Abstract:

Aimed at the lack of effective stability evaluation methods for the current steam power system, an operation stability assessment method suitable for single parameter is proposed. This method is a composite method, which first applied the midpoint and regression based empirical mode decomposition (MREMD) and singular value decomposition (SVD) to decompose the time series of operation parameters and extract their hidden trend terms. Then, the components are selected for reconstruction according to the optimal algorithm parameter permutation entropy (OAPPE) of each component. Finally, the auto-regressive integrated moving average (ARIMA ) model commonly used in the non-stationary time series analysis is utilized to predict the trend and the disturbance of parameters, and their distribution characteristics are also extracted in this process, based on which, the probability of instability (PI) of operation parameters at each point on the predicted trend are calculated, and their stabilities are quantitatively evaluated. The actual case proves that this method can effectively assess the operation stability of a single parameter of the steam power system, which has a certain theoretical innovation and engineering application value.

Key words: midpoint and regression based empirical mode decomposition (MREMD), permutation entropy, probability of instability (PI), stability assessment