RankineLab is a MATLAB tool for the thermodynamic analysis and optimization of Rankine cycles. The code was developed aiming at simplicity and flexibility in terms of cycle configurations and operating conditions. Some of the notable features of the code are listed below:
- Supports simple and recuperated Rankine cycle architectures.
- Supports a wide range of cycle configurations, including: trilateral, partial-evaporation, saturated, superheated, transcritical, and supecritical cycles.
- Supports a wide range of fluids, such as water, carbon dioxide, refrigerants, hydrocarbons and siloxanes.
- Supports first law (energy) and second law (exergy) cycle analyses.
- Uses the equations of state of the CoolProp or REFPROP fluid libraries to compute the thermodynamic properties of the fluids.
- Uses the gradient-based algorithms of the MATLAB Optimization Toolbox to find the optimal cycle configuration in a systematic way. The usual execution time for one cycle optimization is less than 10 seconds on a single core.
In order to use RankineLab, you need a MATLAB installation and the MATLAB Optimization Toolbox. In addition you need to install CoolProp and interface it with MATLAB through Python. This may sound complicated, but it is not!
Check the step-by-step instructions below to learn how to interface MATLAB with CoolProp in a Windows operating system. The installation for Linux or Mac operating systems would be similar.
Download the Miniconda environment management system and follow the installation instructions.
Open a Miniconda terminal (look for "Anaconda Prompt" or "Miniconda3"). Once the terminal is open, type the following command to create a new virtual environment named coolprop_env:
conda create --name coolprop_env python=3.8Don't worry if you are not familiar with the command window or with virtual environments, you only have to type two more commands before the installation is complete. Now that the environment is created, you can activate it. Just use the following command:
conda activate coolprop_envFinally, type the following command to install CoolProp:
conda install CoolProp --channel conda-forgeThat's it! Note that it was necessary to tell Miniconda that it should look for Coolprop in the conda-forge channel.
Open MATLAB (or close and open it if it was already open) and type the following command to let MATLAB know where is the Python executable (python.exe) of the virtual environment that you have just created:
pyversion C:\Users\rober\.conda\envs\coolprop_env\python.exeNote that, in my case, the executable was located at C:\Users\rober\.conda\envs\coolprop_env\. You should replace this part with the correct path in your computer.
Good! You have installed CoolProp and interfaced it with MATLAB. Let's do a simple test to check if the installation was successful. We are going to use CoolProp to compute the saturation temperature of water at atmospheric pressure. Just type the following command in MATLAB:
py.CoolProp.CoolProp.PropsSI('T','P',101325,'Q',0,'Water')If it does not throw and error and returns 373.1243 K, the installation was successful.
The best way to learn how to use RankineLab is to open one of the examples and start playing around with the different parameters and settings. The examples have plenty of comments to guide the users and help them understand how the code works. You can use the example scripts as a template to start your own projects.
Check out the technical note if you want to learn more about the formulation of the optimization problem and the thermodynamic modeling behind RankOpt.
RankineLab is licensed under the terms of the MIT license. See the license file for more information.
RankineLab was developed by Roberto Agromayor and of Lars O. Nord at the Norwegian University of Science and Technology (NTNU). Drop us an email to [email protected] if you have questions about the code or you have a bug to report!
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