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TU Berlin

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Research

Expertise
The modeling of pioneering power and energy system concepts that are characterized by sustainability, economics, and robustness is at the heart of our research. In particular, we open up forward-looking solutions for the integration of renewable energy and storage in local as well as global network and market structures. As the underlying fundamental paradigms, we develop and discover ground-breaking methodologies of simulation and optimization for the planning as well as operation of integrative energy systems.


Optimization of networks with renewable energy and storage
Network infrastructures have traditionally been dominated by large power plants with controllable output. For the large-scale integration of intermittent renewable energy sources, we research system-wide storage concepts. In this context, we also illustrate the technical as well as economic feasibility.

Cache-storage in power systems
In computer engineering, cache storage is known for its critical role of fast and intermediate storage of data. We demonstrate how this concept can also be applied to the fast and intermediate storage of energy. It so can play a vital role of system integration in power and energy networks - in analogy to computer engineering.

Non-sampling stochastic network modeling
We have pioneered the use of polynomial chaos for representing uncertainties in networks and so eliminated the need for computationally expensive Monte Carlo sampling. In particular when there are few independent random inputs such as the temperature, we observe a dramatic increase in simulation speed.

Multi-scale modeling of networks
As of today, diverse methods are used for the purpose of modeling power electric networks. The selection depends on whether low-frequency electromechanical power oscillations between power plants or high-frequency electromagnetic transients such as traveling waves are considered. During blackouts, both phenomena can appear, thus evidencing the importance of modeling than can bridge multiple time scales.

With our method FAST (Frequency Adaptive Simulation of Transients), this is made possible in that the shift frequency is introduced as a novel simulation parameter in addition to the time-step size. The Fourier spectrum is then shifted depending on whether the instantaneous values or the envelopes of alternating quantities are of interest. A scale-bridging very fast and accurate simulation process is so attained.

Benchmarking of distributed energy systems
The decentralized organization of power systems is of increasing significance. Together with CIGRE (International Council on Large Electric Systems) we develop test networks that allow for a targeted benchmarking and so answer the questions on the best-suited technology.

Optimal horizon planning of distribution networks
What does the optimal distribution network of the future look like? Based on estimates of fundamental quantities such as the load behavior and population density, we design the optimal solution and its phased implementation.

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