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Master theses

Decomposition Methods for Energy System Optimization

Ansprechpartner: Christopher Ripp, Frühester Beginn: sofort

Decomposition Methods for Energy System Optimization

Ansprechpartner: Christopher Ripp, Frühester Beginn: sofort

EINS develops together with an industrial partner a tool to simulate and optimize future multi-modal energy systems. This is yields consistent master plans of the Energiewende that directly shape the political and economic discussions in the energy sector.
In this project the existing tool that is based on mixed-integer linear programming shall be modified to support the decomposition of the simulation / optimization work. This is necessary for large models, such as one that models all energy sectors in hourly resolution from now until 2050, which leads to very large problems (tens of millions of variables). For different general purpose decomposition approaches (Benders, Wolfe-Dantzig) it shall be examined how to optimally apply them to the problem, i.e. which splits are optimal. At least one algorithm shall be implemented in the existing framework and tested for its properties. Optimally, one could even develop problem- specific novel decomposition approaches.

Modern N-1: Estimating power systems' resilience w.r.t. a hacked HVDC line

Ansprechpartner: Johannes Börner, Frühester Beginn: sofort

Modern N-1: Estimating power systems' resilience w.r.t. a hacked HVDC line

Ansprechpartner: Johannes Börner, Frühester Beginn: sofort

Classical N-1 considers the random outage of any component in the power system. It guarantees that the system still runs smoothly in that case. What we call modern N-1 should also consider the intended misbehavior of any component. This is of ever greater importance as system become more and more digitalized and cyber attacks more common and professional. Of special importance for the power system ar HVDC lines due to their large capacity and their ability for fast and well-controllable dynamics.
The thesis should examine the different effects that a successful hacker of the controller of an HVDC line could produce. The thesis should work on a qualitative level and survey potential attack directions. It should also simulate the effects in a high time-resolution simulation of an exemplary two zone power system connected via an HVDC link. Of interest are both short term distortions such as (partial) blackouts but also the destruction of the underlying hardware, as this would have long term dangerous consequences.
The thesis should conclude with first indications how the most detrimental effects could be avoided.

Probabilistic modeling of e-car charging

Ansprechpartner: Tim Janke, Frühester Beginn: sofort

Probabilistic modeling of e-car charging

Ansprechpartner: Tim Janke, Frühester Beginn: sofort

Based on empirical data from an e-car charging station, the target is to develop and fit a probabilistic model for the power consumption of such a station. The model should be able describe both today's charging behavior as well as future situations, when the c-car density can be assumed to be much higher.
The intented use of such models is in energy management. Stochastic optimization routines can schedule flexible generation & consumption in accordance with the current and predicted charging demand. A description of the variance of the charging demand also gives rise to system optimization, i.e. determining how many charging stations to combine or which electrical flexibility options to integrate to offset varaibility. First steps in this directions should be undertaken.

Reconstructing Power Wholesale Market Prices from Operational Data

Ansprechpartner: Christopher Ripp, Frühester Beginn: sofort

Reconstructing Power Wholesale Market Prices from Operational Data

Ansprechpartner: Christopher Ripp, Frühester Beginn: sofort

This project aims at understanding in detail how prices at the day-ahead power markets arise, given the technical behavior of all relevant participants is known. This in an important ingredient for modeling future power systems and thus optimizing the course of the Energiewende.
Since 2016 the operational schedules of all large power plants in Europe are published on an hourly basis. Given their cost structure and a description of the demand and the renewable infeed it should then be possible to explain the observed power market prices. A straight-forward approach to this problem, however, does not yield satisfying results, an important factor being that it is not clear how to distribute long-term cost components onto individual hours.
The project will test and develop different models how to derive the true market prices given the real operation and fixed cost parameters for each power plant.
(source: Wikipedia)

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