Multi-variable optimization of pressurized oxy-coal combustion
Multi-variable optimization of pressurized oxy-coal combustion
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DOI：
10.1016/j.energy.2011.12.043
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发表时间：
2012-02
期刊：
影响因子：
9
通讯作者：
Hussam Zebian;M. Gazzino;A. Mitsos
中科院分区：
文献类型：
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作者：
Hussam Zebian;M. Gazzino;A. Mitsos
以300 MWe湿循环加压富氧煤燃烧过程为研究对象，采用多启动的多变量梯度优化方法，对燃烧过程进行了同步优化。该模型考虑了实际的组件行为，包括热损失、蒸汽泄漏、压降、循环不可逆性和其他技术经济考虑。优化研究涉及16个变量，其中三个是整数值，和10个约束条件的目标是最大限度地提高热效率。求解过程遵循主动不等式约束，这些约束是通过基于代数的分析确定的，以便于收敛。多变量优化的结果进行了比较，类似于在文献中进行的压力敏感性分析，在这里进行的两个评估的基础情况下是一个有利的解决方案，在文献中找到。与文献设计相比，在低得多的操作压力和其他操作变量的适度变化下，获得了显着的循环性能改善。对循环性能和约束条件的变量的影响进行了分析和解释，以增加对系统实际行为的理解。这项研究反映了多变量同时优化的重要性，揭示了系统的特性，并发现了有利的解决方案，具有更高的效率比大气操作或单变量灵敏度分析。
Simultaneous multi-variable gradient-based optimization with multi-start is performed on a 300 MWe wet-recycling pressurized oxy-coal combustion process with carbon capture and sequestration. The model accounts for realistic component behavior including heat losses, steam leaks, pressure drops, cycle irreversibilities, and other technoeconomical considerations. The optimization study involves 16 variables, three of which are integer valued, and 10 constraints with the objective of maximizing thermal efficiency. The solution procedure follows active inequality constraints which are identified by thermodynamic-based analysis to facilitate convergence. Results of the multi-variable optimization are compared to a pressure sensitivity analysis similar to those performed in literature; the base-case of both assessments performed here is a favorable solution found in literature. Significant cycle performance improvements are obtained compared to this literature design at a much lower operating pressure and with moderate changes in the other operating variables. The effect of the variables on the cycle performance and on the constraints are analyzed and explained to obtain increased understanding of the actual behavior of the system. This study reflects the importance of simultaneous multi-variable optimization in revealing the system characteristics and uncovering the favorable solutions with higher efficiency than the atmospheric operation or those obtained by single variable sensitivity analysis.