from one RFM submodule to another, depending on the modeling context. For example, renewable resources such as solar, wind, and geothermal energy are not fuels; rather, they are inputs to electricity or heat conversion processes. As a result, the Solar Submodule, Wind Submodule, and Geothermal Submodule do not provide fuel product prices.

Our Office of Long-Term Energy Modeling Electricity, Coal, and Renewables Modeling Team determines initial cost and performance values for renewable electricity technologies based on the examination of available information. For AEO2020, we re-evaluated and updated the cost and performance characteristics for all generating technologies, including non-renewables. The cost and performance characteristics include:

  • Capital costs (excluding the construction financing and the process and project contingency components that are provided in the EMM)
  • Fixed and variable operation and maintenance (O&M) costs
  • Capacity factors
  • Construction lead times

All cost values are converted to 1987 dollars.

The following sections provide summaries of the six RFM submodules that we use to produce the current projections:

  • Landfill Gas Submodule (LFG)
  • Wind Energy Submodule (WES)
  • Solar Energy Submodule (SOLAR)
  • Biomass Submodule
  • Geothermal Energy Submodule (GES)
  • Conventional Hydroelectricity Submodule (CHS)

Each sections concludes with information on the RFM archival package and EIA point of contact.

Landfill Gas Submodule (LFG)
The Landfill Gas Submodule provides annual projections of energy produced from estimates of U.S. landfill gas capacity. The submodule calculates the quantity of LFG produced, derived from an econometric equation that uses gross domestic product (GDP) and U.S. population as the principal drivers. We estimate the LFG capacity based on reported waste and landfill gas production data and judgment about future trends in recycling. The submodule uses LFG supply curves to reflect competition between new LFG-to-electricity capacity and other technologies in each projection period and in each EMM region.

Wind Energy Submodule (WES)
The Wind Energy Submodule (WES) projects the availability of undeveloped wind resources, expressed as megawatts (MW) of capacity in each region, which is passed to the EMM, which models for the building and dispatching of wind turbines that are competing with other electricity-generating technologies. The wind turbine data are expressed in the form of energy supply curves that provide the estimated maximum amount of turbine generating capacity that could be installed, given the available land area, average wind speed, and capacity factor. These variables are passed to the EMM in the form of nine time segments that are matched to respective electricity load curves within the EMM.

Solar Energy Submodule (SES)
Solar technologies in RFM include solar thermal (also referred to as concentrating solar power, CSP) and photovoltaic. Starting in AEO2021, we include a combined solar PV and battery storage hybrid system as a generating technology option for capacity expansion. All three technologies are grid-connected and provided by electric utilities, small power producers, or independent power producers. Performance characteristics unique to solar technologies (such as season and region-dependent capacity factors) are passed to the EMM via the SES.

Biomass Energy Submodule (BES)
The Biomass Submodule provides biomass resource and performance characteristics for a biomass-burning, electricity-generating technology to the EMM. The submodule uses a regional biomass supply schedule that we use to determine the biomass fuel price; fuel prices are added to variable operating costs because renewable fuels have no fuel costs in the NEMS structure. The biomass supply schedule is based on the accessibility of wood resources by the consuming sectors from existing wood and wood residues, crop residues, and energy crops. The LFMM also accesses the biomass supply curve to determine availability of feedstocks for production of cellulosic ethanol, biomass pyrolysis oils, and biomass-to-liquids. Projected feedstocks for production of sugar- or starch-based ethanol (primarily from corn, or maize, in the United States) are determined within the LFMM. The Industrial Demand Module (IDM) model captive capacity in the wood products and paper industries as cogeneration.

Geothermal Energy Submodule (GES)
The Geothermal Energy Submodule (GES) models current and future regional supply, capital cost, and operation and maintenance costs of electric-generating facilities. The GES uses hydrothermal resources (hot water and steam) and so-called near-field enhanced geothermal systems (EGS) sites, which are areas around the hydrothermal sites with high temperatures but less fluid as a basis for its model. The data are assembled from 125 known hydrothermal sites and the 125 corresponding near-field EGS areas, each represented by information that reflects the specific resource conditions of that location. The GES generates a three-part geothermal resource supply curve for geothermal capacity for each region in each forecast year for competition with fossil-fueled and other generating technologies.

Conventional Hydroelectricity Submodule (CHS)
The Conventional Hydroelectricity Submodule (CHS) models the supply (MW), capital cost, and operation and maintenance costs of conventional hydroelectric power available from adding new hydro generating capacity in increments of 1 MW or greater to:

  • New sites without dams
  • Sites with existing dams but without hydroelectricity
  • Existing hydroelectricity sites that can accommodate additional capacity

The CHS uses the Idaho Hydropower Resource Economics Database (IHRED). The CHS does not account for:

  • Pumped storage capacity
  • Increments of capacity less than 1 MW available from refurbishing and upgrading existing hydro capacity
  • Capacity available from new in-stream, offshore, or ocean technologies

Within each NEMS region, for each NEMS cycle, the CHS first identifies additional hydro capacity available at or less than an avoided cost specified by the EMM. It then segments the available capacity into three cost categories: lowest cost, midrange cost, and highest cost. The CHS then submits the megawatts of available capacity, expressed as average capital cost and operation and maintenance costs (each weighted by nameplate capacity) and capacity factors to the EMM for each of the three cost categories. After projecting capacity change decisions, the EMM informs the CHS of required decrements to potential available for selection in the next NEMS cycle.

Capacity credit for intermittent generation
The intermittent and battery storage generators can contribute some fraction of their rated capacity to the reserve margin because of the significant probability that at least some intermittent and battery storage generators will be available during peak-demand periods and the significant probability that some portion of operator-dispatched capacity will not be available during that time,. This fraction, referred to as the capacity credit, is a function of the correlation between the temporal generation pattern of the resource and the peak-load periods, as well as the fraction of intermittent generation compared with total regional output.

The intermittent capacity credit is determined in NEMS as a function of the estimated average contribution that all intermittent units will provide to meet an assumed system reliability goal of 99.999% availability. This contribution is, in turn, largely determined by the:

  • Average, peak-load period capacity factor for the intermittent capacity
  • Standard deviation around that average
  • Degree to which the output at each individual site in a region is correlated with the output at other sites
  • Reliability characteristics of the operator-dispatched (conventional) capacity in the region

The battery storage capacity credit is determined as a function of the available energy stored in batteries during the hours of peak net load using the load duration curve (LDC) calculation method.

Representation of depreciation for renewables-fueled generating technologies
Biomass, geothermal, solar (photovoltaic and thermal), and wind (onshore and offshore) are assigned five-year tax lives and five-year double declining balance capital depreciation in NEMS2, accelerated cost recovery. Landfill gas and hydroelectric technologies are assumed to have 20-year tax lives during which the capital is depreciated, which is the same for most central-station, electricity-generating technologies except nuclear technologies, which are assigned a 15-year tax life.

Archival Media
The RFM is archived as part of the NEMS production runs.

Model Contact
Manussawee Sukunta
Electricity, Coal, and Renewables Modeling Team
Office of Long-Term Energy Modeling
U.S. Energy Information Administration, EI-34
1000 Independence Ave. SW
Washington, DC 20585
Phone: (202) 586-0279
Email: manussawee.sukunta@eia.gov

Report organization
Subsequent chapters of this report provide detailed documentation of capacity credit algorithm for intermittent generation and each of the RFM's six working submodules. Each chapter contains:

  • Model Purpose—a summary of the submodule's objectives, detailing input and output quantities, and the relationship of the submodule to other NEMS modules
  • Model Rationale—a discussion of the submodule's design rationale, including insights into assumptions used in the model development process, and alternative modeling methodologies considered during the submodule development phase
  • Model Structure—an outline of the model structure, using text and graphics to illustrate the major model data flows and key computations

This report also contains appendixes—supporting documentation for input data and parameter files currently residing on our computer network. Appendix A in each RFM submodule chapter lists and defines the input data used to generate parameters and endogenous projections. Appendix B contains a mathematical description of the computation algorithms, including model equations and variable transformations. Appendix C is a bibliography of reference materials used in the model development process. Appendix D is a model abstract. Appendix E discusses data quality and estimation methods.

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