Abstract
In this article, the adaptive neuro-fuzzy inference system (ANFIS) and multiconfiguration gas-turbines are used to predict the optimal gas-turbine operating parameters. The principle formulations of gas-turbine configurations with various operating conditions are introduced in detail. The effects of different parameters have been analyzed to select the optimum gas-turbine configuration. The adopted ANFIS model has five inputs, namely, isentropic turbine efficiency (Teff), isentropic compressor efficiency (Ceff), ambient temperature (T1), pressure ratio (rp), and turbine inlet temperature (TIT), as well as three outputs, fuel consumption, power output, and thermal efficiency. Both actual reported information, from Baiji Gas-Turbines of Iraq, and simulated data were utilized with the ANFIS model. The results show that, at an isentropic compressor efficiency of 100% and turbine inlet temperature of 1900 K, the peak thermal efficiency amounts to 63% and 375 MW of power resulted, which was the peak value of the power output. Furthermore, at an isentropic compressor efficiency of 100% and a pressure ratio of 30, a peak specific fuel consumption amount of 0.033 kg/kWh was obtained. The predicted results reveal that the proposed model determines the operating conditions that strongly influence the performance of the gas-turbine. In addition, the predicted results of the simulated regenerative gas-turbine (RGT) and ANFIS model were satisfactory compared to that of the foregoing Baiji Gas-Turbines.
Highlights
Energy management, performance analysis, and economic evaluation of a combined heating, cooling, and power system are complicated tasks and often woven into a major project requiring teams of engineers from multidisciplinary backgrounds [1]
This section investigates the performance of gas-turbine configurations based on various operating conditions such as isentropic turbine efficiency (Teff ), ambient temperature (T1), isentropic compressor x y A1
It is noted that the drop in fuel consumption occurs when increasing both the pressure ratio and the isentropic turbine efficiency
Summary
Performance analysis, and economic evaluation of a combined heating, cooling, and power system are complicated tasks and often woven into a major project requiring teams of engineers from multidisciplinary backgrounds [1]. Since the sources and consequences of the primary failure of this whole system need to be addressed as efficiently as possible, more research work is required to improve the performance of power plants with the improvement of energy productivity and the reduction in fuel consumption For this purpose, computerized mathematical modeling of the GT plant will be very useful. The study conducted by Wang et al [30] has developed a generic algorithm to optimize the configuration of a CHP system for a hotel application Their model evaluated a comprehensive set of operational parameters including the annual changes in monthly electricity and natural gas prices to deduce the optimal primary energy consumption for the most efficient and highest cost savings [30].
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