|Title||Potential for Renewable Energy Development: Alternatives to AEO2001|
|Year of Publication||2001|
|Authors||Peter T Chan, Julie G Osborn, Kristina Hamachi LaCommare, Chris Marnay, Etan Gumerman|
Levelized cost of energy assumptions for renewable energy technologies significantly influence forecast projections of U.S. grid-connected power generation and associated carbon emissions. Assumptions that are based on cost alone ignore the potential of other factors, such as direct access and green marketing, to drive capacity expansion. In recent years, deregulation has enabled consumers in many states to purchase electricity from renewable sources, even if it is not the least-cost option. Capacity expansion decisions in the National Energy Modeling System (NEMS) are primarily determined by factors directly affecting the cost of energy. NEMS is a commonly referenced computer model of the U.S. energy-economy that is used by the U.S. Department of Energy to produce the Annual Energy Outlook and its projections through 2020. In NEMS, renewable energy technologies fail to capture a significant share of the electricity market, even by the end of the forecast period.
This study explores the potential impact of green marketing-supported electric-generator capacity additions and alternative cost of energy assumptions for renewable energy technologies on the overall cost and development of renewable grid-connected power generation in a modified version of NEMS. The expectation is that policies and programs designed to increase market share will leverage economies of scale and learning by doing that will in turn help reduce the cost of these technologies, making them more cost-competitive in the long run with currently established technologies. Seven simulations were conducted using a modified version of the Energy Information Administration's National Energy Modeling System (NEMS-GPRA)1. Results are compared to the Annual Energy Outlook 2001 (AEO2001) Reference Case for six renewable energy technologies. For each of these scenarios, the renewable energy technologies considered were geothermal, biomass, solar thermal, solar photovoltaic, wind and municipal solid waste (excluded in the levelized cost scenarios).