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National Energy Modeling System (NEMS) Documentation Archive

Renewable Fuels Module - NEMS Documentation

December 14, 2018

Introduction

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 the production of the Annual Energy Outlook 2018 (AEO2018) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu 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 the legal requirement of the U.S. Energy Information Administration (EIA) to provide adequate documentation in support of its models (Public Law 93-275, Federal Energy Administration Act of 1974, Section 57(b) (1)). Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA's 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 purpose of the RFM is to define the technology, cost, performance, and renewable resource supply for renewable electricity technologies in the NEMS. The RFM estimations are provided to the Electricity Market Module (EMM) for use 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, and fuel price. Because of the extensive interaction between the RFM and EMM, these two 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, and 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. Consequently, the Solar, Wind, and Geothermal Submodules do not provide fuel product prices.

EIA’s Office of Electricity, Coal, Nuclear and Renewables Analysis determines initial cost and performance values for renewable electricity technologies based on examination of available information. Several sources for the cost and performance characterizations were examined for use in this version of the RFM. These sources provide values for capital costs (excluding the construction financing and process and project contingency components that are provided in the EMM), fixed and variable operation & maintenance (O&M) costs, capacity factors, and construction lead times. All cost values are converted to 1987 dollars.

Provided below are summaries of the six RFM submodules that are used for producing the current forecasts: the Landfill Gas Submodule (LFG), the Wind Energy Submodule (WES), the Solar Energy Submodule (SOLAR), the Biomass Submodule, the Geothermal Energy Submodule (GES), and the Conventional Hydroelectricity Submodule (CHS). Each chapter 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 and U.S. population as the principal forecast drivers. The landfill gas capacity is estimated based on reported waste and gas production data and judgment about future trends in recycling. The submodule uses LFG supply curves to reflect competition between new landfill gas-to-electricity capacity and other technologies in each projection period. The supply curves account for the amounts of high, low, and very low methane producing landfills located in each EMM Region.

Wind Energy Submodule (WES)
The Wind Energy Submodule (WES) projects the availability of wind resources. Projected undeveloped wind resource availability, expressed as megawatts (MW) of capacity in each region, is passed to the EMM, which models the building and dispatching of wind turbines in competition with other electricity generating technologies. The wind turbine data are expressed in the form of energy supply curves. The supply curves 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 electricity load curves within the EMM.

Solar Submodule (SOLAR)
Two solar technologies are represented in NEMS, a 150 MW single-axis tracking grid-connected central station photovoltaic (PV) unit without energy storage, and a 100 MW central receiver (power tower) solar thermal unit (also called concentrating solar power or CSP) also without energy storage. Both technologies are grid-connected and provided by electric utilities, small power producers, or independent power producers.

PV and solar thermal electric cost and performance characteristics are defined consistently with characteristics of fossil and other fuels reside in the ECPDAT input file. Performance characteristics unique to solar technologies (such as season and region-dependent capacity factors), however, are passed to the EMM via the solar submodule SOLAR.

Biomass Submodule
The Biomass Submodule provides biomass resource and technology cost and performance characteristics for a biomass burning electricity generating technology to the EMM. The technology currently modeled is a direct combustion system. The submodule uses a regional biomass supply schedule from which the biomass fuel price is determined; fuel prices are added to variable operating costs because there are no fuel costs in the structure of NEMS for renewable fuels. 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/starch based ethanol (primarily from corn/maize in the United States) are determined within the LFMM.

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 using 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. The data are assembled from 125 known hydrothermal sites and the 125 corresponding near-field EGS areas, each represented by information which 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 (a) new sites without dams, (b) sites with existing dams but without hydroelectricity, and (c) existing hydroelectricity sites able to 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, potential available from refurbishing and upgrading existing hydro capacity, or capacity available from new in-stream, off-shore, or ocean technologies. Within each NEMS region, for each NEMS cycle, the CHS first identifies additional hydro capacity available at or below an avoided cost specified by the EMM, then segments the available capacity into three cost categories: lowest cost, midrange cost, and highest cost. The CHS then submits the MW 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.

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