Abstract
The current paper investigates the possibility of establishing an empirically based model for predicting the emission rate of nitrogen oxides (NOx) from oil refinery furnaces, in order to continually track emissions with respect to environmental licence limits. Model input data were collected by direct stack monitoring using an electrochemical cell NOx analyser, as well as a range of telemetry sensors to obtain refinery process parameters. Principal Component Analysis (PCA), in conjunction with Partial Least Squares (PLS) regression was then used to build a series of models able to predict NOx emissions from the furnaces. The models produced were proven to be robust, with a relatively high accuracy, and are able to predict NOx levels over the range of operating conditions which were sampled. It was found that due to structural/operational variations a separate model is usually required for each furnace. The models can be integrated with the refinery operating system to predict NOx emission rates on a continuous basis. Two models representing structurally different furnaces are considered in this paper.
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