Model-based bidding strategies on the primary balancing market for energy-intense processes

Abstract

Energy-intense enterprises that flexibilize their electricity consumption can market this either at electricity spot markets or by offering ancillary services on demand, such as balancing power. We formulate optimization of the balancing power bidding strategy as a mixed-integer nonlinear program considering both price forecasts for the ancillary service market and hourly varying spot market prices. We solve this two-stage approach by decomposition into a nonlinear bidding problem and a mixed-integer linear scheduling problem. We consider aluminum electrolysis participating in the German primary balancing market. We show savings in weekly production costs of 5–20% compared to stationary operation. The savings due to the optimal bidding strategy are up to twice the savings from pure exploitation of electricity spot market price spreads. We thus demonstrate that energy-intense processes can systematically take advantage of highly profitable demand-side management measures beyond a spot market price adjusted production.