Abstract
Geothermal district heating (GDH) systems have limited penetration in the U.S., with an estimated installed capacity of only 100 MWth for a total of 21 sites. We see higher deployment in other regions, for example, in Europe with an installed capacity of more than 4,700 MWth for 257 GDH sites. The U.S. Department of Energy Geothermal Vision (GeoVision) Study is currently looking at the potential to increase the deployment in the U.S. and to understand the impact of this increased deployment. This paper reviews 31 performance, cost, and financial parameters as input for numerical simulations describing GDH system deployment in support of the GeoVision effort. The focus is on GDH systems using hydrothermal and Enhanced Geothermal System resources in the U.S.; ground-source heat pumps and heat-to-electricity conversion technology were excluded. Parameters investigated include 1) capital and operation and maintenance costs for both subsurface and surface equipment; 2) performance factors such as resource recovery factors, well flow rates, and system efficiencies; and 3) financial parameters such as inflation, interest, and tax rates. Current values as well as potential future improved values under various scenarios are presented. Sources of data considered include academic and popular literature, software tools such as GETEM and GEOPHIRES, industry interviews, and analysis conducted by other task forces for the GeoVision Study, e.g., on the drilling costs and reservoir performance.
Original language | American English |
---|---|
Number of pages | 11 |
State | Published - 2017 |
Event | 42nd Workshop on Geothermal Reservoir Engineering - Stanford University, Stanford, California Duration: 13 Feb 2017 → 15 Feb 2017 |
Conference
Conference | 42nd Workshop on Geothermal Reservoir Engineering |
---|---|
City | Stanford University, Stanford, California |
Period | 13/02/17 → 15/02/17 |
NREL Publication Number
- NREL/CP-5500-67864
Keywords
- direct-use of geothermal energy
- geothermal district heating systems
- techno-economic modeling