Parameter Adaptive Modelling of a 500 Megawatt Drum Boiler

Abstract Measurements of the coal feed, feedwater flow, drum level, steam flow, turbine steam valve (TSV) pressure error and generator power were monitored on a 500 MW(e) drum boiler during full power operation under closed loop control. The fluctuations in these measurements about their mean value are analysed using multivariate time series techniques and parametric models to Identify the dynamics of the drum boiler. Recursive parameter estimation techniques and identlflability problems In determining the ‘optimum’ order autoregressive moving average (ARMA) models of the feedforward (process) and feedback (recycle/control) paths of distributed closed loop systems are discussed. The advantages of using cross-correlation techniques for systems involving unknown feedback structure are illustrated. Parametric models of the variable affecting drum level are then identified using a recursive parameter estimation methodology which Incorporates a covariance resetting procedure.