Applying data analytics on multiple data sources to better understand Transmission System Operators (TSO’s) challenge to maintain a stable grid frequency.
This innovation project is part of DNV GL’s (and Statnett’s) strategic roadmap towards improving data-smartness and better understanding how to handle and analyse new, big and distributed data sources in advanced analytic tools with the ultimate goal in mind to improve operation of the power grid. The project has also been part of Optique’s Partner Program as a Pilot partner.
The scope of the project was to build experience on information governance techniques such as data quality management, data processing, data correlation and data visualisation using a number of data analytics tools. In this project we have applied the IEC Common Information Model (CIM) ontology, which is widely used in the electrical power industry. IEC CIM describes many aspects of the electrical assets and the operation of the electrical grid. The analytics platforms that have been used in the project are:
- The Optique platform. Optique is an EU-funded research project and a software platform aiming at exploiting recent advances in semantic technologies.
- The DNV GL Strategic Research and Innovation Hadoop cluster platform (Blitz).
- Information Workbench from FluidOps.
In the project, we zoomed in on any TSO’s challenge to maintain a stable power grid frequency of 50 Hz. This 50 Hz frequency is impacted by an imbalance in load and consumption in the power network The project looked at what the impact could be of an inaccurate weather forecast on the variances in the 50 Hz power frequency.
This research question is relevant for any TSO, and has resulted in the interest of Statnett, who is together with the other TSO in the Nordic responsible for the Nordic frequency zone. The project has brought the following results:
- Hands on experience of big data solutions from several vendors and the challenges of information governance and usage of multiple distributed and big data sources.
- Improved understanding of challenges of using the power sector Common Information Model as basis for integrating multiple data sources.
- Understanding of risk and opportunities in big data projects.
The project experience has given Energy Advisory Scandinavia, DNV GL Netherlands and Statnett a large push forward on topics like big data, data analytics, common information model, digitalization and becoming data smart.
DNV GL: Theo Borst and Per Myrseth
Optique project: Tore Hartvigsen (DNV GL)