AN ACCURATE PREDICTIVE EMISSIONS MONITORING-SYSTEM (PEMS) FOR AN ETHYLENE FURNACE

The Predictive Emissions Monitoring System (PEMS) has been recently pr oposed as an alternative to hardware continous emissions monitors (CEM ). PEMS has two distinct advantages over hardware CEM: much lower cost s to install and maintain, and ability to provide information on emiss ions under various conditions. Using a state-of-the-art computer progr am, and accurate PEMS was developed for an ethylene furnace at Exxon C hemical Company's Baytown Olefins Plant, Baytown, Texas. First, a test plan was carefully designed to collect furnace process and stack emis sions data over the total operating range of the furnace. The emission s data (NOx, O-2 and CO) were collected and measured by an independent company for 5 days. The related process data were recorded in the DCS system during the same 5-day period. A dataset with some 7,000 patter ns of related process and emissions data was generated. The PEMS syste m contains 2 parts: emissions prediction and sensor validation models. The main purpose of the sensor validation model is to validate the in put sensor's raw data and reconstruct new sensor values, if necessary, before they are used in the prediction model. Its usage provides a hi gh degree of confidence for the PEMS system. Two separate emissions pr ediction models were built, one for NOx and O-2, and the other for CO. Both final models have the same 9 input sensors. A PEMS relative accu racy test audit (RATA) was performed by an independent company to test the PEMS system under the three firing rate conditions (low, medium, and high). Test results indicate that the PEMS system satisfied both t he relative accuracy (RA) and the stringent statistical test requireme nts including the F-test, t-test and r-correlation.