Investigating Technology Options for Climate Policies: Differentiated Roles in ADAGE.

• Author: Ross, Martin T.
• Position: Report

1. INTRODUCTION

   Given the lack of progress on establishing a national cap-and-trade system for greenhouse gas (GHG) emissions, interest in the United States has focused on alternative approaches for improving energy systems in the country, especially those related to electricity generation and transportation. The 2011 Economic Report of the President stated that a Clean Energy Standard (CES) for electricity would play an important role in reducing domestic emissions, and many states have already instituted CES or renewable energy standards (RES). Also, in August 2012, President Obama announced new regulations to achieve fuel economy in personal vehicles equal to 54.5 miles per gallon by 2025, with the support of automobile manufacturers. This paper examines how such existing and proposed regulations may interact with more comprehensive cap-and-trade climate policies in the future.

   What technology options are available both now and in the future will have significant implications for any adjustments to the U.S. energy infrastructure needed to meet future climate goals in this context. Some technological approaches may be more effective at lowering GHG levels than others, and what are the most cost-efficient options under one set of regulations may not work well under another set. As such, this paper examines interactions between a broad cap-and-trade system for GHG allowances and the more industry-specific features of CES and RES. The investigation is conducted under a range of assumptions about technology options and baseline emissions in the absence of any policies.

   To focus more explicitly on the role of electricity generation under a setting of RES or CES mandates, the RTI Applied Dynamic Analysis of the Global Economy (ADAGE) model, a computable general equilibrium (CGE) model, has been linked to a more detailed linear optimization model of the United States electricity industry. CGE, or "top down," models emphasize interrelationships in the economy and how economic theory can be used to evaluate policy responses in a model with real-world data. However, they tend to lack the technological detail needed to examine some types of legislative proposals, especially those related to renewable electricity generation. On the other hand, "bottom up" technology models can provide much more detailed characterization of generation options, renewable resources, and electricity demand, but lack the ability to look at national policies in a broader context if there are macroeconomic implications to policy features. (1)

   This paper attempts to combine the best feature of both classes of models in order to explore the impacts of alternative transition pathways to a future economy with fewer GHG emissions. Several scenarios are run to evaluate the impacts of technological availability on model results. Results of all scenarios are compared against a "business-as-usual" reference forecast to examine effects on emissions levels and the resulting GHG allowance prices, along with economic indicators such as Gross Domestic Product (GDP) and household consumption, and energy prices. The rest of the paper is organized along the following lines: Section 2 first describes the CGE component of the ADAGE model, followed by a description of the electricity model that places a special emphasis on modeling the characteristics of renewable generation, and finally a discussion of how alternative technology assumptions are considered. Section 3 covers the policy settings of interest, and Section 4 gives model results for GHG allowance prices, electricity generation, and other macroeconomic findings.

2. MODEL DESCRIPTION

   The RTI ADAGE model is a dynamic, intertemporally optimizing CGE model designed to estimate the macroeconomic effects of climate-change mitigation policies, potentially along with the impacts of climate change itself on the economy. Because many of the most effective options for reducing GHG are anticipated to be in the electricity sector, for this investigation the macro-economic component of ADAGE has been linked to a detailed dispatch model of U.S. electricity generation options. The electricity model--RTI Electricity Markets Analysis (EMA) Model--has been adapted to focus on choices related to climate policies and also incorporates information on the characteristics and availability of wind and solar generation from the National Renewable Energy Laboratory's (NREL) ReEDS electricity model (Short et al., 2011).

   2.1 Macroeconomic Model

   The overall structure of ADAGE is similar to other CGE models used to evaluate climate policies such as the MIT EPPA model (Babiker et al., 2008)--see Ross (2009) for more detailed ADAGE model documentation. Economic data in ADAGE come from the IMPLAN and GTAP databases; energy data and various growth forecasts come from the Energy Information Administration (EIA) of the U.S. Department of Energy (2) and the International Energy Agency (IEA). These data are used to describe initial economic and energy market conditions in multiple countries and/or regions to represent the global economy and also the economies of six regions within the United States. ADAGE typically solves in 5-year time intervals from 2010 to 2050 (and beyond) and assumes perfect foresight, where people act to mitigate the impacts of future policies. Emissions and abatement costs for six types of GHG are included in the model--C[O.sub.2], C[H.sub.4],[N.sub.2]O, HFCs, PFCs, and S[F.sub.6].

   The sectors of the economy in ADAGE are shown in Table 1. Much of the emphasis of the structure is on the natural resources and industries necessary to provide energy, along with additional detail on how households allocate their purchases across energy and investment goods such as housing and personal vehicles. Other industries are more aggregated in this version of the model. The United States is separated into six regions, aggregated from EIA's Census regions (see Figure 1). The regional breakdown has been chosen to facilitate the linkage to the electricity model discussed in Section 2.2 below.

   Features of the ADAGE model with the largest effects on estimated results for climate policies include: the initial energy production and consumption levels (based on IEA and EIA data); growth in economic output and consumption (based on the forecasts discussed below); model parameters that control the ability of households and industries to improve energy efficiency, switch among fuels, and reduce demand (see model documentation); inclusion of emissions and abatement costs for five non-C[O.sub.2] GHG (see EPA [2006] for data); representation of new forms of advanced electricity generation--whether nuclear, renewables, or options including carbon capture and storage (CCS)--through a linkage to a detailed electricity model; and, most recently, inclusion of an explicit capital stock in housing that improves the transitional dynamics associated with reducing energy consumption in the residential sector of the economy.

   Given the importance of energy markets to climate policies, ADAGE distinguishes five primary energy sources: coal, crude oil, electricity (through the detailed model), natural gas, and refined petroleum. In addition to detailed electricity generation options, ADAGE includes advanced types of personal transportation vehicles including plug-in hybrid vehicles and electric vehicles. Other production industries in the model are more aggregated to accommodate computational constraints associated with an intertemporally optimizing CGE framework. The overall structure of the model allows ADAGE to estimate allowance prices associated with meeting GHG emissions targets and consistently evaluate impacts of international climate policies on the United States.

   2.2 Electricity Model

   The EMA model is an intertemporally optimizing dynamic linear-programming model of U.S. wholesale electricity markets. It is designed to examine how mid- to long-term policies affecting these markets will influence electricity supply decisions, generation costs, and wholesale electricity prices. To accomplish this, the model determines least-cost methods for meeting electricity demand on a seasonal and time-of-day basis, while considering factors such as growth in demand, peak demands, and any limits on emissions or other electricity policy goals.

   2.2.1 Structure of the Electricity Model

   The basic structure of EMA is similar to other models such as IPM (EPA, 2010), where the objective function of the model attempts to minimize the costs of generating enough electricity to meet exogenous demands. While the linkage to ADAGE requires some modifications to this objective function to facilitate convergence between the two models (see discussion in Section 2.3), the basic structure remains (see Table 2 for details). Annual electricity demands at a regional level (from AEO forecasts) are expressed through load duration curves that convert the annual demand into demands distinguished by season and time of day to reflect the unique, non-storable nature of electricity. The demand side of the model also reflects decisions of generators to maintain adequate reserves over anticipated peak demands to ensure reliability.

   On the supply side of the model, electricity is generated by either existing units or through construction of new units. The NEEDS database (EPA, 2010) of over 15,000 existing units is aggregated into 256 model plants across regions, types, and heat rates. Information from the IPM model (EPA, 2010) also informs the model regarding units' availability, retirement options, and necessary minimum generation levels. Characteristics of new units are taken from the Assumptions to AEO 2011 (U.S. EIA, 2011b), including construction and operating costs and fuel efficiencies. More detailed information on wind generation options is discussed in Section 2.2.2.

   Generating costs for existing units are from IPM (EPA, 2010) and new units are from EIA (2011b). Fuel costs...