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The National Energy Modeling System APPENDIX D ILLUSTRATIVE CASE STUDIES As the committee deliberated the requirements of the proposed National Energy Modeling System (NEMS), it decided to undertake three hypothetical case studies that would generate some generic understanding of how a NEMS might be applied and what kinds of analyses it could provide. The three examples presented in this appendix address energy demand, energy supply and research and development (R&D) program planning. Case Study 1 relates to automobile fuel economy standards, Case Study 2 to natural gas pipeline certification, and Case Study 3 to R&D program planning for magnetically levitated trains. They resulted in some general insights about what a NEMS could and could not be expected to provide as explained later. CASE STUDY 1: AUTOMOBILE EFFICIENCY STANDARDS Establishing the Need for Policy Intervention In our economic and political system it is generally presumed that individuals make economic choices that serve their self-interest, and will balance the costs and benefits of energy efficiency in making decisions such as automobile purchases. The aggregate of all such choices by consumers will provide the market's preference for energy efficiency and guidance to auto producers about the array of options to offer consumers. This model of perfectly rational decision makers operating in a textbook market often fails to describe the real world. The extent to which the perfect market paradigm characterizes real markets for energy supply or energy demand has a great deal of
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The National Energy Modeling System relevance to the issue of government intervention. If the market is functioning perfectly, and all costs are reflected in the marketplace, then government intervention will always reduce economic efficiency. But if the market fails to perform as microeconomic theory would hold, or if significant costs or benefits are not reflected in market prices for energy or energy services, then carefully designed government policies can improve economic efficiency. Thus, a necessary condition for government intervention in the market is the existence of significant market failures or externalities. These can be identified either empirically--through studies showing that the market does not produce the results consistent with economic theory--or preferably by identifying specific mechanisms of market failure. Next, the sufficient condition for government intervention is that the benefits of intervention must exceed its direct and indirect costs. In the case of standards, not only should the benefits exceed the costs, but the benefits of a particular level of standards should be higher than alternative levels, and the benefits of standards as a policy must be greater than the benefits of alternative policies that could achieve similar results. The quantitative analysis of market failures, and the cost-benefit analysis of alternative policies intended to address those failures, would make use of the National Energy Modeling System (NEMS). Analytical Requirements The first step is to analyze market failures that may be affecting the choice of automotive fuel economy. The existence of market failures would explain why there are societally cost-effective improvements in energy efficiency that are not currently being exploited. The analysis would attempt to identify all possible externalities and market failures with a bearing on the efficiency issue, and determine the best ways of rectifying these failures. This analysis will develop the arguments as to whether government mandated efficiency standards will best address those market failures. Efficiency standards may represent a “second-best” approach to these market failures, in which case the infeasibility of first-best approaches must be established. Plausible externalities to be examined include: Presence of market power over the world oil price; Degradation of environmental resources that are not factored into private consumption and production decisions; The public good aspects of investment in research and development (R&D) that would cause the private sector to underinvest in more efficient technology; Possible differences between social and private discount rates; and
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The National Energy Modeling System Economic costs of oil market disruptions that are not internalized in private decisions (i.e., energy security externalities). Once the linkage between market failure and efficiency standards has been established conceptually, it is time to turn to NEMS for quantitative analysis that will help set a standard and determine how it is to be implemented. Presumably, the standard will be set on the basis of a quantitative estimate of the magnitude of the distortion in consumer preference for efficiency caused by market failures. Thus, NEMS must include certain ingredients: Data that describes the current vehicle fleet; A model that describes the vintaging of the fleet under different assumptions; A production cost model that calculates the cost of standards and their effect on producer surplus; A consumer choice model that will estimate the effect on auto demand caused by changes in efficiency and auto prices, gasoline prices, safety, and other relevant variables; and; A travel demand model that will estimate the effect of standards on fuel consumption and, together with (d), the effect on consumer surplus. A more complete policy analysis requires comparisons between the economic costs and benefits of standards with alternative policies that will achieve similar results, such as: Higher excise taxes on gas guzzlers; Rebates on high miles-per-gallon cars, possibly on a sliding scale and in conjunction with (1); Sliding scale subsidies for high mileage cars, funded by gasoline taxes or registration fees; Higher gasoline taxes; Subsidies to consumers or manufacturers for higher efficiency cars; and Subsidies or taxes to promote the use of alternative fuels. Each of these policies will have implications for the economy, for the environment, and for energy security. Consequently, the analysis must include an evaluation of relationships between each policy action and the primary measures of output discussed in Chapter 2.
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The National Energy Modeling System Even the most complete form of NEMS cannot accomplish all the tasks described above. Independent analytical input is required in identifying market failures and in establishing a cost-benefit framework that gives meaning to the quantitative output of the models. In addition, key decisions must be made by policymakers in setting the standard (i.e., in balancing costs and benefits), in choosing between standards and alternative policies, and in choosing an implementation strategy. Nevertheless, it may be concluded that: The structure and use of the NEMS can be changed to handle these analyses. Not all of the separate pieces of the analysis need be done directly within the NEMS. However, NEMS can provide a consistent framework for the off-line analyses. The NEMS will require more and greater data disaggregation on the demand side than currently available. The NEMS must provide a better representation of economic decision making by energy consumers and by other related elements of the economy. CASE STUDY 2:NATURAL GAS PIPELINE CERTIFICATION Establishing the Need for Policy Intervention This problem arose in the following context. The Federal Energy Regulatory Commission (FERC), a quasi-independent regulatory body with commissioners appointed by the Executive Branch, but statutorily independent from the Department of Energy, is charged with the responsibility of certifying the need for new natural gas pipelines. Such a certificate is required before any new interstate transportation system for natural gas can be operated. There are those who believe that the FERC has been slow in issuing these certificates and thus has inhibited the development of new natural gas reserves and the effective use of existing reserves to the detriment of sound National Energy Strategy. Could a model be used to quantify the consequences of inaction by the FERC and thus support the policy prescription that the FERC be abolished and the function transferred to the Department of Energy? Analytical Requirements The natural gas transportation problem involves distributing from supply sources to points of end use. As supply will include gas from new fields in the Rocky Mountains and also from Canadian reserves and will include new uses on both coasts, the need for new pipelines is clear. Producers in the new fields are interested in seeing adequate transportation for development of their reserves. Customers are interested in seeing new supplies and in generating gas on gas competition from different regions as a means of holding down prices. Prospective investors in new pipelines see the opportunity to generate profits by matching supply and demand. Several groups of investors are competing for the
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The National Energy Modeling System rights to construct new facilities. Construction of a new pipeline confers at least a partial natural monopoly to its owners. All of the competing proposals cannot be built and operated profitably. Which of the new proposals are in the “public interest?” At the same time, existing producers and pipeline owners have competing proposals for expansion of existing systems as a “cheaper” method of satisfying the need. Should these proposals be accepted as well? What are the consequences of “overbuilding” or “underbuilding?” To the extent that pipelines to the East are constructed and reserves are dedicated to this region, fewer reserves are available to be dedicated to existing or potential customers in the West. Some of these customers may not have “acceptable” alternative energy supplies. Which allocation of resources is in the “national interest?” What will the consequences for energy security and/or trade matters be if the nation or specific regions become dependent on Canadian gas? These are the types of questions facing the FERC in a pipeline certification case. Clearly, a model of the natural gas system indicating supplies, the existing distribution system, and points of end use would be useful in answering these questions. In fact, of course, these models exist. The American Gas Association model and the models used by the Gas Research Institute are examples of relatively comprehensive models of natural gas supply and demand that are continually updated and validated in an open forum by competent modelers backed by a comprehensive data base and adequate budgets. Many other such models exist and are operated by public agencies, private interest groups and third party modelers and consultants. There is no doubt that the interested parties to the FERC proceedings have their own models and have used these models to show the benefits of their own proposal or position. There is no doubt that the answers conflict. The answers conflict because of varying model constructs, different data base information, different assumptions about future conditions, and different objective functions. In this setting, how is one to judge the performance of the FERC? It is certainly possible to use a model to “quantify” a prejudice or preconceived notion one has on the question. Armed with a historical data base and an appropriate model, one could simulate the past twenty or thirty years of energy supply and demand with the only independent variable being new gas pipeline construction. Then using some objective function related to, say, minimizing the cost of energy services, compare the current actual pipeline configuration with the “optimum” configuration computed by the model. All else being equal, the difference could be ascribed to be the “cost” of the FERC. Alternately, using a consistent future scenario, the model could be run with and without new pipeline capacity, or with a “regulatory lag” of an extra, say, two years. Differences in the objective function could be ascribed to inaction or slow reaction by the FERC. The Role of Analysis There are obvious problems with either of these approaches even when the model adequately addresses the physical situation. The first problem relates to the “all else being equal” constraint. This constraint is never absolutely true. The more significant new pipeline construction is to overall energy supply and demand, the more difficult it is to make appropriate simplifying assumptions without distorting the answer. At the other
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The National Energy Modeling System extreme, that is new pipeline construction does not matter to aggregate supply and demand, the small difference between two large numbers generated as “the answer” by the model is mathematically extremely imprecise. The second set of problems relates to the definition of the objective function. The model can be fairly simple and the data required readily available if the objective function is narrowly defined. If cost of service tariff minimization on the pipeline system as a whole over a ten or twenty year period is the only objective, the answer can be obtained without too much difficulty. Natural gas burner tip price minimization with fuel switching requires larger models and significantly more data. As soon as real world considerations of “externalities” including environmental factors in production, transportation and consumption; treaties and trade policy with other sovereign countries; regional political considerations, etc. are included, the problems become very large. The third set of problems relates to ascribing any difference between the objective functions to a policy solution that abolishes the FERC. Just because the FERC under past commissioners and policies may have “made a mistake,” is no reason to expect that the errors will continue or that some alternate regulatory body or the “free market” can do a better job in the future. The sum total of these problems could dwarf the technical modeling issues and data requirements. In fact, no simple model run is likely to be very useful in grading the performance of the FERC or guiding an alternate regulatory construct. This is not to say that models are not useful in pipeline certification cases. The opposite is true. There is great value in having all parties argue before the FERC or any subsequent regulatory body using consistent historical data, common future reference cases and similar modeling tools. The process will select those models and the data that are most useful to decision making. The process will ensure that data bases are kept current and complete, that new modeling techniques are employed and that externalities are quantified and considered as society muddles through the tradeoffs. This analytical framework, although developed and used by FERC for pipeline certification, is valuable to a NEMS. Models and data could be transferred wholesale to NEMS or simplified for inclusion in the more general model. At the same time, the consistency of having to use a NEMS data and policy set as a base case for pipeline certification is just as useful in the other direction. However, the question of whether the FERC should be restructured or report directly into the Executive Branch as an advocate of policy is not likely to be settled by a natural gas supply and demand model specifically or a NEMS generally. In summary, the NEMS should be capable of evaluating the economic, environmental, and energy security implications of the various U.S. natural gas alternatives. The gas model needs to include gas transportation alternatives and be able to deal with the uncertainty associated with changing sources and uses for natural gas.
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The National Energy Modeling System CASE STUDY 3: MAGLEV R&D Establishing the Need for Policy Intervention. Evaluating different R&D opportunities at the Department of Energy is one of the more difficult problems for energy models to handle. Nevertheless, the committee believes that modelling can play a useful role in helping set R&D priorities by subjecting all proposals to the discipline of self-consistency with the nation's energy plans and forecasts. Modelling can also help by establishing a uniform context for all projects instead of program-specific assumptions for performing benefit cost analysis. In some cases, merely structuring the decision to involve a benefit cost equation will be a step forward that modelling can help achieve. While a national energy modelling system can be useful in helping to evaluate R&D projects, it cannot provide a complete answer, because many of the calculations that are necessary--even energy modelling calculations--will require additional detail that is not appropriate to put into the NEMS. NEMS modules should be designed to accommodate this added detail, but the detail should not be added to the NEMS unless the need for this detail is demonstrated on a repetitive basis. Nevertheless, NEMS may have a role in the analysis even where off-line analyses are also needed, to establish consistency. The consistency should work in two directions: the results of more detailed modeling for specific program evaluation should be consistent with the more simplified modeling that goes into NEMS. Because of this need for interaction between the NEMS and more detailed models, DOE program offices must have independent analytical capabilities. These conclusions were guided by the following analysis of the case study of evaluating R&D proposals for magnetically levitated passenger railroads (MAGLEV). This case study addresses the questions of what the NEMS should be expected to offer to the R&D portfolio planning process by analyzing what it could offer to the evaluation of high speed rail. Analytical Requirements EIA is under pressure to make technology assumptions in projections explicit in order to assist DOE in evaluating the potential benefits and other impacts of candidate programs for R&D funding. The ultimate objective would be to establish R&D program priorities on a benefit to cost basis to assist in program planning and budgetary tradeoffs. There are several analytical requirements in R&D program planning. NEMS can contribute to some of them: The R&D technical and economic targets must be established for the technology and constantly updated as the R&D progresses. They include target efficiencies and capabilities, target capital and operating costs, target dates for market availability. These are the responsibility of the program manager.
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The National Energy Modeling System The setting or outlook in which the technology must enter the market should be uniformly established to impose discipline on benefit-cost evaluations and comparisons among competitive R&D proposals. A NEMS “base case” without DOE sponsored R&D could provide consistent inputs such as energy service requirements--fuel and electricity price tracks--economic parameters such as inflation rates, cost of money. (There may be more than one such scenario measures of uncertainty.) The program manager is a potential NEMS user. Specific considerations of market entry and competitive technologies to the candidate R&D should be proposed by the program manager and validated in negotiation with NEMS (to the advantage of both). One implication of this is that the program office must acquire substantial analytical capabilities. For this kind of program office analysis to be effective, DOE must invest in research on non-technology issues (e.g., economic market and decision-making and policy issues related to land-use decision making-policy issues) relevant to such analysis. The Analytic Process and the Use of NEMS The process of analyzing an R&D option such as MAGLEV could begin with the use of the NEMS base case without advanced inter-city transportation technology research. This will provide a projected description of: Costs of fuels and electricity; Economic parameters--cost of money, disposable income, etc.; Transportation efficiencies--air, rail, vehicle fleets; and Needs for personal transportation. These needs would be contained at some level of disaggregation in the transport module of the NEMS. Possible disaggregations include separation into urban, suburban, and inner city travel, separation of inner city travel by trip distance or by region or by transportation corridor, and possibly down to the consolidated metropolitan statistical area (CMSA) level. To the extent that these disaggregations are not incorporated in the NEMS, they are likely to be necessary as described below for inclusion in a more detailed model that can be used for evaluating MAGLEV. The program office will then provide: Technological capability of new technology, speed, capacity, electric efficiency (energy use per passenger mile); Cost of new technology--capital, operating; Costs of competing technologies, including conventional technology such as highways, cars, airports, and planes;
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The National Energy Modeling System Estimated market entry date; Probability of success (used to discount potential benefits in comparative analysis); Estimates or models of market penetrations of the new technology, if successful. Outputs should be made compatible with NEMS. The analytic process would proceed as follows: The program office may use detailed transportation models to evaluate market entry. Parameters would be consistent with NEMS base case. Program office inputs would be run in NEMS to evaluate macro impacts: National Security (oil savings) Environmental impacts (emissions tradeoffs: vehicles vs. electric power production) Macroeconomic impacts (consumer surplus) Capital requirements of the changed transportation system would be provided by these program managers. These would be incorporated into an economic growth model as part of NEMS (if part of NEMS). That would require a suitable economic growth model to be developed and made a module of NEMS. More detailed model and off-line analysis compare costs of R&D to benefits for comparison with other candidates. Validation with NEMS run reveals contradictions and can lead to negotiations. This more detailed analysis off-line should consider a number of issues regarding MAGLEV including its benefits or disbenefits in convenience relative to competing modes, including conventional rail, European or Japanese style high-speed rail, automobile, and air travel. Such discussions would include dimensions of analyzing which corridors MAGLEV would be appropriate in, whether MAGLEV would have capacity advantages within that corridor compared to other options, whether capacity expansions of airports or highways would be needed without MAGLEV in that corridor and the relative capital costs of those options, and related land-use issues. The process of validation and negotiation would serve two functions: it would provide discipline to the project manager in projecting a stream of benefits from the project consistent with the rest of the nation's energy (and in this case transportation) systems, and may improve the structure of NEMS by comparison with the more detailed off-line model. Over time, technology paths in base case and NEMS at large are improved through negotiations and external program office micro analyses.
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The National Energy Modeling System The Role of Analysis Establishment of appropriate base cases. R&D programs should be compared to a base case of DOE's current R&D budget, which may be zero for a particular technology. One option that must be considered is that entities other than DOE will do the R&D; for example, in this case, private transportation companies or foreign companies or governments. One should also consider the alternative case in which no R&D is done but similar options such as conventional rail high-speed trains using current or incremental improvements on current technologies are built, or that foreign or industrial R&D efforts will produce the needed technologies. Varying levels of DOE effort. How much would the proposed program be slowed down if its budget were reduced? Is there a minimum viable level of effort to make the R&D worthwhile? Double counting alternative R&D approaches. For example, will advanced vehicle R&D reduce the number of gallons of gasoline that can be saved by MAGLEV? Alternative NEMS scenarios. Will the value of MAGLEV change radically under different economic, technical, or policy scenarios? SUMMARY In summary, then, these case studies illustrate the following points: Important policy options including R&D portfolio planning should be subjected to consistent scenario discipline. NEMS can be of value in establishing parameters for this consistency. Program offices must have independent analytical capabilities. NEMS should integrate additional detail only as the repetitive need is demonstrated, but it should be improved to remain consistent with detailed analysis once it is validated. NEMS modules should be designed to accommodate added detail, but all detail must not be added to NEMS and NEMS may have a role in analysis where off-line analyses are also needed.
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