DGOPT
ikki407/DGOPT - Flexible Optimization Project of DG Allocation Problem, written in Python.
Description
Two-stage stochastic programming is used to formulate an allocation problem of distributed generation(DG).
DGOPT helps to perform numerical simulations under various conditions.
User can set and change any parameters, which include distribution systems, demand & weather data, system conditions, costs, and more.
DGOPT has mainly used Pyomo, which provides an effective framework for stochastic programming.
Environment
Linux or Mac OS/X
Python 2.7
Gurobi 7.0.0 (or 6.5.0)
Install
This library is recommended to be installed by using virtualenv, but if you do not use virtualenv, just type git clone.
git clone git@github.com:ikki407/DGOPT.git
Virtualenv (Recommended)
Make virtual environment.
mkvirtualenv DGOPT
Then, work on workon DGOPT and move to the root directory of virtualenv cdvirtualenv and clone DGOPT.
git clone git@github.com:ikki407/DGOPT.git
Requirement
Move to DGOPT directory, and type,
pip install -r requirements.txt
Remark
If you had a import problem of matplotlib under virtualenv, change the backend in matplotlibrc as follows:
backend : Tkagg
The path of your matplotlibrc can be found by
python -c "import matplotlib;print(matplotlib.matplotlib_fname())"
Usage
Optimization will start by running the following command in src directory.
sh all_run.sh
Files
ikki407/DGOPT/data - Directory for demand and weather data.
ikki407/DGOPT/src - Source directory.
ikki407/DGOPT/src/all_run.sh - Main source script.
ikki407/DGOPT/src/config - Directory for config files of general settings and parameters.
ikki407/DGOPT/src/concrete - Directory for concrete optimization models.
ikki407/DGOPT/src/scenario_generation - Directory for scripts of scenario generation.
ikki407/DGOPT/src/system_data - Directory for distribution system data.
ikki407/DGOPT/src/arrange.py - Script for arranging simulation results.
ikki407/DGOPT/src/postprocessing.py - Postprocessing script for summarizing all results.
Contribution
- Fork (https://github.com/ikki407/DGOPT/fork)
- Create your feature branch (git checkout -b my-new-feature)
- Commit your changes (git commit -am 'Add some feature')
- Push to the branch (git push origin my-new-feature)
- Create new Pull Request
If you had a problem or suggestion, please feel free to contact me.
Reference
[1]Pyomo