Abstract

The potential of replacing the use of natural gas with biomass gasification syngas through an externally fired micro-gas turbine (EFMGTs) is the main scope of this study. This includes the performance assessment at various off-design and ambient conditions compared to a reference natural-gas-fired Micro-Gas Turbine. The penetration of biomass use in the decentralized combined heat and power (CHP) sector can reduce fossil fuel dependency and contribute to the achievement of the net-zero emissions target. For this purpose, an analytical externally fired thermodynamic model is incorporated and validated with an artificial neural network (ANN) based on a natural-gas-fired micro-gas turbine unit. An operating strategy is proposed to ensure the system's safe operation under any fuel input conditions. The performance between the investigated cases is compared using an exergetic analysis. The main loss contributors that determine each case's performance are the exit losses. The substantial decrease of the latter results in high externally fired part-load efficiency, maximizing 110% of design-point efficiency. System performance has a linear dependency on ambient conditions. The increased flexibility introduced by the proposed operating strategy case facilitates the transition from natural gas to biomass, especially for higher heat-to-power ratio demands. The analysis highlights that the current externally fired configuration lags behind in high electrical demands (>90 kWel). However, this deficiency is diminished in cold ambient temperatures (<0 °C), indicating that the proposed technology is very opportune for these climatic conditions.

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