This thesis addresses the problem of price distortions and uplift payments in non convex electricity markets by proposing an efficient methodology for Convex Hull Pricing computation. An extended network-flow–based Unit Commitment formulation is developed, explicitly incorporating intertemporal ramping constraints and warm-up periods, and solved through an adaptation of the Bienstock–Zuckerberg algorithm. This column-generation and partition-refinement framework enables an accurate representation of generator operational flexibility and the computation of prices that minimize unrecovered costs, while progressively tightening the feasible solution space across iterations. Computational experiments on real-world systems from California, FERC, RTS-GMLC and Belgium demonstrate that the proposed approach outperforms traditional methods such as Dantzig–Wolfe decomposition and the Level Method in terms of robustness and convergence speed. Moreover, the results show that omitting ramp constraints leads to an underestimation of equilibrium prices, and that preprocessing techniques are critical for the computational viability of the model.
Lucas Borquez Cerda (Fri,) studied this question.