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Two-phase Geothermal Source ORC Power Plant

The provided scripts implement a workflow for the parametric optimization of a two-phase geothermal source ORC power plant by applying different search algorithms to a TESPy model of an ORC cycle. Besides parameter influence analysis, both single and multivariate, optimization procedures are available.

Installation and Usage

After downloading install the requirements within a fresh virtual environment:

python -m pip install -r requirements.txt

Three different tasks can be accomplished with the software:

  • single parameter influence analysis (from geothermal_orc import single_parameter_influence),
  • single parameter optimization (from geothermal_orc import single_optimization) and
  • multivariate parameter optimization (from geothermal_orc import multivariate_optimization)

Import the respective functionality and run it with the .json control file. The result date are passed to the function call. Example applications can be found within the scripts folder:

  • single.py
  • parameter_influence.py
  • multivariate.py

Sample input data can be found in the same folder.

Topology and System Design

Alt flow diagram of the geothermal ORC Flow diagram of the geothermal ORC plant (a) and Ts-diagram of the process (b)

Please note: You will find all input parameters as well as all equations applied in the models of the example runs in the pdf model report!

The table below highlights the design parameters of the system.

Item Parameter Symbol Value Unit
Geothermal resource Steam temperature Tgs 140 °C
Steam mass flow rate ṁgs 20 kg/s
Brine temperature Tgb 140 °C
Brine mass flow rate ṁgb 180 kg/s
Steam mass fraction x 0.1 -
Brine/steam pressure pgeo 3.615 bar
Ambient condition Average temperature Tam 5 °C
Average pressure pam 0.6 bar
Location Parameter Symbol Value Unit
Turbine Isentropic efficiency ηs, t 90 %
Feed pump Isentropic efficiency ηs, fp 75 %
Air fan Isentropic efficiency ηs, af 60 %
Main condenser Upper terminal temperature difference ΔTt, u 10 °C
Pressure ratio on hot side pr1 1 -
Pressure ratio on cold side pr2 0.995 -
Geo-steam evaporator Pressure ratio on hot side pr1 1 -
Pressure ratio on cold side pr2 1 -
Geo-brine evaporator Pinch point temperature difference ΔTpp 8 °C
Pressure ratio on hot side pr1 0.98 -
Pressure ratio on cold side pr2 1 -
IHE & preheater Pressure ratio on hot side pr1 0.98 -
Pressure ratio on cold side pr2 0.98 -
Preheater outlet Approach point temperature difference ΔTap 2 °C
Generator Efficiency ηel, mech 97 %
Motors Efficiency ηel, mech 97 %

Configuring the input file

It is possible to choose the decision variables for the optimization as well as the objective of the optimization. Additionally, other boundary conditions can be specified. Apart from the geosteam share three variables or boundary conditions must be specified in total. Available parameters are listed below:

Parameter Meaning
p_before_tur pressure at connection 1
T_before_tur temperature at connection 1
T_reinjection temperature at connection 35
brine_evap_Td temperature change from connection 33 to 34 (negative)
Q_brine_ev heat transferred by brine evaporator
dT_air temperature change from connection 21 to 22
IHE_sizing IHE sizing factor: 0 = IHE non existent; 1 = maximum heat transfer
Q_ihe heat transferred by IHE

Boundary conditions

  • It is mandatory to specify the geosteam share.
  • For single parameter investigation specify two additional parameters
  • For multivariate investigation specify less than two additional parameters

Variables

  • Specify variable(s) to investigate with upper and lower limit as well as tolerance in case of single optimization

Results

  • Specify components, connections and misc for retrieving the respective data in the results DataFrames.

Parameters for misc:

Parameter Meaning
gross power output power output of the rankine cycle only
thermal efficiency efficiency considering gross power output
net power output power output including the power required for the condensator's fans
net efficiency efficiency considering net power output
IHE sizing factor IHE sizing factor (see above)

Possible objectives

Choose from:

  • "gross power output"
  • "net power output"

Reference

An archived version of this repository can be found at zenodo: https://zenodo.org/record/5094931. For more information also see the respective publication: https://doi.org/10.1016/j.energy.2022.123910.

  • Chaofan Chen, Francesco Witte, Ilja Tuschy, Olaf Kolditz, and Haibing Shao. "Parametric optimization and comparative study of an organic Rankine cycle power plant for two-phase geothermal sources." Energy 252 (2022): 123910.

If you have any questions or suggestions feel free to contact us anytime!

License

Copyright (c) 2022 Francesco Witte, Chaofan Chen

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.