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PhD thesis ‘Optimal demand flexibility- and criticality-based power distribution in smart grids preventing critical network states’


Institut für Thermische Energietechnik und Sicherheit (ITES)


The energy transition plays a key role in achieving sustainability goals. However, the transformation of the energy system towards a supply, based on renewables is accompanied by new risks and uncertainties: volatility of electricity generation, new power-consuming technologies, new vulnerabilities of a digitalized energy system etc. For sustainable energy systems to be future-proof, they must be able to adapt to critical situations, caused by power shortages or overloaded grids, in a very short time. At KIT, within the research topic ‘System and Sustainability’ and the Helmholtz Energy Program ‘Energy System Design’ innovative and smart concepts for sustainable, resilient and adaptive energy system designs are developed in an interdisciplinary setting.

The context of this PhD thesis is power system stabilization against the scenario of power shortage or overload of the grid. To stabilize a power grid and avoid outages, a new concept for resilient management exists that assumes the presence of a smart metering infrastructure and takes into account demand flexibility of electricity customers and their system criticality. In times of acute power shortage or power grid overload, the supply may be ramped down to a reduced state in an organized manner, effectively avoiding network problems – the probability of outage and black start would be significantly reduced, thus, making the energy system more resilient. For this concept to be applicable in smart distribution grids, globally optimal solutions for a large number of electricity customers (several thousands) in conjunction with non-convex functions involving AC power flows, need to be computed on a sub-minute scale.
Referring to that concept, the main goal of this work is to develop an optimization algorithm for different smart grid configurations to compute a theoretical active power value per electricity customer minimally reduced compared to the normal demand, which would guarantee a maximum stable AC power flow below normal operation.



Persönliche Qualifikation

You have a master's degree (or equivalent) in mathematics, informatics, natural or engineering sciences and are interested in optimization and complex challenges of the energy transition. Experience in mathematical optimization and programming is required. Knowledge in non-convex optimization and AC-optimal power flow is an advantage. The position offers the opportunity to obtain a doctorate Dr. rer. pol. or Dr.-Ing..

Contract duration

limited to 3 years

Application up to


Contact person in line-management

For further information, please contact Dr. Sadeeb Simon Ottenburger, phone +49 721 608-25507.

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Karlsruher Institut für Technologie (KIT)
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