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Title: Future Scenario Development from Disruptive Exploration Technologies and Business Models in the U.S. Geothermal Industry

Abstract

With recent trends toward intermittent renewable energy sources in the U.S., the geothermal industry in its current form faces a crossroad: adapt, disrupt, or be left behind. Strategic planning with scenario analysis offers a framework to characterize plausible views of the future given current trends - as well as disruptions to the status quo. To inform strategic planning in the Department of Energy's (DOE) Geothermal Technology Office (GTO), the Geothermal Vision Study is tasked with offering data-driven pathways for future geothermal development. Scenario analysis is a commonly used tool in private industry corporate strategic planning as a way to prioritize and manage large investments in light of uncertainty and risk. Since much of the uncertainty and risk in a geothermal project is believed to occur within early stage exploration and drilling, this paper focuses on the levers (technical and financial) within the exploration process that can be pulled to affect change. Given these potential changes, this work first qualitatively explores potential shifts to the geothermal industry. Future work within the Geothermal Vision Study will incorporate these qualitative scenarios quantitatively, in competition with other renewable and conventional energy industries.

Authors:
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Office (EE-4G)
OSTI Identifier:
1357743
Report Number(s):
NREL/CP-6A20-66670
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the Geothermal Resources Council Annual Meeting (GRC 2016), 23-26 October 2016, Sacramento, California
Country of Publication:
United States
Language:
English
Subject:
15 GEOTHERMAL ENERGY; disruptive technology; scenario analysis; business models; exploration; strategic planning

Citation Formats

Wall, Anna. Future Scenario Development from Disruptive Exploration Technologies and Business Models in the U.S. Geothermal Industry. United States: N. p., 2017. Web.
Wall, Anna. Future Scenario Development from Disruptive Exploration Technologies and Business Models in the U.S. Geothermal Industry. United States.
Wall, Anna. Mon . "Future Scenario Development from Disruptive Exploration Technologies and Business Models in the U.S. Geothermal Industry". United States. doi:.
@article{osti_1357743,
title = {Future Scenario Development from Disruptive Exploration Technologies and Business Models in the U.S. Geothermal Industry},
author = {Wall, Anna},
abstractNote = {With recent trends toward intermittent renewable energy sources in the U.S., the geothermal industry in its current form faces a crossroad: adapt, disrupt, or be left behind. Strategic planning with scenario analysis offers a framework to characterize plausible views of the future given current trends - as well as disruptions to the status quo. To inform strategic planning in the Department of Energy's (DOE) Geothermal Technology Office (GTO), the Geothermal Vision Study is tasked with offering data-driven pathways for future geothermal development. Scenario analysis is a commonly used tool in private industry corporate strategic planning as a way to prioritize and manage large investments in light of uncertainty and risk. Since much of the uncertainty and risk in a geothermal project is believed to occur within early stage exploration and drilling, this paper focuses on the levers (technical and financial) within the exploration process that can be pulled to affect change. Given these potential changes, this work first qualitatively explores potential shifts to the geothermal industry. Future work within the Geothermal Vision Study will incorporate these qualitative scenarios quantitatively, in competition with other renewable and conventional energy industries.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2017},
month = {Mon May 01 00:00:00 EDT 2017}
}

Conference:
Other availability
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