A Comparison of Analog, Digital and Hybrid Computing Techniques for Simulation of Gas Turbine Performance

Volume 1B: General ◽

10.1115/74-gt-127 ◽

1974 ◽

Cited By ~ 3

Author(s):

B. D. MacIsaac ◽

H. I. H. Saravanamuttoo

Keyword(s):

Real Time ◽

Gas Turbine ◽

Dynamic Performance ◽

Hybrid Computing ◽

Real Time Simulation ◽

Advantages And Disadvantages ◽

Turbine Performance ◽

Time Simulation ◽

Digital Or

Simulation of gas turbine dynamic performance can be accomplished using analog, digital or hybrid computing techniques. The paper discusses computing techniques for each type of computer and reviews their advantages and disadvantages. It is concluded that the three types of simulation are complementary to each other and that all three computers have their place: the analog is essential for real time simulation of complex engines, the digital is most suitable for detailed studies and the hybrid combines the ease of integration of the analog with the logic and stored program capability of the digital.

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Real-time simulation test-bed for an industrial gas turbine engine’s controller

Mechanics & Industry ◽

10.1051/meca/2018028 ◽

2018 ◽

Vol 19 (3) ◽

pp. 311 ◽

Cited By ~ 2

Author(s):

Morteza Montazeri-Gh ◽

Seyed Alireza Miran Fashandi ◽

Soroush Abyaneh

Keyword(s):

Embedded System ◽

Real Time ◽

Gas Turbine ◽

Dynamic Performance ◽

Operational Reliability ◽

Test Bed ◽

Real Time Simulation ◽

Engine Model ◽

Time Simulation ◽

Industrial Gas Turbine

A hardware-in-the-loop (HIL) test for a control unit of an industrial gas turbine engine is performed to evaluate the designed controller. Although the dynamic performance of the studied gas turbine is strictly related to the variable inlet guide vain (VIGV) position, one of the main challenges is to develop an engine model considering VIGV variations. The model should also be capable of real time simulation. Accordingly, the gas turbine is numerically modeled using bond graph concepts. To demonstrate the operational reliability of the engine’s control strategy, the control algorithm is implemented on an industrial hardware as an embedded system. This is then put into a HIL test along with the engine model. The actual component (controller) and the virtual engine model are the hardware and software parts of the HIL test, respectively. In this experiment, the interaction between the real part and the rest of the system is compared with that of the completely numerical model in which the controller is a simulated software-based model as is the engine itself. Finally, the results indicate that the physical constraints of the engine are successfully satisfied through the implementation of control algorithms on the utilized hardware.

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A High-Fidelity Real-Time Simulation Code of Gas Turbine Dynamics for Control Applications

Volume 2: Turbo Expo 2002, Parts A and B ◽

10.1115/gt2002-30039 ◽

2002 ◽

Cited By ~ 6

Author(s):

S. M. Camporeale ◽

B. Fortunato ◽

M. Mastrovito

Keyword(s):

Mathematical Model ◽

Real Time ◽

Gas Turbine ◽

Dynamic Behavior ◽

Computational Time ◽

High Fidelity ◽

Simulation Code ◽

Real Time Simulation ◽

Time Simulation ◽

The Mathematical Model

A novel high-fidelity real-time simulation code based on a lumped, non-linear representation of gas turbine components is presented. The aim of the work is to develop a general-purpose simulation code useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of the gas turbine engine. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed.

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An innovative sliding mode load controller for gas turbine power generators: Design and experimental validation via real-time simulation

Energy ◽

10.1016/j.energy.2020.119363 ◽

2020 ◽

pp. 119363

Author(s):

A. Palmieri ◽

D. Lanzarotto ◽

S. Cacciacarne ◽

I. Torre ◽

A. Bonfiglio

Keyword(s):

Real Time ◽

Gas Turbine ◽

Experimental Validation ◽

Sliding Mode ◽

Power Generators ◽

Real Time Simulation ◽

Time Simulation

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State Vector Identification of Hybrid Model of a Gas Turbine by Real-Time Kalman Filter

Mathematics ◽

10.3390/math8050659 ◽

2020 ◽

Vol 8 (5) ◽

pp. 659

Author(s):

Gustavo Delgado-Reyes ◽

Pedro Guevara-Lopez ◽

Igor Loboda ◽

Leobardo Hernandez-Gonzalez ◽

Jazmin Ramirez-Hernandez ◽

...

Keyword(s):

Kalman Filter ◽

Real Time ◽

Gas Turbine ◽

State Vector ◽

Convergence Time ◽

Mean Square ◽

Real Time Simulation ◽

Time Simulation ◽

The Mean ◽

Mean Square Errors

A model and real-time simulation of a gas turbine engine (GTE) by real-time tasks (RTT) is presented. A Kalman filter is applied to perform the state vector identification of the GTE model. The obtained algorithms are recursive and multivariable; for this reason, ANSI C libraries have been developed for (a) use of matrices and vectors, (b) dynamic memory management, (c) simulation of state-space systems, (d) approximation of systems using equations in matrix finite difference, (e) computing the mean square errors vector, and (f) state vector identification of dynamic systems through digital Kalman filter. Simulations were performed in a Single Board Computer (SBC) Raspberry Pi 2® with a real-time operating system. Execution times have been measured to justify the real-time simulation. To validate the results, multiple time plots are analyzed to verify the quality and convergence time of the mean square error obtained.

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