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首页> 外文期刊>International Journal of Greenhouse Gas Control >A new carbon capture proxy model for optimizing the design and time-varying operation of a coal-natural gas power station
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A new carbon capture proxy model for optimizing the design and time-varying operation of a coal-natural gas power station

机译:一种新的碳捕获代理模型,用于优化煤天然气电站的设计和时变运行

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摘要

We optimize the design and time-varying operation of a CO2-capture-enabled power station burning coal and natural gas, subject to a CO2 emission intensity constraint. The facility consists of a coal-fired power plant and an amine CO2 capture system, which is powered by a combined-heat-and-power auxiliary gas-fired subsystem. The detailed design of the CO2 capture system, the detailed heat integration of the facility, and time-varying operations schedule across all hours of the year are determined in a single optimization problem. This problem is formulated as a bi-objective mixed integer nonlinear program: objectives include minimizing total capital requirement (TCR) and maximizing net present value (NPV). Because the Aspen Plus model used for the CO2 capture system is too computationally intensive to use directly in optimization runs, we develop a statistical proxy model of the capture system that reproduces Aspen Plus results but is several hundred times faster. The integrated proxy model includes statistical submodels for the CO2 absorption and solvent regeneration blocks, as well as simple physical models of other system components. Incorporating the detailed CO2 capture system in the optimization provides important design information such as the optimal number of CO2 capture trains required. Two scenarios are considered, based on historical data for Texas and India. Results show that the choice of objective function can have a strong effect on planned operating profile (constant or variable operations). Similarly, hourly electricity price variability strongly affects design and plant scheduling. In the West Texas scenario, which has high price variability, the maximum NPV objective favors variable operations, with a CO2 capture system utilization factor of 65.9% (out of a maximum of 85%), while the minimum TCR objective favors constant operations. In contrast, because of low electricity price variability in the India scenario, there is little value in time-shifting the demand for capture heat, so constant operations are favored in this case for both objectives. (C) 2015 Elsevier Ltd. All rights reserved.
机译:我们优化设计和时变运行的CO2捕集能力的燃煤和天然气电站,但要遵守CO2排放强度约束。该设施包括一个燃煤发电厂和一个胺CO2捕集系统,该系统由热电联产辅助燃气子系统提供动力。在一个优化问题中确定了二氧化碳捕集系统的详细设计,设施的详细热集成以及一年中所有小时的时变运行时间表。这个问题被表述为双目标混合整数非线性程序:目标包括最小化总资本需求(TCR)和最大化净现值(NPV)。由于用于CO2捕集系统的Aspen Plus模型计算量太大,无法直接在优化运行中使用,因此我们开发了捕集系统的统计代理模型,该模型可复制Aspen Plus结果,但速度快了数百倍。集成的代理模型包括用于CO2吸收和溶剂再生模块的统计子模型,以及其他系统组件的简单物理模型。在优化中结合详细的CO2捕获系统可提供重要的设计信息,例如所需的最佳CO2捕获数量。根据德克萨斯和印度的历史数据,考虑了两种情况。结果表明,目标函数的选择可以对计划的运行配置文件(恒定或可变运行)产生很大影响。同样,小时电价的可变性也会严重影响设计和工厂调度。在价格波动较大的西德克萨斯州情景中,最大NPV目标有利于可变操作,CO2捕集系统利用率为65.9%(最大为85%),而最小TCR目标有利于持续操作。相比之下,由于印度情景中的低电价波动性,随时间变化的热量收集需求几乎没有价值,因此在这种情况下,为实现这两个目标,均应保持恒定运行。 (C)2015 Elsevier Ltd.保留所有权利。

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