Thermo-economic analysis of a direct supercritical CO<sub>2</sub> electric power generation system using geothermal heat

doi:10.1007/s11708-021-0749-9

Front. Energy

2022, Vol. 16

Issue (2) : 246-262 https://doi.org/10.1007/s11708-021-0749-9

RESEARCH ARTICLE

Thermo-economic analysis of a direct supercritical CO₂ electric power generation system using geothermal heat

Xingchao WANG¹, Chunjian PAN²(

), Carlos E. ROMERO², Zongliang QIAO³, Arindam BANERJEE⁴, Carlos RUBIO-MAYA⁵, Lehua PAN⁶

¹. Department of Mechanical Engineering, Colorado School of Mines, Golden, CO 80401, USA; National Renewable Energy Laboratory (NREL), Golden, CO 80401, USA
². Energy Research Center, Lehigh University, Bethlehem, PA 18015, USA
³. Key Laboratory of Energy Thermal Conversion and Control of the Ministry of Education, Southeast University, Nanjing 210096, China
⁴. Department of Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015, USA
⁵. Mechanical Engineering, Universidad Michoacán de San Nicolas de Hidalgo, Morelia, Michoacán C.P. 58030, Mexico
⁶. Energy Geosciences Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, USA

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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 wellbore-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 MW_e 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.

Keywords geothermal heat mining supercritical CO₂ power generation thermo-economic analysis optimization

Corresponding Author(s): Chunjian PAN

About author:

Tongcan Cui and Yizhe Hou contributed equally to this work.

Online First Date: 13 July 2021 Issue Date: 25 May 2022

Cite this article:

Xingchao WANG,Chunjian PAN,Carlos E. ROMERO, et al. Thermo-economic analysis of a direct supercritical CO₂ electric power generation system using geothermal heat[J]. Front. Energy, 2022, 16(2): 246-262.

URL:

https://academic.hep.com.cn/fie/EN/10.1007/s11708-021-0749-9
https://academic.hep.com.cn/fie/EN/Y2022/V16/I2/246

Fig.1 Direct turbine expansion system with CO₂ injection and production geothermal loop (adapted with permission from Ref. [20]).

Fig.2 Sketch of well pattern and CO₂ stream lines in T2Well/ECO2N modeling domain.

Fig.3 Predicted results by T2Well/ECO2N over 30 years under the base case conditions (adapted with permission from Ref. [21]).

Fig.4 Effects on production well head pressure, injection well head pressure, production well head temperature, and production CO₂ flowrate.

Fig.5 Effect of well distance and CO₂ injection flowrate (one-quarter) on output parameters.

Fig.6 Schematic of direct sCO₂ expansion system (adapted with permission from Ref. [21]).

Fig.7 T-s diagram of direct sCO₂ turbine expansion for the base case condition (adapted with permission from Ref. [21]).

Fig.8 Sketch of a well field with well-sets and power plant.

Parameter	Value
Loan period n/a	20
Capacity factor F_capacity	0.75
Geothermal well drilling successful rate S/%	85
Annual interest rate i/%	4
Taxes and insurance factor F_{insurance&tax}/%	1.5
Counted CO₂ sequestration credit $b co 2$ /($·t^–1)	0–5

Tab.1 Parameter values for cost estimation and optimization analysis

Tab.2 Parameter values for base case LCOE optimization analysis

Fig.9 Flowchart of LCOE optimization analysis process.

Parameter	Value
Minimal LCOE/($·kWh^–1)	0.177
Overall cycle thermal efficiency η_th/%	15.13
Optimal well distance R/m	500
Optimal $m ˙ CO 2,inj$ per well-set/(kg·s^–1)	120
Optimal $T CO 2,inj$ /°C	30
Optimal P_bottom,prod/MPa	30
Optimal P_t,dis,opt /MPa	8.07
Number of geothermal well-sets needed	20
Plant capital cost/($1M)	264.25
Geothermal well cost/($1M)	260.01

Tab.3 Results of base case LCOE optimization analysis

Fig.10 LCOE and capital cost versus power plant capacity.

Fig.11 LCOE break points considering CO₂ sequestration credit.

Fig.12 LCOE, system thermal efficiency, and net power output per well-set versus turbine discharge pressure.

Fig.13 Effects of design parameters and operating conditions on LCOE, system thermal efficiency, capital costs, well head pressure difference, and produced sCO₂ flowrate per well-set.

R	The radial distance from the injection well to production well/m
D	Diameter of well/m
$m ˙$	Mass flowrate/(kg·s^–1)
T	Temperature/°C
P	Pressure/MPa
h	Specific enthalpy/(kJ·kg^–1)
s	Isentropic process
Q	Thermal Energy/kW_th
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_CO2	CO₂ sequestration credit/($·t^–1)
V	Volume flowrate//(L·min^–1)
N_wellset	Number of well-set required
W	Power plant capacity/MW_e
e	Error in RSM design
r²	Coefficient of determination
t	Turbine
comp	Compressor
inj	Injection well
prod	Production well
reinj	Re-injection well
dis	Discharge
opt	Optimal value
th	Thermal
α	RSM regression coefficient
ε	Heat exchanger effectiveness
ρ	Density//(kg·m^–3)
η	Efficiency
sCO₂	Supercritical carbon dioxide
RSM	Response surface methodology
LCOE	Levelized cost of electricity
O&M	Operation and maintenance
HX	Heat exchanger
APF	Annual payment factor
M$	Million US Dollars

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