Abstract:
The profitable exploitation of asset portfolios in the European electricity markets has become more challenging in recent years. This is particularly true for combined heat and power (CHP) generation units that are often facing must-run conditions due to heat demands that need to be satisfied. Including the use of flexibility from storage technologies is key to optimize power plant operation margins and therefore it is crucial to adequately account for price uncertainties in the European market design. Stochastic optimization is thus frequently suggested for an optimal bidding and dispatch of said portfolios. In our contribution, we develop a novel chain of one weekly and five daily two-stage stochastic optimizations with recourse to identify the optimal bidding strategies for CHP portfolios to all relevant markets, including the key European electricity market segments, i.e., hourly day-ahead and quarterhourly intraday opening auctions, and control reserve markets, i.e., primary (FCR), secondary (aFRR) and tertiary (mFRR) reserve auctions. We test our model by means of a rolling-horizon approach on historical data and contrast our model's performance with regards to objective function improvement and computation time for various numbers of scenarios. We furthermore benchmark the model against its deterministic representation with and without perfect information. We find that stochastic optimization may substantially increase portfolio returns, without impairing the usability of stochastic optimization frameworks in real-world contexts, a result that is stable with and without the consideration of heat provision and with different market designs regarding FCR provision periods.