Impact of enhanced geothermal systems on US energy supply in the twenty-first century |
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Authors: | Tester Jefferson W Anderson Brian J Batchelor Anthony S Blackwell David D DiPippo Ronald Drake Elisabeth M Garnish John Livesay Bill Moore Michal C Nichols Kenneth Petty Susan Toksoz M Nafi Veatch Ralph W Baria Roy Augustine Chad Murphy Enda Negraru Petru Richards Maria |
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Affiliation: | Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA. testerel@mit.edu |
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Abstract: | Recent national focus on the value of increasing US supplies of indigenous renewable energy underscores the need for re-evaluating all alternatives, particularly those that are large and well distributed nationally. A panel was assembled in September 2005 to evaluate the technical and economic feasibility of geothermal becoming a major supplier of primary energy for US base-load generation capacity by 2050. Primary energy produced from both conventional hydrothermal and enhanced (or engineered) geothermal systems (EGS) was considered on a national scale. This paper summarizes the work of the panel which appears in complete form in a 2006 MIT report, 'The future of geothermal energy' parts 1 and 2. In the analysis, a comprehensive national assessment of US geothermal resources, evaluation of drilling and reservoir technologies and economic modelling was carried out. The methodologies employed to estimate geologic heat flow for a range of geothermal resources were utilized to provide detailed quantitative projections of the EGS resource base for the USA. Thirty years of field testing worldwide was evaluated to identify the remaining technology needs with respect to drilling and completing wells, stimulating EGS reservoirs and converting geothermal heat to electricity in surface power and energy recovery systems. Economic modelling was used to develop long-term projections of EGS in the USA for supplying electricity and thermal energy. Sensitivities to capital costs for drilling, stimulation and power plant construction, and financial factors, learning curve estimates, and uncertainties and risks were considered. |
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