TY  - JOUR
KW  - Cleaning; Complex networks; Costs; Crude oil; Fouling; Heat exchangers; Losses; Problem solving; Pumps; Refining; Stochastic systems
KW  -  Additional pressure drops; Cleaning schedules; Global optimum solutions; Heat exchanger network; Hydraulic impacts; Simplifying assumptions; Stochastic algorithms; Stochastic optimization methods
KW  -  Optimization
ID  - scholars6833
N2  - 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, which 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 is 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 utilizes the additional pumping cost in the objective function, which increases about 19.34 of maximum potential savings. © 2016 Elsevier Ltd
VL  - 108
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984597017&doi=10.1016%2fj.applthermaleng.2016.05.068&partnerID=40&md5=96bf1c9177832feeb37e19ce183627a2
A1  - Biyanto, T.R.
A1  - Ramasamy, M.
A1  - Jameran, A.B.
A1  - Fibrianto, H.Y.
JF  - Applied Thermal Engineering
Y1  - 2016///
SP  - 1436
TI  - Thermal and hydraulic impacts consideration in refinery crude preheat train cleaning scheduling using recent stochastic optimization methods
N1  - cited By 22
AV  - none
EP  - 1450
SN  - 13594311
PB  - Elsevier Ltd
ER  -