Optimal allocation of cleanings in heat exchanger networks

Abstract This paper addresses the identification of the optimal set of heat exchangers to be cleaned during a plant maintenance shutdown. The proposed methodology is based on the resolution of a mixed-integer linear programming problem which allows the identification of the cleaning requirements aiming to reduce costs during the interval between scheduled plant shutdowns. The linear structure of the proposed formulation avoids problems associated to multiple local optima, and the resultant problem dimension allows the analysis of large heat exchanger networks without excessive computational efforts. The application of the proposed approach is illustrated through the investigation of two heat exchanger networks. The first example explores some typical cleaning patterns and the other example demonstrates the utilization of the proposed approach applied to a real network.

[1]  Richard S. H. Mah Chemical Process Structures and Information Flows , 2013 .

[2]  David I. Wilson,et al.  Scheduling cleaning in a crude oil preheat train subject to fouling: Incorporating desalter control , 2010 .

[3]  C. Floudas Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications , 1995 .

[4]  Miguel J. Bagajewicz,et al.  On a New MILP Model for the Planning of Heat-Exchanger Network Cleaning. Part III: Multiperiod Cleaning under Uncertainty with Financial Risk Management , 2005 .

[5]  André L.H. Costa,et al.  Investigation of an alternative operating procedure for fouling management in refinery crude preheat trains , 2009 .

[6]  G. Owren,et al.  How do the inaccuracies of enthalpy and vapour-liquid equilibrium calculations influence baseload LNG plant design? , 1996 .

[7]  David Kendrick,et al.  GAMS, a user's guide , 1988, SGNM.

[8]  Peter J. Fryer,et al.  A prototype cleaning map: A classification of industrial cleaning processes , 2009 .

[9]  Vassilios S. Vassiliadis,et al.  Identifying optimal cleaning cycles for heat exchangers subject to fouling and ageing , 2012 .

[10]  Miguel J. Bagajewicz,et al.  On a New MILP Model for the Planning of Heat-Exchanger Network Cleaning. Part II: Throughput Loss Considerations , 2005 .

[11]  André L.H. Costa,et al.  Stochastic simulation of supercritical fluid extraction processes , 2000 .

[12]  Vassilios S. Vassiliadis,et al.  Long-Term Scheduling of Cleaning of Heat Exchanger Networks , 2002 .

[13]  James Riley Couper,et al.  Process Engineering Economics , 2003 .

[14]  Luis Jose Amendola,et al.  IDENTIFICATION OF THE CRITICAL PHASES AND DECISION-MAKING CRITERIA FOR THE SHUTDOWN OF CHEMICAL PROCESSING PLANTS. CASE STUDIES: SOUTH AMERICA, SPAIN AND PORTUGAL. , 2010 .

[15]  D. P. Sekulic,et al.  Fundamentals of Heat Exchanger Design , 2003 .

[16]  Miguel J. Bagajewicz,et al.  On a New MILP Model for the Planning of Heat-Exchanger Network Cleaning† , 2004 .

[17]  B. L. Yeap,et al.  Evaluation of laboratory crude oil threshold fouling data for application to refinery pre-heat trains , 2002 .

[18]  André L.H. Costa,et al.  A matrix approach for steady-state simulation of heat exchanger networks , 2007 .

[19]  Lazaros G. Papageorgiou,et al.  Optimal Energy and Cleaning Management in Heat Exchanger Networks Under Fouling , 2000 .

[20]  F. S. Liporace,et al.  Real Time Fouling Diagnosis and Heat Exchanger Performance , 2007 .

[21]  Vassilios S. Vassiliadis,et al.  Mitigation of fouling in refinery heat exchanger networks by optimal management of cleaning , 2001 .

[22]  R. Smith,et al.  Optimization of Operating Conditions for Mitigating Fouling in Heat Exchanger Networks , 2007 .