LBNL Report Number
This study investigates the effect of modeling assumptions about levelized costs and market penetration on the U.S. Department of Energy's Annual Energy Outlook (AEO) forecast for wind technologies. The AEO's annual report of energy supply, demand, and prices through 2020 is based on results from the Energy Information Administration (EIA) National Energy Modeling System (NEMS). NEMS predicts the market penetration of individual energy technologies based on a variety of inputs and assumed changes in these base values over time. The NEMS forecast of technology adoption and use is influenced most strongly by the model's assumptions about the levelized cost of energy for the various technologies. For each year, NEMS allocates a share of the energy market to least-cost technologies; this allocation affects forecasts for future years. NEMS uses cost multipliers and constraints to represent potential physical and economic limitations on growth in capacity; these limitations include depletion of resources, costs of rapid manufacturing expansion, and the stability or instability of the power grid when high levels of generation come from intermittent resources. Wind power was chosen as a case study because it is found over a relatively wide geographic range and is the closest of the renewable technologies to being economically competitive. Because wind power is modeled similarly to some of the other renewable technologies, such as solar thermal and photovoltaics (PV), our findings may be applicable to these areas of NEMS as well. Our sensitivity analysis focused on relaxing assumptions (not including capital cost) to make them less restrictive to wind development. In our initial explorations, we conducted a limited set of runs with more restrictive assumptions and found that those scenarios did not differ much from the Reference Case results. Therefore, we concluded that further restricting the assumptions would not be very instructive. In this report, we first review the NEMS model structure and input data for wind power. We then present the results of a sensitivity analysis of wind development in NEMS to the assumptions other than capital cost that are used by the model for economic and physical conditions that affect wind resource development.