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Tim Pfüller M.Sc.

Working area(s)

Time Series-Based Probabilistic Load Flow Calculations in the Distribution Grid

Contact

work +49 6151 16-24666
fax +49 6151 16-24665

Work S3|10 207
Landgraf-Georg-Straße 4
64283 Darmstadt

“I completed my studies in Sustainable Electric Power Supply at the University of Stuttgart, specializing in electrical power grids and grid integration of renewable energies.

During my studies, I was already particularly interested in the field of electrical energy grids, which is why my master's thesis dealt with the modelling of 380-kV-transformers for probabilistic load flow calculations in the 110 kV grid.

Since October 2016, I have been working for Syna GmbH in Frankfurt. After the successful completion of the trainee program in Asset Management High Voltage I was employed as a project manager in Digital Systems Engineering. There, I was able to improve my knowledge in the field of secondary and grid protection technology. Since 2019, I have been working as a grid engineer in the field of high-voltage grid development planning. In this context, I am involved in the further development of the 110 kV grid of Syna GmbH in Frankfurt.”

“As a result of the energy turnaround and the ever-increasing proportion of volatile producers and consumers, energy suppliers and in particular grid operators are faced with the major challenge of planning their grids to be future-proof. The current planning approaches of the conventional approach with deterministic load scenarios do not take this volatility sufficiently into account and thus bear the risk of wrong dimensioning of electric circuits.

My research focus is on time series-based probabilistic load flow calculations with the aim of future-proof dimensioning of distribution grids and to promote grid expansion only where it is really necessary. The possibility of determining the probability of occurrence and its duration offers completely new insights and possibilities in grid planning. The knowledge gained from the past can be used in conjunction with future forecasts for various scenarios to create a new planning tool and thus drive forward grid expansion planning in line with requirements.”