The current shift from centralized to decentralized power generation with renewables as prime movers necessitates the integration of reliable small-scale power supply units to compensate for the intermittency of renewables. Micro gas turbines’ (MGTs) characteristics such as high reliability and low maintenance, along with flexible operation and quick load-following capabilities have made them a dependable source for the modern power generation industry and for households. MGTs are small-scale gas turbine units with a power range lower than 500 kW that can operate with low-calorific fuels such as biofuels and syngas as well as conventional fossil fuels and zero-carbon fuels.
The utilization of MGTs in innovative cycle layouts or varying types of feeding fuels is increasing, which requires the evaluation of system dynamics to ensure the safe operation of the engine and its components. Moreover, the role of MGTs as a backup for the intermittent renewable inputs means that they operate under more transient conditions rather than constant power production mode. Therefore, a reliable dynamic model of an MGT is required to investigate the dynamic response of the engine under various transient modes to ensure safe operation. Moreover, utilizing a dynamic model is vital in the designing process of MGT-based cycles in order to evaluate the behaviour of coupled components in off-design conditions and to optimize the controller parameters. To that end, developing a dynamic model of the MGT cycle that is accurate enough to predict the dynamic response of the engine and its components and fast enough to be utilized in design iterations is necessary.
In this paper, a high-fidelity model for real-time simulation of an MGT, based on a lumped and nonlinear representation of gas turbine components is presented. The model for a recuperated T100 MGT was constructed in Simscape, the object-oriented environment of MATLAB for modelling physical systems. MGT components were modelled as lumped volumes with dynamic equations of mass, momentum, and energy balance along with component-characteristic maps describing the evolution of the flow passing through them. Results from simulations were validated by experimental data collected from a real engine operating under different load conditions. Experimental tests and numerical simulations were conducted for pure methane as well as for blended methane/hydrogen as feeding fuels.