Optimal bidding strategy for GENCOs based on parametric linear programming considering incomplete information

• A profit-maximizing bidding strategy for a real-time marketplace is proposed.
• Reliant on mature techniques, the proposed algorithm is computationally efficient.
• It handles non-continuous and non-convex piecewise staircase energy offer curves.
• It yields optimal solutions.
• It raises participant profit in multi-interval process with incomplete information.

Electric energy market participants face risks and uncertainties associated with the ever-changing market environment. A profit-driven bidding decision tool is thus crucial for generation companies (GENCOs) to maintain a competitive position. Although optimal bidding strategies have been extensively studied in the literature, most previous research assumes continuous and differentiable generation offer curves, whereas actual offer curves are piecewise staircase curves. Based on the foregoing, this paper presents an optimal bidding strategy for GENCOs, derived by using parametric linear programming, and extends the proposed method to consider incomplete information. We show that the proposed algorithm is able to utilize the characteristics of piecewise staircase energy offer curves in contrast to the findings of previous researchers.