Risk-Constrained Self-Scheduling of a Thermal Power Producer

TLDR

The study tackles the self‑scheduling problem of a price‑taker thermal power producer, emphasizing the trade‑off between maximizing profit and minimizing risk. A mixed‑integer quadratic programming model jointly optimizes profit and risk, solved with commercial solvers. Case‑study results demonstrate the model’s effectiveness in balancing profit and risk for realistic operations.

Abstract

This paper addresses the self-scheduling problem of a price-taker power producer. It focuses on risk modeling, emphasizing the tradeoff existing between maximum profit and minimum risk. The paper analyzes a self-scheduling model that considers simultaneously profit and risk. This model is formulated as a mixed-integer quadratic programming problem, which is solved using commercially available software. Relevant results from a realistic case study are discussed.