The objective of this work is to present a decision support system that determines the optimal dispatch strategy of thermal power plants while considering the particular specifications of fuel supply agreements, such as take-or-pay and make-up clauses. Opportunities for energy purchase and selling at the spot market as well as a detailed modeling of the power plant (maintenance cycles, influence of temperature, etc.) are also considered during the optimization. In an integrated approach, the model also determines the plants’ optimal schedule for maintenance. Since decisions in a stage have an impact in the future stages, the problem is time-coupled with a multi-stage framework. Moreover, the main driver for the decision-making is the energy spot price, which is unknown in the future and is modeled in this tool through user-defined scenarios. Therefore, the calculation of the optimal dispatch strategy is modeled as a decision under uncertainty problem, where at each stage the objective is to determine the optimal operation strategy that maximizes the total revenues taking into account the constraints and characteristics of the fuel supply contract. The methodology applied is a hybrid Stochastic Dual Dynamic Programming (SDDP)/Stochastic Dynamic Programming (SDP). Examples and case studies will be analyzed for the Brazilian system.
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