Multi-objective optimization of a triple shaft gas compressor station using Imperialist Competitive Algorithm

作者：Bayareh Morteza^*; Mohammadi Mehdi

来源：Applied Thermal Engineering, 2016, 109: 384-400.

DOI：10.1016/j.applthermaleng.2016.08.089

• Exergy
• ICA
• Regression
• ANOVA
• Triple shaft gas turbine

Triple-shaft gas turbine is one of the most commonly used gas compressor driven in natural gas compressor stations. In this work, exergy equilibrium formula of each components of a gas compressor station was specified and modeled using several mathematical models. The models predicted different parameters based on the environmental and operational conditions. A multivariate linear regression and ANOVA technique were employed to develop high precision models. Exergy analysis showed that the heater and combustion chamber have the lowest exergy efficiency in gas compressor stations. A significant exergy destruction occurs in the combustion chamber and approximately 13 MW of the available energy is lost in exhaust. Imperialist Competitive Algorithm was used for single-objective and multi-objective optimizations based on the socio-political relationship of countries. Results of this optimization revealed that application of this novel algorithm, can lead to a significant decrease in the computational time. This algorithm can be applied to the most of the industrial subjects, especially energy issues. Finally, a Matlab graphical user interface program was developed in order to make the modeling and optimization simpler to use. The best gas compressor operating conditions of all gas compressor stations driven by triple-shaft gas turbines can be determined using this algorithm.

• 出版日期2016-10-25