This paper presents a physical simulator for predicting the off-design and dynamic behavior of a single shaft heavy-duty gas turbine plant, suitable for gas-steam combined cycles. The mathematical model, which is nonlinear and based on the lumped parameter approach, is described by a set of first-order differential and algebraic equations. The plant components are described adding to their steady-state characteristics the dynamic equations of mass, momentum, and energy balances. The state variables are mass flow rates, static pressures, static temperatures of the fluid, wall temperatures, and shaft rotational speed. The analysis has been applied to a 65 MW heavy-duty gas turbine plant with two off-board, silo-type combustion chambers. To model the compressor, equipped with variable inlet guide vanes, a subdivision into five partial compressors is adopted, in serial arrangement, separated by dynamic blocks. The turbine is described using a one-dimensional, row-by-row mathematical model, that takes into account both the air bleed cooling effect and the mass storage among the stages. The simulation model considers also the air bleed transformations from the compressor down to the turbine. Both combustion chambers have been modeled utilizing a sequence of several sub-volumes, to simulate primary and secondary zones in presence of three hybrid burners. A code has been created in Simulink environment. Some dynamic responses of the simulated plant, equipped with a proportional-integral speed regulator, are presented.

Heavy-duty gas turbine plant aerothermodynamic simulation using simulink

Backpressure adjustable gas turbine combined cycle: A method to improve part-load efficiency

A coupling diagnosis method of sensors faults in gas turbine control system

https://cyberleninka.org/article/n/212855.pdf

Off-design performance of solar Centaur-40 gas turbine engine using Simulink

Part-load performance analysis of a combined cycle with intermediate recuperated gas turbine

This paper will discuss why the sequential algorithm resulted in error, and a new method, that is, the inverse algorithm, will be proposed. Then, a new model for solving the performance of gas turbine engines will be recommended to obtain a more rapidly converging and more accurate solution

A New Method of Predicting the Performance of Gas Turbine Engines

This paper points out that the turbine performance computation method used widely at present in solving the performance of gas turbine engines is a numerically instable algorithm. So a new method, namely inverse algorithm, is proposed.This paper then further proposes a new mathematical model of solving the stable performance of gas turbine engines. It has the features of not only being suitable for inverse algorithm for turbine performance, but also having less dimensions than existing models. So it has the advantages of high accuracy, rapid convergence, good stability, less computations, and so forth. It has been fully proven that the accuracy of the new model is much greater than that of the common model for gas turbine engines. Additionally, the time consumed for solving the new model is approximately 1 / 4 ∼ 1 / 10 of that for the common model. Therefore, it is valuable in practice.Copyright © 1990 by ASME

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For the purpose of increasing the effectiveness of sensors,used for monitoring the service state of gas turbines,a fault diagnosing method,using sensors in connection with a kind of wavelet analysis,is being proposed.With this method,by Multi Resolution Analysing(MRA) the sensor's output signals,drifting incipient faults and abruptly occurring faults can both be identified by making use of a signal's apparent tendency and its details.The type of abrupt fault concerned can simultaneously be distinguished by using Lipschitz's index,according to the fault's point of sudden change,and also by noticing the change in energy,triggered off by the fault.Fault simulation studies,using real time data of gas turbine exhaust gas temperatures,indicate the effectiveness of the proposed method.Figs 6,table 1 and refs 7.

Application of Wavelet Analysis in Fault Diagnosis with Gas-Turbine Sensors

Considering the non-stationary and random nature of data in the chemical production process and different noises,characteristic,as well as based on the characteristics of wavelet analysis,this paper proposes a method that the multiple wavelet transform is combined with a new threshold to remove random noises,collect true signals and improve the credibility of the dataThe method is applied to a modeling for the performance figure of NPAC productive process and the result indicates that it can effectively regain the factuality of the data and improve the fitting and generalization capability of the soft measurement modeling

Signal De-noising Based on Multiple Wavelet Transform and Application in Soft-measurement

Based on the traditional loss models of turbines,a new idea of how to calculate the loss of the VGT(Variable Geometry Turbine)has been mentioned.By comparing the different results of a real turbine as example using several common models,a new calculation method of how to get the loss of VGT was given in detail.

Wang Yong-hong

Papers

A New Method of Predicting the Performance of Gas Turbine Engines

A New Method of Predicting the Performance of Gas Turbine Engines

Application of Wavelet Analysis in Fault Diagnosis with Gas-Turbine Sensors

Signal De-noising Based on Multiple Wavelet Transform and Application in Soft-measurement

Analysis on The Loss Model of Variable Geometry Turbines