A simplified model for the estimation of life-cycle greenhouse gas emissions of enhanced geothermal systems

被引:2
作者
Lacirignola M. [1 ]
Meany B.H. [2 ,4 ]
Padey P. [3 ]
Blanc I. [4 ]
机构
[1] Energy Networks and Renewable Energy Department, French Environment and Energy Management Agency (ADEME), 27 rue Louis Vicat, Paris
[2] Ecole Polytechnique, Route de Saclay, Palaiseau
[3] Energy Group, Institute for Environmental Sciences and Forel Institute, University of Geneva, 7 route de drize, Geneva
[4] O.I.E. - Centre Observation, Impacts, Energie, MINES ParisTech, PSL Research University, CS 10207 rue Claude Daunesse, Sophia Antipolis Cedex
关键词
Enhanced geothermal systems; Global sensitivity analysis; Life-cycle assessment; Simplified model;
D O I
10.1186/s40517-014-0008-y
中图分类号
学科分类号
摘要
Background: The development of ‘enhanced geothermal systems’ (EGS), designed to extract energy from deep low-enthalpy reservoirs, is opening new scenarios of growth for the whole geothermal sector. A relevant tool to estimate the environmental performances of such emerging renewable energy (RE) technology is Life Cycle Assessment (LCA). However, the application of this cradle-to-grave approach is complex and time-consuming. Moreover, LCA results available for EGS case studies cover a fairly high variability range. Methods: A new type of LCA-based approach, called simplified model, is developed based on the analysis of environmental performance variability of energy pathways. Such methodology has been applied to produce a reduced parameterized model, designed to estimate life-cycle greenhouse gas (GHG) emissions of EGS power plants applicable to a large sample of configurations. Results: Two parameterized models to assess EGS greenhouses gases (GHG) are the outcomes of this study. A parameterized reference model is developed to describe a large sample of possible EGS power plants located in central Europe. Two or three wells plants equipped with a binary system producing only electricity are accounted for. Applying global sensitivity analysis (GSA) to this reference model allows the identification of three key variables, responsible for most of the variability on GHG results: installed power capacity, drilling depth, and number of wells. A reduced parameterized model for the estimate of the GHG performances as the only function of these three key variables is then established. A comparison with the results of published EGS LCAs confirms the representativeness of our new simplified model. Conclusions: Our simplified model, issued from the reference parameterized model, enables a rapid and simple estimate of the environmental performances of an EGS power plant, avoiding the extensive application of the LCA methodology. It provides an easy-to-use tool for the stakeholders of the EGS sector and for decision makers. It aims at contributing to the debate about the performances of this new emerging technology and its related environmental impacts. © 2014, Lacirignola et al.; licensee Springer.
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页数:19
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