joint work with Raphael Hauser
In the seminal paper on optimal execution of portfolio transactions, Almgren and Chriss define how to liquidate a fixed volume of a single security under price uncertainty. Yet sometimes, as in the power market, the volume to be traded can only be estimated and becomes more accurate when approaching the delivery time. We propose a model that accounts for volume uncertainty and show that a risk-averse trader has benefit in delaying trades. With the incorporation of a risk, we avoid the high complexity associated to dynamic programming solutions while yielding to competitive performance.
joint work with Christoph Bergs
Many production industries require energy, e.g. in form of electricity, heat, or compressed air. With the rise of renewable energies and storage technologies, the question arises how such industries can take advantage of it, and to get an idea of energy flexibilization potentials at all. In this talk, we will introduce a software tool that is currently being developed at Siemens that allows industry users to assess their flexibilization potentials, and also to ensure cost-optimal operation of production systems. The underlying optimization problem is a Mixed-Integer NonLinear Program (MINLP).
joint work with Maryam Kamgarpour
Core-selecting auctions are well-studied in the deterministic case for their coalition-proofness and competitiveness. Recently, stochastic auctions have been proposed as a method to integrate intermittent participants in electricity markets. In this talk, we define core-selecting stochastic auctions and show their properties depending on the way uncertainty is accounted for in the payment mechanism. We illustrate a trade-off between achieving desirable properties, such as cost-recovery and budget-balance, in expectation or in every scenario. Our results are verified with case studies.