(109c) Decision Support Solution for the Operational Improvement of Refinery Pre-Heat Trains

The optimal operation of refinery crude pre-heat trains represents a significant challenge to the operations engineer. Frequent change in the crude feedstock and usual changes in the performance specifications create plant operation variations that are difficult to predict. Heat exchanger fouling compromises optimality and the usual implementation of ad hoc heat exchanger cleaning schedules compromises the optimal operation of the pre-heat train and reduces the overall profitability of the plant. Moreover, furnace fuel consumption is expensive and can be throughput limited if the fired heater capacity is reached. A three-step monitoring and performance improvement solution is presented that facilitates the involvement of the engineer in the daily pre-heat train operation and maintenance.

In the performance monitoring step, reconciled plant data is used to estimate the extent of fouling for the individual heat exchanger units. This first step also predicts the impact of pre-heat train fouling on the furnace inlet temperature. The subsequent decision support step evaluates the economic impact using pre-defined scenarios. In this second step, the effectiveness of cleaning and the use of bypasses, among other operating changes, are evaluated. Rapid assessment of the impact on Key Performance Indicators (KPIs) is conducted by using Aspen HX-Net Operations®. The final decision implementation step compares KPIs for the selection of the most practical and cost effective solution.