MILP energy modeling framework - https://infoscience.epfl.ch/record/231814
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README.md
ses_main.dat
ses_main.mod

README.md

Copyright notice

Everything contained in this directory and its subdirectories is the property of the Industrial Process and Energy Systems Engineering (IPESE) group, École Polytechnique Fédérale de Lausanne (EPFL).
This program is distributed "as is" and WITHOUT ANY WARRANTY, either expressed or implied, without even the implied warranties of merchantability or fitness for a particular purpose.
You can freely use, modify and adapt the code, as long as you comply with the following restrictions.

The restrictions are that:
(i) In the academic spirit of collaboration, the source code should be appropriately acknowledged in the resulting scientific disseminations.
You may cite it as follows:

  • [1], for reference to the Swiss-EnergyScope project or the online version of the calculator energyscope.ch
  • [2], for reference to the MILP modeling framework
  • [3], for reference to the MILP modeling framework and the data for the application to the Swiss energy system

(ii) the recipient agrees to publicly share further developments of the source code, under the same restrictions. This means that no commercial product can be developed using this code. Opportunities for commercial applications may be discussed with the owner of the code.

You are welcome to report any bugs related to the code to the following:
moret.stefano@gmail.com

Copyright IPESE, EPFL, Lausanne, Switzerland.
October 27, 2017

Content

This folder contains the Swiss-EnergyScope (SES) MILP model.
The version of the model corresponds to the one documented in [4], Chapter 1.
The data used in the model are fully documented in [4], Appendix A.

How to run the model

The model is coded in GLPK, using the open-source solver GLPSOL. To run the model, perform the following 4 steps:

  1. Install GLPK:

a) on Mac OS X (Option 1, recommended): use homebrew http://arnab-deka.com/posts/2010/02/installing-glpk-on-a-mac/

b) on Mac Os X (Option 2)/Linux:

$ cd ~/Downloads
$ tar -xzf glpk-4.63.tar.gz
$ cd glpk-4.63 [or newer version]
$ ./configure --prefix=/usr/local
$ make
$ sudo make install

See if your system recognises it:

$ which glpsol

should reveal:

$ /usr/local/bin/glpsol

Now try:

$ glpsol --help

Source: http://hichenwang.blogspot.ch/2011/08/fw-installing-glpk-on-mac.html

c) on Windows:

  • Download the source files from: https://sourceforge.net/projects/winglpk/files/latest/download
  • Extract the files in a folder. Depending on your operating system use glpsol.exe from: ./w64 if running on a 64 bit version ./w32 if running on a 64 bit version
  • For facilitating the access to glpsol.exe you can add the full path (depending on your operating system, see below) from the previous point to the system variables PATH
  1. Clone/download the content of this folder
  2. Navigate to that folder via terminal/cmd prompt and execute (check glpsol documentation for more options):

$ glpsol -m ses_main.mod -d ses_main.dat -o ses_main.out (You might need to use 'glspol.exe' on Windows)

  1. Check that the ses_main.out file is correctly generated.

If the command at point (3) did not run, it might be that glpsol is not on your PATH. Two solutions for that:

The model was originally developed in AMPL. Compatible solvers are CPLEX, Gurobi, etc. Running the model in AMPL requires the licences of AMPL and of at least one MILP solver.

References:
[1] V. Codina Gironès, S. Moret, F. Maréchal, D. Favrat (2015). Strategic energy planning for large-scale energy systems: A modelling framework to aid decision-making. Energy, 90(PA1), 173–186. https://doi.org/10.1016/j.energy.2015.06.008
[2] S. Moret, M. Bierlaire, F. Maréchal (2016). Strategic Energy Planning under Uncertainty: a Mixed-Integer Linear Programming Modeling Framework for Large-Scale Energy Systems. https://doi.org/10.1016/B978-0-444-63428-3.50321-0
[3] S. Moret, V. Codina Gironès, M. Bierlaire, F. Maréchal (2017). Characterization of input uncertainties in strategic energy planning models. Applied Energy 202, 597–617. https://doi.org/10.1016/j.apenergy.2017.05.106
[4] S. Moret (2017). Strategic Energy Planning under Uncertainty. PhD Thesis n. 7961, EPFL, Switzerland. http://dx.doi.org/10.5075/epfl-thesis-7961