abstract
- The efficient utilization of limited available resources plays a significant role in the operation of hydroelectric power systems. The purpose of scheduling in such systems is to determine the optimal power generation and generating unit commitment schedules so as to optimize an economic performance indicator subject to various system and external constraints. Fluctuations in electricity prices caused by the ever changing market conditions have a significant impact on the generation schedules for hydroelectric power systems. This may also give rise to a phenomenon of significant variation in optimal power generation and unit commitment schedules in response to slight fluctuations in pricing. These variations are undesirable since they warrant changes to the operational policy. This work focuses on the analysis of this “nervousness” phenomenon and the development of two strategies to mitigate its severity. This work involves the development of a mixed-integer nonlinear programming (MINLP) model for the short-term hydro scheduling (STHS) problem and its solution using a computationally efficient successive linear programming (SLP) technique. The effectiveness of the proposed methodology is demonstrated through a case study for daily generation scheduling in a cascaded hydroelectric power system.