Use of gray wolf algorithm to optimize gas microturbineUse of gray wolf algorithm to optimize gas microturbine

 In this research, optimization of gas microturbine through economic, exergy and environmental analysis has been investigated by the gray wolf algorithm. First, a thermodynamic modeling was performed for each of the above modes, and then using the gray wolf method, optimum points were determined for each systemchr('39')s performance. For modeling, the code written in MATLAB software was used. The results of the study showed that the increase in maximum temperature has a small effect on the increase in the cost of purchasing and installing and maintaining equipment on the micro turbine cycle, which indicates that increasing the combustion temperature to the extent that the metallurgical limit of the cycle allows us to be a good factor in increasing the cycle efficiency with Considering economic issues. As well as increasing the efficiency of the recuperator, the greatest cost is borne by other factors on micro turbines. As the compressor compressor ratio increases, the cost of fuel is increased as shown above. The effect of increasing the turbine input temperature on the cost of exergy damage and the total cost of consuming fuel and purchasing, installation, and maintenance, as well as the matching of input data with the model derived from the gray wolf algorithm related to the total purchase, installation, and maintenance costs In addition, the cost of exergy damage plus fuel consumption is shown.