Skip to content
The application renpassG!S stands for (r)enewable (en)ergy (pa)thway (s)imulation (s)ystem capable of working with data from geographic information systems (GIS). It is based on the original idea of renpass and closely linked to the Open Energy Modelling Framework (oemof).
Python
Branch: master
Clone or download
Pull request Compare This branch is 178 commits behind znes:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
documents
.gitignore
LICENSE
README.rst
renpass_gis_main.py

README.rst

The application renpassG!S stands for (r)enewable (en)ergy (pa)thway (s)imulation (s)ystem capable of working with data from geographic information systems (GIS). It is based on the original idea of renpass and closely linked to the Open Energy Modelling Framework (oemof).

This documentation is meant to explain the basic functionality and is structured as follows:

1   Overview

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. Making use of the broad functionality of oemof, the application enables the user to calculate easy-to-understand energy system scenarios for different regions in spreadsheet format (CSV), optimizing the power plant dispatch at minimum costs. Results are exported into spreadsheet format as well an can be easily accessed using suitable software such as LibreOffice Calc or Microsoft Excel.

The general functionality can be derived from the following figure:

renpassG!S model model overview

Currently, it is developed and maintained at the Center for Sustainable Energy Systems (Zentrum für nachhaltige Energysysteme (ZNES)) in Flensburg. As there are currently some licensing issues concerning the scenario data, this repository only provides the application code. For questions on the data, you can use our contact details below.

2   Application Examples

The model has been used in different research projects. One application was to model future scenarios of the power plant dispatch and day-ahead market price formation in Germany and its interconnected neighbor countries based on operational and marginal costs and the assumption of an inflexible electricity demand. The following figures show some impressions of possible outcomes.

2.1   Hourly power plant dispatch for a week in January

power plant dispatch

2.2   Day-ahead market price formation for a week in May/June

wholesale market price formation

2.3   Annual production per energy carrier for two selected scenarios

annual production

2.4   Diurnal pumped-storage dispatch in Norway for a selected scenario

pump

Currently, a similar spin-off model is adapted to the requirements of the Middle East and North Africa (MENA) region to model possible pathways for the future electricity generation based on a high share of renewables.

3   Installation

renpassG!S is build within oemof and works with the current stable version (v.0.1). Please follow the installation guidelines in the documentation.

If oemof has been installed successfully (including a suitable solver), the application can be run from the directory. Just clone this repository using:

git clone https://github.com/znes/renpass_gis.git

4   Usage

Energy supply systems can be modelled via oemof's csv-reader functionality. There are two examples on how to use it provided in the oemof example folder.

Once the energy supply systems have been modelled, the application script can be run from the command line:

General usage:

renpass_gis_main.py [options] NODE_DATA SEQ_DATA

Getting help:

renpass_gis_main.py -h

Example usage with another solver (standard is CBC):

renpass_gis_main.py -o gurobi path/to/scenario.csv path/to/scenario-seq.csv

Per default, all result files are written back into the subfolder results.

5   Contribution

We adhere strictly to the oemof developer rules. For any questions concerning the contribution, you can use our contact details below.

6   Contact

If you have any questions or want to contribute, feel free to contact us!

For questions, bugs, or possible improvements please create an issue.

For all other concerns, please write us an e-mail:

  • Cord Kaldemeyer (Flensburg University of Applied Sciences): <cord.kaldemeyer(at)hs-flensburg.de>
  • Martin Söthe (University of Flensburg): <martin.soethe(at)uni-flensburg.de>

7   Credits

Oemof and renpassG!S are community projects and have been realised in collaborative work. We therefore thank all people who contributed to the framework and the scenario development, and in particular the following people for their contributions to this first version of renpassG!S:

  • Simon Hilpert and Uwe Krien for the effort they put in the oemof-refactoring
  • Wolf-Dieter Bunke and Marion Christ for the initial scenario development
  • Clemens Wingenbach and Stephan Günther for providing the prior version
  • Frauke Wiese and Gesine Bökenkamp for creating renpass
  • All people at the Center for Sustainable Energy Systems (ZNES) Flensburg

8   Citation

We have an entry in the Open Science Network which can be used.

9   Publication

Boysen, Cnythia; Grotlüschen, Heike; Großer, Hauke; Kaldemeyer, Cord; Tuschy, Ilja ( 2017 ) Druckluftspeicherkraftwerk Schleswig-Holstein - Untersuchung zur Eignung Schleswig-Holsteins als Modellstandort für die Energiewende. Nr. 5 der Reihe Forschungsergebnisse des ZNES Flensburg (elektronisch: ISSN 2196-7164 / Print: ISSN 2195-4925) Download

Ulf Philipp Mueller, Lukas Wienholt, David Kleinhans, IlkaCussmann, Wolf-Dieter Bunke , Guido Pleßmann and Jochen Wendiggensen (2017) The eGo grid model: An open source approach towards a model of German high and extra-high voltage power grids. SciGRID International Conference on Power Grid Modelling (submitted)

Becker, Liv; Bunke, Wolf-Dieter; Christ, Marion; Degel, Melanie; Grünert, Judith; Söthe, Martin; Wiese, Frauke; Wingenbach, Clemens (2016) VerNetzen: Sozial-ökologische und technisch-ökonomische Modellierung von Entwicklungspfaden der Energiewende. der Reihe Forschungsergebnisse des ZNES Flensburg (elektronisch: ISSN 2196-7164) Download

Berg, Marina, Bohm, Sönke, Fink, Thomas, Hauser, Muriel, & Komendantova, Nadejda (2016). Summary of workshop results: Scenario development and multi-criteria analysis for Morocco's future electricity system in 2050. Bonn. Download

You can’t perform that action at this time.