Dynamic self-scheduling of a fuel and emission constrained power producer under uncertainties

This work addresses a new framework for self-scheduling of a price-taker fuel and emission constrained power producer in a day-ahead market. The goal is determination of a trade-off between the expected profit and the risk when the power producer participates in day-ahead energy and spinning reserve markets. In this paper, a set of uncertainties including price forecasting uncertainty and available fuel uncertainty are contemplated. The latter uncertainty is raised due to the uncertainty of calling the power plant to generate in the spinning reserve market as well as forced outages of power plant. With considering of these uncertainties, a new framework for self-scheduling problem is proposed which is called dynamic self-scheduling. This risk-constrained dynamic self-scheduling framework is therefore formulated and solved as a mixed integer non-linear programming problem. Numerical results for a case study are discussed.