Abstract
A comprehensive thermo-economic model combining a geothermal heat mining system and a direct supercritical CO2 turbine expansion electric power generation system was proposed in this paper. Assisted by this integrated model, thermo-economic and optimization analyses for the key design parameters of the whole system including the geothermal well pattern and operational conditions were performed to obtain a minimal levelized cost of electricity (LCOE). Specifically, in geothermal heat extraction simulation, an integrated well-bore-reservoir system model (T2Well/ECO2N) was used to generate a database for creating a fast, predictive, and compatible geothermal heat mining model by employing a response surface methodology. A parametric study was conducted to demonstrate the impact of turbine discharge pressure, injection and production well distance, CO2 injection flowrate, CO2 injection temperature, and monitored production well bottom pressure on LCOE, system thermal efficiency, and capital cost. It was found that for a 100 MWe power plant, a minimal LCOE of $0.177/kWh was achieved for a 20-year steady operation without considering CO2 sequestration credit. In addition, when CO2 sequestration credit is $1.00/t, an LCOE breakeven point compared to a conventional geothermal power plant is achieved and a breakpoint for generating electric power generation at no cost was achieved for a sequestration credit of $2.05/t.
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Abbreviations
- R :
-
The radial distance from the injection well to production well/m
- D :
-
Diameter of well/m
- ṁ :
-
Mass flowrate/(kg·s−1)
- T :
-
Temperature/°C
- P :
-
Pressure/MPa
- h :
-
Specific enthalpy/(kJ·kg−1)
- s :
-
Isentropic process
- Q :
-
Thermal energy/kWth
- v :
-
Velocity/(m·s−1)
- z :
-
Well depth/m
- S :
-
Well drilling successful rate/%
- C :
-
Cost/M$
- F capacity :
-
Capacity factor
- F insurance&taxes :
-
Taxes and insurance factor
- i :
-
Annual interest rate/%
- n :
-
Loan period/a
- \({b_{{\rm{C}}{{\rm{O}}_2}}}\) :
-
CO2 sequestration credit/($·t−1)
- V :
-
Volume flowrate//(L·min−1)
- N wellset :
-
Number of well-set required
- W :
-
Power plant capacity/MWe
- e :
-
Error in RSM design
- r 2 :
-
Coefficient of determination
- t :
-
Turbine
- comp:
-
Compressor
- inj:
-
Injection well
- prod:
-
Production well
- reinj:
-
Re-injection well
- dis:
-
Discharge
- opt:
-
Optimal value
- th:
-
Thermal
- α :
-
RSM regression coefficient
- ε :
-
Heat exchanger effectiveness
- ρ :
-
Density//(kg·m−3)
- η :
-
Efficiency
- sCO2 :
-
Supercritical carbon dioxide
- RSM:
-
Response surface methodology
- LCOE:
-
Levelized cost of electricity
- O&M:
-
Operation and maintenance
- HX:
-
Heat exchanger
- APF:
-
Annual payment factor
- M$:
-
Million US Dollars
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Acknowledgements
This work was funded by the Mexican National Council of Science and Technology (CONACYT in Spanish), under the Sectorial Fund for Energy Sustainability, CONACYT-Secretary of Energy (No. S0019-2012-04).
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Wang, X., Pan, C., Romero, C.E. et al. Thermo-economic analysis of a direct supercritical CO2 electric power generation system using geothermal heat. Front. Energy 16, 246–262 (2022). https://doi.org/10.1007/s11708-021-0749-9
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DOI: https://doi.org/10.1007/s11708-021-0749-9