Real Time Micro Gas Turbines Performance Assessment Tool: Comprehensive Transient Behavior Prediction With Computationally Effective Techniques

Abstract

Conventional centralized power generation is increasingly transforming into a more distributed structure. The periodic power production that is created by the renewable production unit generates the need for small-scale heat and power units. One of the promising technologies which can assist flexible power grid is micro gas turbines (mGTs). Such engines are competent candidates for small-scale combined heat and power (CHP). mGTs, as compensators for demand fluctuations, are required to work on transient and part-load conditions, creating new research challenges. A complete characterization of their dynamic behavior through a real-time simulation tool is necessary to establish effective control systems. Moreover, the energy transition requires the conversion of conventional mGTs to more sophisticated high-efficient cycles with the addition of extra components (saturation unit, aftercooler, etc.). Consequently, a modular and computationally fast real-time tool offers an asset in the development of future cycles based on the mGT concept. This paper presents the development of a numerical in-house tool implemented in Python programing language for the performance prediction of the mGT. The fundamental target of our work is to achieve high fidelity of the simulated dynamic responses. The key benefit of this tool is the low complexity component modules. The model is validated with experimental results from the VUB T100 test rig. The code reproduces the experimental data well during steady-state and transient operations as the key cycle parameters present a deviation from the measurements within the range of 1.5%.