Power systems represent a fascinating and inspiring field of research in control engineering and science. Algorithmic and theoretical challenges resulting thereof feature rich dynamics and decision making architectures including networks, hierarchies, switching, hybridness, multi- and large scales, time-delay, state jumps, event-triggering, etc. Currently the chair is researching on flexibilities and implementation of ancillary services by means of control and systems theory.
Flexibilities enable a stable balance between electricity generation and electricity demand and thus ensure secure supply. They may be active accounting for flexible power plants that adapt their production to the electricity generated by wind power and photovoltaic systems, storage systems that can temporarily store the renewable electricity, and efficient electricity grids that can transport and distribute the electricity over large areas. Another resource of specific interest provide electric vehicles as mobile buffers, a rising topic in view of the emerging technology of bidirectional charging (BDL). Passive flexibilities, on the other hand, are addressed by demand-side management (DSM) or demand-side response. DSM refers to the control of electricity demand, especially in industry, through the targeted switching on and off of loads based on market signals. Adaptation of the production levels is another approach that can be done by controlling processes for which the use of electricity can be varied - for example in mills, furnaces or pumps.
The chair develops economic optimal and stochastic control algorithms that aggregate and deploy the passive and active flexibilities into the market. Such tools support companies with flexible processes to balance out fluctuations in electricity generation from renewable energies by marketing their services, for instance in form of operating reserve via the spot or/and intraday markets.
In the context of demand-side management the industry as a large consumer of energy is supposed to contribute to the stability of the power gird by adjusting their consumption according to the requirements of the grid. To compensate the costs of adjustments for the companies, financial rewards for the flexibilization are provided. The decision of a company to participate actively in the stabilization of the grid is usually based on economic considerations. Our research focuses on designing and implementing optimal predictive control algorithms, in hybrid, distributed and economic setting.
The electromobility and energy markets are currently facing a common challenge given that sector coupling is still in the conceptual initial phase. In fact due to the omission of centrally generated control energy with an increasing fluctuating energy originating from solar and wind power, increased energy demand and peak loads, especially due to the ramp-up of electromobility, new distributed control mechanisms must be found to ensure grid stability. However, electromobility not only creates new challenges, with a suitable approach, it also offers the potential to become an integral part of controlling grid stability.