Optimizing the marketing of flexibility for a virtual battery in day-ahead and balancing markets: A rolling horizon case study
Elisabeth Finhold, C. Gärtner, R. Grindel, Till Heller, Neele Leithäuser, E. Röger, F. Schirra
Abstract
Industrial electricity consumers with flexible demand can profit from adjusting their load to short-term prices or by providing balancing services to the grid. Markets which support this kind of short-term position adjustment are the day-ahead market and balancing markets. We propose a formulation for a combined optimization model that computes an optimal distribution of flexibility between the balancing and day-ahead markets. The optimal solution also includes the specific bids for the day-ahead and balancing markets. Besides the expected profits of each market and their different rules for bidding, our model also takes their different roles in a continuous marketing of flexibility into account. To prevent overrating short-term profits we introduce a variable penalty term that adds a cost to unfavorable load schedules. We evaluate the optimization model in a rolling horizon case study based on the setting of a virtual battery at TRIMET Aluminum SE, which is derived from a flexible aluminum electrolysis process. For such a battery we compute a daily optimal split of flexibility and trading decisions based on data in the period 04/2021–03/2022. We show that the optimal split is more profitable than using only one market or a fixed split between the markets.