Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices
Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices
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DOI：
10.1016/j.energy.2013.02.030
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发表时间：
2013-06
期刊：
影响因子：
9
通讯作者：
S. Mitra;Lige Sun;I. Grossmann
中科院分区：
文献类型：
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作者：
S. Mitra;Lige Sun;I. Grossmann
热电联产（CHP）厂广泛用于工业应用中。在经济衰退之后，许多相关的生产工艺都没有得到充分利用，这对化学公司的竞争力构成了挑战。然而，如果热电联产电厂能够对时间敏感的电价做出动态反应，则利用不足可能是与电网进行更紧密交互的机会，电网正在向所谓的智能电网过渡。在本文中，我们描述了一个广义模式模型的组件的基础上，解决了工业热电联产工厂的操作优化。模式公式以详细的方式跟踪每个设备组件的状态，并且可以考虑不同的操作模式，例如锅炉的燃料切换和燃气轮机的补充燃烧，以及过渡行为。过渡行为，如温暖和冷启动，关机和预先计算的启动轨迹建模模式。每个部件的可行操作区域是基于输入-输出关系描述的，这些关系在理论上是合理的，例如蒸汽涡轮机的Willans线。此外，我们强调使用数学上有效的逻辑约束，允许快速求解大规模模型。我们提供了一个工业案例研究，并研究了不同情况下利用不足的影响。
Combined heat and power (CHP) plants are widely used in industrial applications. In the aftermath of the recession, many of the associated production processes are under-utilized, which challenges the competitiveness of chemical companies. However, under-utilization can be a chance for tighter interaction with the power grid, which is in transition to the so-called smart grid, if the CHP plant can dynamically react to time-sensitive electricity prices. In this paper, we describe a generalized mode model on a component basis that addresses the operational optimization of industrial CHP plants. The mode formulation tracks the state of each plant component in a detailed manner and can account for different operating modes, e.g. fuel-switching for boilers and supplementary firing for gas turbines, and transitional behavior. Transitional behavior such as warm and cold start-ups, shutdowns and pre-computed start-up trajectories is modeled with modes as well. The feasible region of operation for each component is described based on input–output relationships that are thermodynamically sound, such as the Willans line for steam turbines. Furthermore, we emphasize the use of mathematically efficient logic constraints that allow solving the large-scale models fast. We provide an industrial case study and study the impact of different scenarios for under-utilization.