Data driven solutions- Photo:Torben Nielsen

Data-driven energy solutions

As in many other fields, more and more data are being collected and made available in relation to energy systems. Such data may be used for developing dedicated visualizations, hence allowing to raise awareness (e.g., related to availability of renewable energy, CO2 emissions, etc.), but also for optimizating operation of energy systems.

Data-driven energy solutions require the development of advanced mathematical methods that are able to deal with a large amount of data for both state estimation, prediction, optimization, etc.

Our research focuses on the proposal and validation of such approaches, from methodological development to application and validation based on real-world cases. In view of the quantity of data to be handled and of the complexity of the algorithms involved, emphasis is placed on the computational aspects for parallelization and optimal usage of high-performance computing capabilities.

Contact us for more information.

 

Selected examples:

HD-RESforecasts

renewable energy
Simultaneously predicting the production of large number of renewable energy generation sites.
energy market data
A large-scale dataset for medeling a highly renewable European electricity system.
DTU Electrical Engineering
View full list of research projects.

Pierre Pinson

Pierre Pinson
Professor
DTU Electrical Engineering
+45 45 25 35 41
http://www.cee.elektro.dtu.dk/research/Digital-energy-solutions/Data-driven-solutions
20 OCTOBER 2017