open source data and models for a sustainable power grid modelling and analysis · 2017. 9. 17. ·...

DLR Institute of Networked Energy Systems

DLR.de/VE • Chart 1

Open Source Data and Models for a Sustainable Power Grid Modelling and Analysis Dr. Wided Medjroubi, Dr. Thomas Vogt

08 August 2017

International Conference on Large-Scale Grid Integration of Renewable Energy in India

> Grid Integration > Medjroubi • SciGRID > 8.8.2017


Outline


• Motivation • The SciGRID project • OpenStreetMap • Power Data in OpenStreetMap • Results & Applications the SciGRID:

− Germany − India

• Conclusion & Outlook


Motivation


• Lack of models and (geo-referenced) data of the power (transmission) network

• Restrictive, no-clear license terms of “available” datasets

• Little information available on how network models are derived: − Data sources and quality − Aggregation methods − Simplifications and assumptions − Data parameters (ex. Electrical properties)

• Difficulty validating and/or comparing modelling results

• Restrictive (re)-use of models and data (ex. publication, sharing, cooperation)

• The process of collecting data is “endlessly” repeated


SciGRID Project


• SciGRID: Open Source Reference Model of European Transmission Networks for Scientific Analysis − Individual project supported by BMBF (10/2014 - 09/2017)

• Motivation: − Providing robust open data and models of the European transmission power grid for

the energy research community

• Objectives: − Development of an open source model − Providing data, tools and documentation − Directed towards scientific analysis


What is OpenStreetMap?


• A voluntary map of the world

• Founded in 2004 in the UK by S. Cost

• The most extensive geo-database in the world

• Includes geo-referenced objects and their features (XML-Format)

• Freely accessible under the Open Database Licence (ODbL)

• Open source tools to download and process data are available


Data Structure in OpenStreetMap


node way relation

<-tags-> <-tags->


Data Structure in OpenStreetMap


node way relation 2...2000


Power Transmission Datasets in OSM


node way relation

node id = 724245909 lat = 51.8898354 lon = 14.4283962 power = tower user=* timestamp=* ...

2...2000

Source: Fotolia / Erwin Wodicka, 2012




node way relation


way id = 58417796 nd ref = 724245909 … power = line user = * timestamp = * ...

2...2000

Source: Pitopia / Pehuka, 2013 Source: Fotolia / Erwin Wodicka, 2012




node way relation


way id = 58417796 nd ref = 724245909 … power = line user = * timestamp = * ...

relation id 1560977 Member type=way id=58417796 role=line ... route = power user = * timestamp = * ...

2...2000

Source: Pitopia / Pehuka, 2013 Source: Fotolia / Erwin Wodicka, 2012 Source: www.wikipedia.org


Overview of the SciGRID Model


Relational databank Model source-code and data

Model and data documentation

Geo-boundaries

openstreetmap.org raw data

• Characterization of (power) network models • Validation of the SciGRID model and data • Conversion tools to power flow tools

OSM-raw data post-processing

Derivation of power network

Power network abstraction

Definition of model simplifications

Power network visualization


SciGRID Project Results


• Project results − Open source reference model

including the source code − Technical documentation − Converters to power flow simulation

software (PYPSA, PyPOWER, MATPOWER)

− Validation and verification − Scientific publications − International scientific conference

2017

• Project web-page

http://www.scigrid.de

• Example applications/studies − Characterization of the German

transmission network

− Network comparison tool

https://www.pypsa.org/

https://pypi.python.org/pypi/PYPOWER

http://www.pserc.cornell.edu/matpower/

http://www.scigrid.de/


SciGRID Model: Germany


• Data timestamp: 18.07.2017


SciGRID Model: India


• Data timestamp: 18.07.2017


Source: Matke, et al. "Structure Analysis of the German Transmission Network Using the Open Source Model SciGRID." Advances in Energy System Optimization. Birkhäuser, Cham, . 177-188 (2017).

Application Example: „Characterization of the German Transmission Network using SciGRID Datasets“


• Derivation of the German transmission network − 454 nodes and 826 lines

• Computation of structural properties

• Comparison with the US network − 4941 nodes and 6594 lines

Decomposition of the German network into 13 clusters after removing links with highest betweeness centrality.

Modularity and rescaled nb of clusters as a function of removed links.


Application Example: „Heuristic Modelling of Transmission Networks: GridKit“


• Lack of relations data coverage for Europe

• Heuristic approach in modelling transmission networks − GridKit DE: 1849 (454) nodes, 2166 (826) lines

• Extension of SciGRID to EU countries

Comparison of the SciGRID and GridKit transmission network for Germany.

Example of simplification in GridKit.

GridKit network topology for the French transmission network compared to ENTSO-E map.

Modelling approach in GridKit. Source: B. Wiegmans, Master Thesis (2015).

https://github.com/bdw/GridKit

http://www.scigrid.de/


Application Example: „Automated Comparison Tool for Transmission Network Datasets: AutoGridComp“


• Comparison and characterization of power grid datasets − Towards validating open source power network datasets

• Influence of model derivation on resulting model topology

• Offers 3 characterization “layers”

AutoGridComp characterization of power networks.

Vertices with highest clustering coefficient for SciGRID and GridKit datasets.

Graphical interface of the AutoGridComp plugin.

Source: W. Heittkötter, Master Thesis (2017).


• New challenges in the energy sector due to increasing shares of RES

• Energy modelling and analysis in general and power grid modelling in particular are necessary and need to be transparent

• Increasing importance of detailed modelling transmission networks

• Reliable, transparent and open models and data of transmission networks needed BUT access to existing models and data is restricted

• Heuristic approach in modelling transmission networks

• SciGRID: based on free and open source OpenStreetMap data and models, offers new possibilities

• SciGRID: applied to India is promising as OpenStreetMap power dataset is available

Conclusion



• How to apply SciGRID to India? − Characterization of the OpenStreetMap power datasets − Cleaning, correcting and enhancing OpenStreetMap power datasets − Encourage mapping of power elements and features in OpenStreetMap − Adapting the algorithms and tools to the specificities of the Indian transmission network

Outlook



Thank you for your attention


open source data and models for a sustainable power grid modelling and analysis · 2017. 9. 17. ·...

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