Fouling in heat exchanger network (HEN) in a refinery has been identified as a major obstacle for efficient energy recovery. Fouling causes loss in efficiency over the time, additional pumping cost and loss of production due to additional downtime. A complex crude preheat train (CPT) in a petroleum refinery was chosen in this study to represent an industrial HEN experiencing severe fouling and huge economic losses due to fouling issues. The objective of this study was to develop a realistic cleaning schedule optimization problem. An improved optimization problem for the cleaning schedule of the heat exchangers in the CPT was developed which takes into account the hydraulic impact of fouling through the additional pressure drops. The problem fall into the MINLP class, that is very complex and finding the global optimum is a challenging task. Hence, the recent stochastic methods are proposed and used to solve the MINLP problem without introducing any approximations or simplifying assumptions. Optimizations were performed over an operating period of 44 months following crude slate variations and operating conditions of the refinery. The solution provided by recent stochastic algorithms are global optimum solution. The results show that ignoring the additional pumping cost in the objective function resulted in an optimal cleaning schedule that provides a less savings (18.09% of maximum potential savings) in the net loss compared to the optimal cleaning schedule that utilizing the additional pumping cost in the objective function, which increase about 19.34% of maximum potential savings.

1. Thermal and Hydraulic Impacts
Consideration in Refinery Crude Preheat
Train Cleaning Scheduling Using Recent
Stochastic Optimization Methods
Totok R. Biyanto*a, Henokh Y. Fibriantoa,M. Ramasamyb
aEngineering Physics Department, Institut Teknologi Sepuluh Nopember (ITS), Indonesia.
bChemical Engineering Department, Universiti Teknologi PETRONAS, Malaysia TRB, 2016
Applied Thermal Engineering

2. HE-01Pump HE-02 HE-03 HE-04
HE-09
HE-O8
HE-11
HE-05HE-06HE-07
HE-10
Product 7
Product 5 Product 6
Product 1Product 2Product 3
Product 4
Crude oil
tank farm
Furnace
77o
C
HEN under study
TRB, 2016

3. Time
Heatduty
Under clean conditions
Under fouled
conditions
Energy savings
Energy losses
Under cleaning
schedule
conditions
Objective : Maximize saving
TRB, 2016

4. Utilize recent stochastic algorithms
TRB, 2016

5. Recovered energy under clean, scheduled and dirt conditions
TRB, 2016

6. Comparison of saving with and without additional pumping
cost in the objective function
TRB, 2016

7. Conclusions
• The simultaneous HEN optimizations of all heat exchangers were
performed using the Duelist Algorithm (DA) with objective functions
with and without the additional pumping cost.
• It was observed that the implementation of the optimal cleaning
schedule with and without the additional pumping cost in the
objective function resulted in a net savings increase 19.34% and
18.09% of maximum potential savings during the 44 months period of
optimization, respectively.
• The proposed method confirmed could be proceed for small cleaning
schedule in iteration and by without linearization or decomposition
procedure and could achieve the maximum objective function value
or global optimum
TRB, 2016