• Energy Research

AbstractFacing a cost for emitting carbon dioxide, US entities that own coal-fired power plants have a number of options to pursue as alternatives to retiring the plant and investing in a new one with lower carbon emissions. These include: (1) continuing to operate business as usual and obtaining emission allowances as needed, (2) switching to or cofiring low carbon fuels, (3) retrofitting with carbon capture and sequestration (CCS), (4) repowering with an advanced coal technology incorporating CCS, and (5) refurbishing to improve plant efficiency in combination with any of the previous options. Markets for refurbishing, retrofitting, and repowering were assessed using data bases of existing coal fired power plants along with the Energy Information Administration’s (EIA) National Energy Modeling System (NEMS) code, which was modified to undertake an integrated analysis of how retrofit and repowering options would compete with other options for managing the fleet of coal fired power plants. Sensitivities with respect to key uncertainties are presented, including carbon values, natural gas prices, CCS incentives, and system-wide cost effectiveness of refurbishing in conjunction with retrofitting or repowering.The indicated market for coal fired power plants that could be retrofitted with near commercial CCS technology under carbon cost scenarios ranging from 45–60$/MTCO2e (metric ton CO2 equivalent) is on the order of 100 GW. A similar market is apparent for repowering, but with technologies that are as yet not commercialized. Below 30$/MTCO2e, CCS technologies would not deploy without incentives. While refurbishing can extend the market for either retrofitting or repowering, its impact will depend on the extent to which efficiency as well as other cost related factors can be collectively upgraded.

High penetration of plug-in hybrid electric vehicles (PHEVs) in the next 5-10 years is plausible due to the benefits for both environments and end users. With the assumption of a high PHEV penetration, national energy modeling system (NEMS) software package is exploited to predict the growths of power generation plants. As an adjustable knob for the deregulated electricity market, the charging strategy of PHEVs is comparatively studied to gain a comprehensive picture of its impacts. Four typical daily charging strategies are investigated, which are: (1) uniform charging; (2) home-based charging; (3) off-peak charging; (4) vehicle-to-grid (V2G) charging. Electric capacity expansions by fuel types and preferred PHEV load profiles are characterized.

Many forecasts of the energy use, production, and consumption by industry sectors have been completed in past reports. The forecasts used in this book and various chapters are primarily based on the U.S. Department of Energy Annual Energy Outlook 1995 (AEO95), Annual Energy Outlook 1996 (AEO98), and International Energy Annual 1996 (IEA96) reports and are based on the National Energy Modeling System (NEMS) that is used by the Energy Information Administration as a tool for energy policy analysis that builds upon earlier modeling systems used to forecast energy prices, supply, demand, and imports over the midterm period that is considered to be about 15 to 20 years.

LBNL-59076 E RNEST O RLANDO L AWRENCE B ERKELEY N ATIONAL L ABORATORY Modeling Interregional Transmission Congestion in the National Energy Modeling System Etan Gumerman, Peter Chan, Bernard Lesieutre, Chris Marnay, and Juan Wang Environmental Energy Technologies Division May 2006 http://eetd.lbl.gov/ea/EMS/EMS_pubs.html This work described in this paper was funded by the Assistant Secretary of Energy for Energy Efficiency and Renewable Energy, Planning, Analysis and Evaluation section of Planning, Budget, and Analysis in the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

This report explores the different options for spatial resolution of an energy market model--and the advantages and disadvantages of models with fine spatial resolution. It examines different options for capturing spatial variations, considers the tradeoffs between them, and presents a few examples from one particular model that has been run at different levels of spatial resolution.

Improving the energy efficiency of industry is essential for maintaining the viability of domestic manufacturing, especially in a world economy where production is shifting to low-cost, less regulated developing countries. Numerous studies have shown the potential for significant cost-effective energy-savings in U.S. industries, but the realization of this potential is hindered by regulatory, information, workforce, and financial obstacles. This report evaluates seven federal policy options aimed at improving the energy efficiency of industry, grounded in an understanding of industrial decision-making and the barriers to efficiency improvements. Detailed analysis employs the Georgia Institute of Technology's version of the National Energy Modeling System and spreadsheet calculations, generating a series of benefit/cost metrics spanning private and public costs and energy bill savings, as well as air pollution benefits and the social cost of carbon. Two of the policies would address regulatory hurdles (Output-Based Emissions Standards and a federal Energy Portfolio Standard with Combined Heat and Power); three would help to fill information gaps and workforce training needs (the Superior Energy Performance program, Implementation Support Services, and a Small Firm Energy Management program); and two would tackle financial barriers (Tax Lien Financing and Energy-Efficient Industrial Motor Rebates). The social benefit-cost ratios of these policiesmore » appear to be highly favorable based on a range of plausible assumptions. Each of the seven policy options has an appropriate federal role, broad applicability across industries, utilizes readily available technologies, and all are administratively feasible.« less

How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.