NEEDS: Nuclear Energy Electrical Demand Simulation

Abstract

A computer model is presented called NEEDS — an acro nym for Nuclear Energy Electrical Demand Simulation- which can simuZate the nuclear sector of the United States electric power economy. The code can forecast the impact of various nuclear-reactor growth patterns over the next fifty years in terms of economics, resource utilization, and the requirements for a supporting fuel-cycle industry. NEEDS was developed for the Office of Energy Research and Development Policy of the National Science Foundation as a tool to help evaluate alternative fission reactor develop ment strategies involving advanced reactor concepts, including advanced high-temperature gas-cooled reac tor (HTGR) systems, the gas-cooled fast reactor (GCFR), the molten-salt breeder reactor (MSBR), the Zight-raater breeder reactor (LWBR), and the heavy- water reactor (HWR) . The objectives of the study were to calculate the impacts, benefits, and require ments of various nuclear growth patterns and to determine the sensitivity of these measures to input parameters which are dominating, uncertain, or sub ject to wide variations. The NEEDS model is currently being used to answer such questions as: What benefits would the United States realize by developing the MSBR, the GCFR, or the LWBR as alternatives to the LWR/HTGR/LMFBR power economy? What are the potential impacts on enrich ment requirements and uranium demand of changing per cent tails assay? How does a power economy based upon a thorium-U233 fuel cycle compare with a pluto nium economy? The model has been used to relate the research-and-development requirements for developing an advanced reactor concept to the availability of the reactor system and its impact on the nuclear economy. In summary, the NEEDS model was developed to study questions of national nuclear policy using a simple modeling approach and minimal input data requirements. The model can forecast the impact of nuclear power development under selected national policy options and potential growth scenarios.