Data Reconciliation and Fouling Analysis in Heat Exchanger Network

• Main Author: Abdul Aziz, Ahmad Nuruddin
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi PETRONAS 2014
• Subjects: TP Chemical technology
• Online Access: http://utpedia.utp.edu.my/14113/1/13616_AHMAD_NURUDDIN_DISSERTATION%20.pdf; http://utpedia.utp.edu.my/14113/
• Institution: Universiti Teknologi Petronas

In refinery, crude preheat train is use to preheat the crude oil with various product and pump around stream from downstream atmospheric until it reaches an optimum temperature for furnace heating. The variables such as temperature and flow rates is measured regularly and used to optimize the energy recovery in the train. However, since all measurement subject to certain error, any optimization exercised will not be accurate. In other to minimize the error, the measured variables are reconciled using data reconciliation technique. Data reconciliation is a mathematical approach which allows some adjustment on the measurement data in Heat Exchanger Network (HEN) to be made by eliminating measurement errors and obtain reconciled estimates of all stream flows, enthalpy and temperatures. This is to ensure that the measurement data satisfy the steady-state mass and energy balances of the crude preheat train. In HEN, Steady-State Data Reconciliation technique is implement. A set of mathematical models are generated in the form of matrices and used to treat the raw measurement data around crude preheat train so that more reliable measurement data are produced. The project started by extracting the data from the Piping and Instrumentation Diagram (P&ID) of the refinery. Then, the properties estimation of the data was done using Petrosim. After that, the Steady-State Data Reconciliation Model is developed in terms of matrices and solved by Matlab software. The results obtained consist of a vector of new adjusted raw data measurement or known as reconciled values. Analysis of the results show that the reconciled enthalpy did satisfied energy balances. However, the recalculated temperatures show huge adjustment compared to measured temperature, up to 12 oC adjustment (Stream 37). The data obtain is then used in fouling analysis of heat exchanger network. Fouling is an unwanted deposit on heat transfer equipment results in reduced efficiency of heat recovery. Fouling model is developed using the data from heat exchanger specification sheet supplied by the refinery. The model will predict the fouling resistance of heat exchanger at a time. Using the reconciled temperature, the fouling profile a long time for each heat exchanger is developed and the performance of heat