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Geothermal probabilistic cost model with an application to a geothermal reservoir at Heber, California

Authors: Orren, Lowell H.; Ziman, G. Michael; Jones, Sue C.;

Geothermal probabilistic cost model with an application to a geothermal reservoir at Heber, California

Abstract

A financial accounting model that incorporates physical and institutional uncertainties was developed for geothermal projects. Among the uncertainties it can handle are well depth, flow rate, fluid temperature, and permit and construction times. The outputs of the model are cumulative probability distributions of financial measures such as capital cost, levelized cost, and profit. These outputs are well suited for use in an investment decision incorporating risk. The model has the powerful feature that conditional probability distribution can be used to account for correlations among any of the input variables. The model has been applied to a geothermal reservoir at Heber, California, for a 45-MW binary electric plant. Under the assumptions made, the reservoir appears to be economically viable.

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United States
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Keywords

Power Range 10-100 Mw, 330, Mathematical Models, Economics, Cost, Heber Geothermal Field, Binary-Fluid Systems, Geothermal Fields, 15 Geothermal Energy, Economic Analysis, Resources, Capitalized Cost, Sensitivity Analysis, Geothermal Legacy, Geothermal Power Plants, Resource Development, Investment, Energy Systems, Thermal Power Plants Geothermal Legacy 150800* -- Geothermal Power Plants, Institutional Factors, Geothermal Resources, Power Plants, Profits, Probability

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citations
The total number of citations received by all articles of the researcher of interest.
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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