This late winter/early spring release comprises some new features like minimum up- and downtime constraints and some new functions for the processing of results. Some bug fixes and improvements keep oemof functional and up-to-date.
Checkout the ‘What’s new’ section of the actual documentation for more detailed information.
With this release the pyomo issue is fixed. Please upgrade oemof to bring everything in line (see below for v0.1.x and v0.2.x). Continue reading “Gambling Generator – v0.2.1”
We added a new oemof repository aiming at collecting all kinds of examples on how to use oemof and its various libraries. You are welcome to help us fill the new repo by contributing your example via a pull request or by sending us an e-mail (see here for contact information).
The winter is gone, spring cleaning is done and we come up with a new release…
A revision of the installation guidelines and the examples will make it easier for new users to enter the world of oemof. Additionally, some new features have been imlemented besides a cleaned up code base:
Continue reading “The oemof springtime release (v0.1.2)”
A new version of the oemof database extension package oemof.db is now available.
This week, the first version of the oemof-application renpassG!S has been released!
renpassG!S is an easy-to-use application designed to model the cost-minimal dispatch of energy supply systems. Technically speaking, it is a so-called numerical partial equilibrium model of a liberalised electricity market often referred to as fundamental model.
More information and some screenshots of possible outcomes can be found here: https://github.com/znes/renpass_gis
With the new release of the feedinlib v0.0.11 all wind power calculations have been moved from the feedinlib to the new windpowerlib. We made this move in order to build a wind power modeller community similar to the pvlib. So check out and join the new windpowerlib!
We proudly present the totally revised version of oemof!
Now oemof is more flexible, better documented and ready to join for new contributors and users.
The framework provides the basis for a great range of different energy system model types, ranging from LP bottom-up (power and heat) economic dispatch models with optional investment to MILP operational unit commitment models.
Continue reading “The great revision”
We achieved to goals with this updated demandlib version
- Versioning scheme is corrected
- Demandlib works when installed via pip without appending paths to PYTHONPATH