Abstract The growing energy need for decentralized and renewable power production increases the demand for flexible and very efficient small scale power generation units. Micro gas turbines (mGTs) are promising candidates for small-scale combined heat and power (CHP) generation for the residential, commercial and industrial sectors with a usual power output below 500 kWe. Such units are well-suited for compensating demand fluctuations in renewable-dominated grids. Since their operation must be reliable under transient and part-load conditions, a thorough understanding and examination of their dynamic behavior are crucial. This calls for the development of computationally efficient models for the real-time prediction of key performance parameters that can enable effective control and optimization strategies in mGT systems. For this paper, a dynamic real-time 0D model of a 10 kWe mGT prototype has been constructed and validated. The model is developed following a modular approach in MATLAB/Simulink environment, allowing the flexible integration of different engine components: compressor, turbine, recuperator, combustor, and control system. Each module implemented refined differential equations, ensuring fast computation while capturing the most important transient behaviors. The mGT prototype of 10 kWe was designed and manufactured by MITIS SA to target the residential energy market, biomethanization plants or decentralized power system for 5G antenna. The machine was tested, and key performance parameters were measured in different locations of the cycle. The model was then validated with the experimental data obtained on the mGT prototype, examined under transient and part-load conditions. The most important performance parameters, like shaft speed, turbine inlet temperature, and pressures, proved to be in very good agreement between simulated results and experimental measurements, with deviations contained within the acceptable uncertainty ranges of the sensors. This real-time framework of the 10 kWe prototype offers potential for optimization of mGT within distributed energy applications, and provides a modular basis for further improvement by studying humidified and 2-stage mGT cycles and innovative control strategies.
Gaitanis et al. (Mon,) studied this question.