September 03 - September 14, 2018, University of Oldenburg, Germany

Due to the finiteness of fossil energy sources and the ongoing climate change many countries begin to cover their energy needs with renewable energies. The production of solar and wind energy is increasing worldwide and can even be cheaper than classical energy production, in particular if taking into account secondary costs.

Switching to the use of regenerative energies still requires many advances in technical areas. This includes improving the efficiency of power generation, e.g. for solar cells or wind turbines, and of energy storage. On larger scales, the layout and positioning of wind farms and the capacity and stability of power networks have to be optimized. In the field of energy production control, the analysis and forecasting of the weather also plays a big role, e.g. for the situational activation of conventional backup power plants.

In all these applied areas computer simulations and the analysis of large amounts of data play a prominent role and require the use of computers. The aim of summer school Modern Computational Science: Energy of the Future is therefore the professional training of the participants in the highly topical research field of "Renewable Energies". During the summer school, the essential numerical approaches in this area will be taught in theory and practised in extensive exercise sessions. Topic from all areas will be included, starting with stochastic algorithms and the fundamentals of partial differential equations up to the modeling of networks and fluid dynamically simulations. This very fundamental approach, which places a strong focus on the teaching of (advanced) basic knowledge and practical computer experience is a special characteristics of the MCS Summer Schools.


During the MCS Summer School participants will review and deepen their understanding of basic theory and methods of Computational Science. In addition, specialized topics in different areas of the research field "Energy of the Future" will be covered. Subjects of the Summer School include (but are not limited to):

  • Fundamentals: high-performance computing, data analysis, Monte-Carlo simulations, differential equations, networks
  • Energy Simulations: computational fluid dynamics, energy networks, collective dynamcis of power grids, analysis of wind data, short-term weather prediction

Participants of MCS Summer School 2018 in Oldenburg

‚Personal experiences gained‘

by Poorana Kumar Seethapathy, India (EUREC 2010/11)

With experience in the field of Wind project development, I was pretty often exposed to situations that demanded computations. The applications in fields such as data analysis, curve fitting, uncertainty analysis, wind power forecasting, wind flow modelling and so on were very relevant to my work and therefore made be very inquisitive. The summer school on Modern Computational Science at the University of Oldenburg was a right choice for me since it combined theory and practice which is not common in other similar summer schools. I thoroughly enjoyed the lectures from professors, researchers and experts in this field and this of course gave me new perspectives. The program had various social activities as well which helped me getting to know the other participants. Interesting feature of the summer school was the rich mixture of participants from different countries, different backgrounds and different goals. The organization of the program was very good with facilities such as free transport in Oldenburg, free food in the canteen and free coffee and cookies. The program gave me a good overview of the recent trends in computational science with a special focus on the applications in the field of Renewable Energy. If I should describe the whole program in three words, I would say: Informative, Diverse and Fun. Thank you so much Prof. Dr. Alexander K. Hartmann and Dr. Stefan Harfst for arranging this and I would suggest this summer school for physicists, mathematicians, engineers and anyone who is interested in Computational science.

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