eprintid: 6833
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/68/33
datestamp: 2023-11-09 16:18:38
lastmod: 2023-11-09 16:18:38
status_changed: 2023-11-09 16:07:47
type: article
metadata_visibility: show
creators_name: Biyanto, T.R.
creators_name: Ramasamy, M.
creators_name: Jameran, A.B.
creators_name: Fibrianto, H.Y.
title: Thermal and hydraulic impacts consideration in refinery crude preheat train cleaning scheduling using recent stochastic optimization methods
ispublished: pub
keywords: Cleaning; Complex networks; Costs; Crude oil; Fouling; Heat exchangers; Losses; Problem solving; Pumps; Refining; Stochastic systems, Additional pressure drops; Cleaning schedules; Global optimum solutions; Heat exchanger network; Hydraulic impacts; Simplifying assumptions; Stochastic algorithms; Stochastic optimization methods, Optimization
note: cited By 22
abstract: 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
date: 2016
publisher: Elsevier Ltd
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984597017&doi=10.1016%2fj.applthermaleng.2016.05.068&partnerID=40&md5=96bf1c9177832feeb37e19ce183627a2
id_number: 10.1016/j.applthermaleng.2016.05.068
full_text_status: none
publication: Applied Thermal Engineering
volume: 108
pagerange: 1436-1450
refereed: TRUE
issn: 13594311
citation:   Biyanto, T.R. and Ramasamy, M. and Jameran, A.B. and Fibrianto, H.Y.  (2016) Thermal and hydraulic impacts consideration in refinery crude preheat train cleaning scheduling using recent stochastic optimization methods.  Applied Thermal Engineering, 108.  pp. 1436-1450.  ISSN 13594311