Sonja Germscheid successfully defended her dissertation

Sonja Germscheid successfully defended her dissertation on "Industrial Demand Response Potential of Simultaneous Day-Ahead and Intraday Electricity Market Participation".

The abstract of her thesis is as follows:

"Flexible industrial processes that can adjust their production rate and electricity consumption can reduce operational cost in a demand response scheduling optimization by participating in multiple electricity markets. In particular, day-ahead and intraday electricity markets allow for short-term adjustments and can counteract imbalances caused by variable renewable electricity generation. However, uncertainty of the intraday electricity prices must be accounted for when committing to purchases on the day-ahead market.

We evaluate the demand response potential of industrial applications considering simultaneous participation in both the day-ahead and intraday electricity market. To this end, we model the market participation in a two-stage stochastic program and account for both risk-neutral and risk-averse objectives.

First, we assess which process characteristics are particularly suitable to participate in both markets. To this end, we use an existing generalized model of a single-step continuous production process. In a parameter study, we show that independent of  process flexibility characteristics, risk-averse market participation can significantly reduce the financial risk with minor increases in expected operational cost. Furthermore, we show for three electrolysis processes  how the generalized process model can be used for a simple, quick demand response assessment considering the two markets.

Next, we assess the potential of the copper production as an exemplary multi-step production process. To this end, we adapt an existing copper production model to the simultaneous market participation particularly accounting for a one-week scheduling horizon. We show that modeling choices of integer decisions significantly impact the extent of load-shifting and furthermore, we propose a heuristic sequential day-ahead and intraday scheduling approach that can trade-off financial risk and expected operational cost at low computational cost.

In the subsequent study, we review existing risk-averse scenario reduction methods and compare them to our heuristic sequential scheduling. To this end, we study the impact of the reduction methods on the demand response potential of the simultaneous participation for the generalized process model with respect to both financial risk and expected operational cost and find that the sequential approach shows a particularly promising trade-off.

Finally, we combine on-site renewable electricity supply and demand response of industrial processes. In particular, we integrate the scheduling of the generalized process model into the design optimization of a renewable electricity generation and supply system, study arising ecologic and economic synergies, and assess the impact of considering simultaneous market participation at design stage. We find that the demand response is hardly driven by the locally generated electricity and that accounting for simultaneous participation at design stage can impact potential trading volumes."