ficus: A (mixed integer) linear optimisation model for local energy systems¶
|Maintainer:||Dennis Atabay, <email@example.com>|
|Organization:||Institute for Energy Economy and Application Technology, Technische Universität München|
|Date:||Jan 31, 2018|
|Copyright:||This documentation is licensed under a Creative Commons Attribution 4.0 International license.|
- ficus is a (mixed integer) linear programming model for multi-commodity energy systems.
- It finds the minimum cost energy system to satisfy given demand time-series for possibly multiple commodities (e.g. electricity, heat)
- It considers given cost time-series for external obtained commodities as well as peak demand charges with configurable timebase for each commodity
- It allows to deactivate specific equations, so the model becomes a linear programming model without integer variables
- It supports multiple-input and multiple-output energy conversion technologies with load dependent efficiencies
- ficus includes reporting and plotting functions
If you don’t already have an existing Python I recommend using the Python distribution Anaconda. It contains all needed packages except Pyomo.
- Anaconda (Python 2.7 or Python 3.5). Choose the 64-bit installer if possible. During the installation procedure, keep both checkboxes “modify PATH” and “register Python” selected!
- Pyomo (pip install pyomo)
- download or clone (with git) this repository to a directory of your choice.
- Copy the
ficus.pyfile to a directory which is already in python’s search path or add the
pythonfolder to python’s search path (sys.path) (how to)
- Install a solver (optional).
Pyomo allows using the NEOS Server for Optimization for solving, so it is not required to install a solver.
I still recommend to install and use one of the following solvers.
This is a typical result plot created by
ficus.plot_timeseries(), showing electricity
generation and consumption over 7 days: