On the use of the multivariate autoregressive and relative power contribution models for determination of transient root cause Original Research Article

The multivariate autoregressive (MAR) model and the relative power contribution (RPC) ratio are used in this work to determine the root causes of a power oscillation event and an apparent positive reactivity insertion transient occurred at the at the BWR/5 Units of the Laguna Verde Nuclear Power Plant (LVNPP) of México. The application of the MAR and PRC models leads to identify dominant frequencies and the contribution from other different signals to the dominant frequencies. The methodology firstly uses a linear model to estimate the response characteristics of the system and the spectra of the noise sources. The estimate of the process linear predictor is obtained by the ordinary least squares method. Then, the model performs a MAR analysis, and the RPC ratio is computed to determine the inter-relationship between the different reactor noise signals. The RPC ratio is an indication of how the fluctuation of one variable depends on other variables, at each frequency.