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

机译:优化价格不确定性下热电厂的燃料合同管理与维护调度

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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.
机译:这项工作的目的是提供一个决策支持系统,该系统决定了燃料供应合同协议的特定规范,例如燃料供应合同协议等特定规范的最佳调度策略,如采取或支付和化妆条款。在优化中,还考虑了在优化中考虑了电力现货市场在电力现货市场的能源购买和销售的机会以及电厂的详细建模,以及植物效率的环境温度的影响。以综合方式,该模型还确定植物的维护最佳时间表。由于一个阶段的决策影响了未来阶段,因此问题是时耦合和多阶段。此外,运营决策的主要驱动器是电力点价格,未来未知,在我们的模型中通过场景建模。因此,最佳调度策略是需要在不确定性下决定的随机问题,在每个阶段,目标是确定最佳运行策略,以考虑技术限制和燃料供应合同的条款,最大限度地提高总收入和燃料供应合同的条款。应用的方法是随机双动脉编程(SDDP)。将提出在巴西系统的案例研究。

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