Simultaneously optimizing bidding strategy in pay-as-bid-markets and production scheduling

The volatility of renewable energy sources leads to the development electricity markets with different time horizons, where flexible consumers can monetize their flexibility stabilize electric grid. From an electricity-user perspective, optimal monetization strategy and choice is difficult identify. We consider simultaneous participation in ancillary service market pay-as-bid mechanism a day-ahead market. develop formulation based on Benders decomposition that decouples both markets. This allows optimally distribute bids via scheduling optimizations. In particular, our optimization problem be solved general-purpose nonlinear programming solvers. demonstrate using proposed computationally more efficient than previously published enumeration-based approach.