Session description:
This is a hands-on tutorial, which will demonstrate how an open source gas transport network data set can be generated from different online sources. In the following, the necessary steps to unify data sets of different copyright protection levels are discussed. Hence we will introduce and demonstrate some of the tools, that allow the user to get access to the opendata and the copyrighted data, combine the data sources and use such data for their projects.
Hence the tutorial will start off with the introduction of the SciGRID_gas project, its aims and anticipated goals. This is followed by the introduction of the Non-OSM data sets in conjunction with the OSM data set. Then, several non-OSM data sources will be introduced and the following toolset will be introduced as part of the hands-on tutorial part:
- Using the (freely) open data supplied through the SciGRID_gas project
- Introduction of the copyrighted data sets and their web-location, and some background on the copyright legislation
- Demonstration of the tools generated on how to access copyright protected data sets (hands-on)
- Introduction to the processes and tools that combine above data sets and generate a single gas network data set (hands-on)
- Introduction to some of the methods used to fill data gaps (hands-on)
All information and data sets required for this tutorial will be supplied, in addition to the tools that have been written in Python. Hence limited Python coding is required by the participants, and each participant will need to bring their own computer, on which a Python version of 3.6 or higher is ready for use.
The participants should gain some knowledge on the available gas network data sets, how to access and combine them, and will generate their own data set of a gas transport network, to use in their own models later on.
Please note that, the modeling of gas transport throughout Europe is currently NOT part of this tutorial.
Background:
Models of the Europe gas transport are required for many tasks including, planning processes, case scenarios, model the gas consumption, minimize leaks and optimize overall gas distribution strategies. However, most of the data that is required for such models are not accessible, as they may contain sensitive operational data. Some of the data that is available is copyright protected. In addition, most of the European transport network is buried under ground, hence little is observable and hence such information is sparse in the OSM data bases, such as actual pathways of the pipelines, pipeline diameter, compressor power, or LNG terminal re-gasification capacities. However, this data is required to model the gas-transport throughout Europe. The SciGRID_gas project, funded by the BiWE is developing tools, that can be used to generate a complete gas transport network data set, containing information on:
- gas pipelines
- compressor stations
- LNG terminals
- gas storages
- gas productions
- gas import
- large scale gas consumption.
Part of the tutorial will be the introduction of each of the components and their attributes, as they will allow or limit the use of the data for future model simulations.
Aim:
The aim of the tutorial will be:
- Introduction to SciGRID_gas project: what, who, why, who for, when …
- Hands-on introduction to data sources: where, how to get it, what are limitations
- Hands-on introduction on combining data from different sources: using supplied Python tools to generate a single gas network
- Hands-on introduction on generating missing attribute values using supplied Python tools
Would you like to be responsible for the session:
Yes
Do you need any special infrastructure for this session?
Yes:
- Projector
- Room for ~20 people
- Participants need to bring their own laptop (with USB port), Python installed, and ~10 GB free disk space
- Prior to the tutorial a test version of SciGRID_gas will be available, to iron out any computer system operating problems
Do you have any recommendations who could be part of this session?
Anyone wanting to learn how to use the SciGRID_gas data set in the future?
Anyone wanting to give us feedback on the progress/data/… so far