Optimization of a gas turbine in the methanol process, using the NLP model

详细信息	查看全文 | 推荐本文 |

• 作者：Anita Kovač ; Kralj ; Peter Glavič
• 关键词：Simultaneous optimisation ; NLP ; Model ; Cogeneration ; Gas turbine
• 刊名：Applied Thermal Engineering
• 出版年：2007
• 期刊代码：8_13594311
• 类别：ce
• 出版时间：August 2007
• 卷：27
• 期：11-12
• 页码：1799-1805
• 文件大小：166 K

摘要

Heat and power integration can reduce fuel usage, CO₂ and SO₂ emissions and, thereby, pollution. In the simultaneous heat and power integration approach and including additional production, the optimization problem is formulated using a simplified process superstructure. Nonlinear programming (NLP) contains equations which enable structural heat and power integration and parametric optimization. In the present work, the NLP model is formulated as an optimum energy target of process integration and electricity generation using a gas turbine with a separator. The reactor acts as a combustion chamber of the gas turbine plant, producing high temperature. The simultaneous NLP approach can account for capital cost, integration of combined heat and power, process modification, and additional production trade-offs accurately, and can thus yield a better solution. It gives better results than non-simultaneous methods. The NLP model does not guarantee a global cost optimum, but it does lead to good, perhaps near optimum designs.

This approach is illustrated by an existing, complex methanol production process. The objective function generates a possible increase in annual profit of 1.7 MEUR/a.