Integration of optimal cleaning scheduling and control of heat exchanger networks undergoing fouling: Model and formulation

The performance and operability of heat exchanger networks (HENs) is strongly affected by fouling, which involves the deposition of unwanted material, which reduces the heat-transfer rate and increases the pressure drop, the operational costs, and the environmental impact of the process. Periodical cleaning and control of the flow rate distribution in the HEN are used to mitigate the effects of fouling and restore the performance of the units. The optimal cleaning scheduling has been formulated as a mixed-integer linear programming (MILP) or mixed-integer nonlinear programming (MINLP) problem and is solved using various approaches. The optimal control has been formulated as a nonlinear programming (NLP) problem and is used to define the flow rate distribution of the network. Both problems share the same objective: minimization of the total cost of the operation. In principle, the simultaneous solution of the optimal control problem and the optimal cleaning scheduling problem should provide greater savings than the independent or sequential solution of the two problems, since the interactions of the two mitigation alternatives are considered. However, these two problems have been typically considered separately, because of modeling and solution challenges. Also, it is not quite clear what additional benefit a simultaneous solution may bring. The challenges for solving the integrated problem are the large scale of the associated optimization problem and the different time scales involved in each operational layer. Here, a general and efficient formulation is proposed, using a continuous time discretization scheme for the integrated problem of scheduling and control of HENs subject to fouling. A dynamic model of the heat exchangers is proposed that is sufficiently detailed to represent the physics of interest with novel modifications to address simultaneously their control and scheduling in a network. The problem is formulated as a MINLP and solved using deterministic optimization algorithms. The flexibility of the model and variations of the formulation are demonstrated with two small case studies. The formulation complexity versus scale and advantages are analyzed. The results show that considering the two problems simultaneously has a very strong synergistic effect, with over a 20% decrease in operational cost achieved, in comparison to using either fouling mitigation alternative individually

Optimization of refinery preheat trains: predictive maintenance and operations improvement

Deciding which heat exchanger to clean, when to clean and how to clean in refinery pre-heat trains is a challenging activity that typically relies on operator’s experience. In this paper, an algorithm that allow identifying the most economic cleaning schedule for a given refinery configuration and operating conditions is presented. The method relies on an advanced framework that incorporates rigorous heat exchanger models capable of predicting the fouling behaviour of the refinery as a function of configuration of the individual units and the network, process conditions and time. An industrial case study is presented to illustrate the benefits of the approach, showing that significant improvements over current practice can be obtained

A model-based method for visualization, monitoring, and diagnosis of fouling in heat exchangers

A critical review of current methods for monitoring the performance of heat exchangers in the presence of fouling highlights a number of pitfalls. An improved analysis method and visualization of operation data (the TH-λ plot) are proposed, which enable to accurately and rapidly estimate the location and extent of fouling, the properties of the deposit, and their impact on exchanger performance. The method uses advanced dynamic thermo-hydraulic models to analyze the data. The visualization presents this information in a way easily interpreted by field engineers. The superior features are demonstrated on various applications, where traditional methods give poor visibility or outright wrong information about underlying events. These include organic fouling deposition and aging, incomplete cleaning, multicomponent deposits, and changes in fouling behavior. First, the basic concepts are illustrated with idealized examples (constant inlet conditions, using simulated data). The approach is then applied to three real refining case studies, with pressure drop either measured or generated via soft sensors. The results show that the advanced dynamic models used enable to properly integrate and interpret highly variable data measurements, explain complex underlying thermal and hydraulic effects, adequately monitor performance, and rapidly detect changes in fouling behavior. The approach provides a new practical tool for monitoring of heat exchanger performance and early fouling diagnosis

Crude Oil Fouling Deposition, Suppression, Removal, and Consolidation—and How to Tell the Difference

This research was partially performed under the UNIHEAT project for which EDB and SM wish to acknowledge the Skolkovo Foundation and BP for financial support. The support of Hexxcell Ltd, through provision of Hexxcell Studio, is also acknowledged

Impact of crude oil fouling composition on the thermohydraulic performance of refinery heat exchangers

Papers presented to the 11th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, South Africa, 20-23 July 2015.Crude oil fouling studies generally focus on the thermal impact of organic deposits. The hydraulic limit given by pressure drop is, however, frequent cause of shutdowns and cleaning. Inorganic matter is often found in deposit analysis, but ignored in most studies. A case study is presented based on published plant data from the Esfahan Refinery (Iran). A detailed thermo-hydraulic model of heat exchangers undergoing fouling, together with the available data and reasonable assumptions, is applied to study the exchanger most affected by fouling. Novel modifications are made to: i) capture the effect of inorganics on the deposit conductivity; and ii) use pressure drop measurements, instead of temperature, to fit key fouling parameters. Good agreement is obtained between model and plant data. This demonstrates the need and benefit of considering fouling layer composition and both temperature and pressure drop data in the fitting of model parameters and interpretation of plant data. The potential of using such a model for early detection of operative problems is highlighted.This research was partially performed under the UNIHEAT project. EDB and SM wish to acknowledge the Skolkovo Foundation and BP for financial support. The support of Hexxcell Ltd, through provision of Hexxcell Studio™, is also acknowledged.am201

Organic and inorganic fouling in heat exchangers – Industrial case study: Analysis of fouling state

Skolkovo Foundation; B

Cross Sectional Examination of a Fouled Tube Removed from a Crude Oil Preheat Exchanger

A first attempt to characterize intact foulant of a refinery preheater is presented. A tube was removed from an exchanger located postdesalter and preflash-drum at a 4-year shutdown, and dissected into undisturbed cut-out rings. Following visual inspection, elemental analysis (X-ray maps and line scans) was carried out and radial concentration profiles of the existing elements were established. A stratified colored foulant layer inside the tube appeared in sine waves fluctuating at both axial and angular directions, likely evidencing for the first time a shadow effect and erosion process. Results agreed with our studies on a comparable exchanger of the same refinery. They confirm the proposed deposition mechanism and simulation results, indicating formation of a stratified foulant consisting inorganics ranging 50 wt %, the presence of an acute inorganic deposition period along the chronic organic–inorganic fouling, and the identification of the foulant phases arrangement, among possible conductivity mixing models, as cocontinuous and effective medium theory structures

Comparative genomics of Steinernema reveals deeply conserved gene regulatory networks

Background: Parasitism is a major ecological niche for a variety of nematodes. Multiple nematode lineages have specialized as pathogens, including deadly parasites of insects that are used in biological control. We have sequenced and analyzed the draft genomes and transcriptomes of the entomopathogenic nematode Steinernema carpocapsae and four congeners (S. scapterisci, S. monticolum, S. feltiae, and S. glaseri). Results: We used these genomes to establish phylogenetic relationships, explore gene conservation across species, and identify genes uniquely expanded in insect parasites. Protein domain analysis in Steinernema revealed a striking expansion of numerous putative parasitism genes, including certain protease and protease inhibitor families, as well as fatty acid- and retinol-binding proteins. Stage-specific gene expression of some of these expanded families further supports the notion that they are involved in insect parasitism by Steinernema. We show that sets of novel conserved non-coding regulatory motifs are associated with orthologous genes in Steinernema and Caenorhabditis. Conclusions: We have identified a set of expanded gene families that are likely to be involved in parasitism. We have also identified a set of non-coding motifs associated with groups of orthologous genes in Steinernema and Caenorhabditis involved in neurogenesis and embryonic development that are likely part of conserved protein–DNA relationships shared between these two genera

Stability of optimal closed-loop cleaning scheduling and control with application to heat exchanger networks under fouling

Heat exchanger networks subject to fouling are an important example of dynamic systems where performance deteriorates over time. To mitigate fouling and recover performance, cleanings of the exchangers are scheduled and control actions applied. Because of inaccuracy in the models, as well as uncertainty and variability in the operations, both schedule and controls often have to be revised to improve operations or just to ensure feasibility. A closed-loop nonlinear model predictive control (NMPC) approach had been previously developed to simultaneously optimize the cleaning schedule and the flow distribution for refinery preheat trains under fouling, considering their variability. However, the closed-loop scheduling stability of the scheme has not been analyzed. For practical closed-loop (online) scheduling applications, a balance is usually desired between reactivity (ensuring a rapid response to changes in conditions) and stability (avoiding too many large or frequent schedule changes). In this paper, metrics to quantify closed-loop scheduling stability (e.g., changes in task allocation or starting time) are developed and then included in the online optimization procedure. Three alternative formulations to directly include stability considerations in the closed-loop optimization are proposed and applied to two case studies, an illustrative one and an industrial one based on a refinery preheat train. Results demonstrate the applicability of the stability metrics developed and the ability of the closed-loop optimization to exploit trade-offs between stability and performance. For the heat exchanger networks under fouling considered, it is shown that the approach proposed can improve closed-loop schedule stability without significantly compromising the operating cost. The approach presented offers the blueprint for a more general application to closed-loop, model-based optimization of scheduling and control in other processes