Abstract
The deregulation of utilities and the emerging power markets are creating renewed interest in operating micro-turbines in parallel with the utility system. As micro-turbines proliferate, it is necessary to reduce the model order of each micro-turbine to enable computational analysis. The application of the autoregression with exogenous signal (ARX) identification algorithm is presented to compute low-order micro-turbine models, suitable for analysis. This algorithm consists of a procedure for calculating the transfer function of a micro-turbine from samples of its input and output. Each micro-turbine reduced-order model influences the grid in the same manner as an actual micro-turbine would, modulating real and reactive power in response to voltage and frequency changes on the grid.
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