Optimization of Fuel Contracts Management and Maintenance Scheduling for Thermal Plants under Price Uncertainty

The objective of this work is to present a decision support system that determines the optimal dispatch strategy of gas fuelled thermal power plants taking into account the particular specifications of fuel supply contract agreements, such as take-or-pay and make-up clauses. Opportunities for energy purchase and selling at the electricity spot market as well as detailed modeling of the power plant such as maintenance cycles and influence of ambient temperature in the plants efficiency are also considered in the optimization. In an integrated way, the model also determines the plants' optimal schedule for maintenance. Since decisions in one stage impact the future stages, the problem is time-coupled and multi-stage. Moreover, the main driver for the operations decision-making is the electricity spot price, which is unknown in the future and is modeled in our model through scenarios. Therefore, the optimal dispatch strategy is a stochastic problem requiring decision under uncertainty, where at each stage the objective is to determine the optimal operation strategy that maximizes the total revenues taking into account technical constraints and the clauses of the fuel supply contract. The methodology applied is the stochastic dual dynamic programming (SDDP). A case study in the Brazilian system will be presented