Welcome to gep_onsset User’s Guide!

gep_onsset

gep_onsset is a modified version of OnSSET model, openly distributed as gep-onsset.. It was developed to support the functionalities of the Global electrification Platform. The package is available at pypi but installation is also possible through github.

Note

This user guide is currently under development. Fully-fledged documentation over the use of gep_onsset will become available later in 2019. In the meantime feel free to take sneak peek of similar supporting material here.

Contents

Overview

Installation

Requirements

gep_onsset requires Python >= 3.5 with the following packages installed:

  • et-xmlfile>=1.0
  • jdcal>=1.4
  • numpy>=1.16
  • openpyxl>=2.6
  • pandas>=0.24
  • python-dateutil>=2.8
  • pytz==2019.1
  • six>=1.12
  • xlrd>=1.2

Install with pip

` python -m pip install -i https://test.pypi.org/simple/ gep-onsset `

Install from GitHub

Download or clone the repository and install the required packages (preferably in a virtual environment):

` git clone https://github.com/global-electrification-platform/gep-onsset.git `

` cd gep-onsset `

` pip install -r requirements.txt `

Note

The use of GEP generator requires also installation of

  • IPython
  • jupyter
  • matplotlib
  • seaborn

Supporting Methods & Tools

The Open Source Spatial Electrification Tool (OnSSET)

gep_onsset code is a modified version of the OnSSET model, accustomed to serve the Global Electrificatio platform. The methodology behind the model is available in a peer-reviewed academic publication available online since April 2019.

Q-GIS plug-in for developing population clusters

The identification of population settlements is the basis of the electrification analysis in many models. gep_onsset requires that population settlements are represented as vector clusters. KTH dESA has developed a methodology for generating such vector clusters based on open access data. The output dataset is openly accessible. Furthermore, an open source Q-GIS plug-in.

Note

The above methodology requires processing in Q-GIS (an open-source GIS software).

Q-GIS plug-in for extracting GIS information to vector clusters

Geospatial electrification models are inextricably connected with GIS data. Extracting geospatial information to each vector cluster (see above), is therefore a necessary yet time consuming process. The extraction commands can be executed manually in QGIS; however, the KTH team has developed a Q-GIS plugin in order to automate the process.

Note

In order to run succelfully run gep_onsset the vector clusters need to be attributed using 26 GIS layers. An extensive list of those together with open access sources is available here.

Training material

Training material related to the use of gep_onsset package are available on Google’s Open Online Education platform.

Contact

You can send inquiries and feedback at seap@desa.kth.se.

Review and/or add your questions on our Forum.

Meet the team here.

License

MIT License

Copyright (c) 2019 The division of Energy Systems Analysis at KTH

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.