A crude oil refinery is an industrial process plant where crude oil is processed and refined into different petroleum products (i.e.
|
|
- Bruce Jacobs
- 6 years ago
- Views:
Transcription
1
2
3
4 A crude oil refinery is an industrial process plant where crude oil is processed and refined into different petroleum products (i.e. gasoline, diesel, kerosene, jet fuel)
5 This figure shows a typical refinery distillation unit, including atmospheric column, stabiliser and vacuum columns. As shown, the crude oil is heated in a set of heat exchange units prior to entering the preflash drum to separate the light components to the column. These units exchange heat with the hot streams from the products and pump-around streams. Then the crude oil is further heated in a furnace before feeding into the atmospheric column. The atmospheric column products are either stored for use or further processed in the stabiliser and vacuum column. The vacuum column processes atmospheric residue and produces different grades of gas oil and vacuum residue.
6 The structure of the crude distillation unit (CDU) is very complex and expensive to modify. There are strong interactions between the tower and Heat Exchanger Network (HEN). The hot streams such as the pump-arounds, condenser and distillation products streams are integrated with the cold streams, such as the crude oil feed. The remaining energy requirements are supplied by fuel oil in the furnace and cooling water. Despite the fact that the system is heat-integrated, it still is an energy intensive process, consuming fuel at the equivalent of 2% of the total crude oil processed (Liebmann,1998). This large amount of fuel burned during its operation makes the distillation unit an environmentally challenging process (Liebmann,1998). Crude oil is a mixture of a very large number of different hydrocarbons. Each type of crude is a unique combination of components, which define its physical and chemical properties (Fahim,2009). The variable composition has a substantial impact on the separation and energetic performance of the column, and the characteristics of the distillation products (e.g. density, viscosity). In industrial practice, crude oil feedstock conditions such as temperature and flow rate change constantly, and the column must be designed and operated to perform efficiently over this broad range of scenarios while keeping product specifications within desirable values. Liebmann, K., V. R. Dhole, and M. Jobson (1998). Integrated Design of a Conventional Crude Oil Distillation Tower Using Pinch Analysis. IChemE 76(March), Fahim, M., T. Al-Sahhaf, H. Lababidi, and A. Elkilani (2009). Fundamentals of petroleum refining. Elsevier Science.
7 This figure shows the main fractions from atmospheric crude oil distillation, their uses, and the trends in properties. Distillation products are further processed in the refinery (i.e. vacuum distillation, hydrotreating, etc.), distillation product properties and flow rates have an impact in downstream process costs and yields.
8 This figure shows the main petroleum products with carbon numbers and boiling point ranges. Fahim, M., T. Al-Sahhaf, H. Lababidi, and A. Elkilani (2009). Fundamentals of petroleum refining. Elsevier Science.
9 Several products can be obtained from the crude oil distillation unit, such as light and heavy naphtha, distillate, and residual crude oil. Common product quality specifications for crude oil distillation towers include flow rates, cut point and gap temperatures, which define separation achieved. In practice, refinery products are characterised by one or more properties, for example, Reid vapour pressure for distillate and heavy naphtha; flash point for heavy naphtha and recovery at 366 o C for residual crude oil (Basak et al., 2002; Fahim et al., 2009, chap. 9). Retrofit design deals with an existing column and heat exchanger network with physical constraints, such as column diameter, number of stages, pump around locations, heat exchanger matches, etc. Consequently, retrofit design has to deal with a greater number of restrictions and the number of independent variables is more limited than for grassroots design. Basak, K., K. S. Abhilash, S. Ganguly, and D. N. Saraf (2002, March). On-Line Optimization of a Crude Distillation Unit with Constraints on Product Properties. Industrial & Engineering Chemistry Research 41 (6), Fahim, M., T. Al-Sahhaf, H. Lababidi, and A. Elkilani (2009). Fundamentals of petroleum refining. Elsevier Science.
10 In this work, the influence of the yields on the heat-recovery system and the process profitability is explored. The goal is to increase profit by maximising the yields of the most valuable distillation products, while maintaining product quality within acceptable limits.
11 The objective of this work is to develop a methodology for increasing heatintegrated crude oil distillation system profit, considering operational variables. This is achieved by maximising the yields of the most valuable distillation products, while maintaining product specifications within acceptable limits. A new optimisation framework for heat-integrated CDUs using Artificial Neural Networks (ANN) is proposed. In this approach, a statistical model for the atmospheric tower is constructed from data generated in rigorous models simulations. The heat-integrated system is incorporated in an optimisation scheme to maximise product profit and minimise operating costs. The optimisation problem is formulated to consider the dominant operational degrees of freedom of the distillation column, product property constraints (i.e. T5%, T95% points) are also incorporated. New stream data information from the column optimisation is passed to an algorithm to optimise the HEN separately.
12
13
14 In the simplified models developed by Suphanit (1999), the complex crude oil tower is decomposed into a sequence of simple columns, and then, each simple column is represented by modified Fenske-Underwood-Gilliland (FUG) equations. Established short-cut models, commonly known as the FUG method, represent the separation performance of a simple distillation column. The FUG consists of three main steps, as described in Seader et al. (2006, Chap. 9). See slide 15. Suphanit (1999) and Gadalla (2003) developed grassroots and retrofit short-cut models based on the Fenske-Underwood and Gilliland methods. Rastogi (2006) extended the short-cut models to account for pressure drop and pump-around locations. Short-cut models for vacuum units have also been developed. Chen (2008) extended the work of Rastogi (2006) to account for the effect of the pump-around location on the separation performance. Chen, L. (2008). Heat-integrated Crude Oil Distillation Design. Ph. D. thesis, University of Manchester, Manchester. Gadalla, M. (2003). Retrofit of Heat Integrated Crude Oil Distillation Systems. Ph. D. thesis, University of Manchester Institute of Science and Technology, Manchester. Rastogi, V. (2006). Heat-Integrated Crude Oil Distillation System Design. Ph. D. thesis, University of Manchester, Manchester. Seader, J. D., E. J. Henley, and D. K. Roper (2006). Separation Process Principles. Wiley. Suphanit, B. (1999). Design of Complex Distillation Systems. Ph. D. thesis, University
15 The FUG consists of three main steps, as described in Seader et al. (2006, Chap. 9) 1. Minimum reflux condition. Given the feed condition and the recoveries of the light and heavy key components, the Underwood equations predict the minimum vapor and distillate flow rates at minimum reflux condition. 2. Total reflux condition. The equation developed by Fenske (1932, cited in Seader et al. 2006), calculates the total reflux condition in the simple column and the minimum number of stages required to perform the specified separation, given the relative volatilities of the key components. This equation can be rearranged to determine the distribution of components between the distillate and bottom product for a reflux ratio greater than its minimum value. 3. Actual reflux condition. Gilliland (1940, cited in Seader et al. 2006) developed a graphical method to calculate the actual reflux ratio and the total number of theoretical stages for a specified separation. The Kirkbride correlation relates the key components compositions in the feed and products, and product flow rates to determine the feed stage location. In the case of reboiled columns, the Kirkbride correlation is used to calculate the number of stages in the rectifying and stripping sections. In the case of steam stripped columns, the stripping section is modelled by consecutive flash calculations from the bottom to the feed stage. Suphanit (1999) extended and modified the FUG method to overcome the assumption of constant molar overflow in the column and to apply the model to
16 Since simplified models require the specification of key components and their recoveries, Gadalla (2003) presented a procedure to transform traditional product specifications of crude oil distillation columns into key components and their recoveries in each column section. Chen (2008) modified the procedure proposed by Gadalla (2003) and developed a methodology for systematically selecting key components and their recoveries as a function of product flow rates and TBP specifications. Chen, L. (2008). Heat-integrated Crude Oil Distillation Design. Ph. D. thesis, University of Manchester, Manchester. Gadalla, M. (2003). Retrofit of Heat Integrated Crude Oil Distillation Systems. Ph. D. thesis, University of Manchester Institute of Science and Technology, Manchester.
17
18 An example of a heat-integrated atmospheric distillation column is presented to show the interactions between distillation column and heat exchanger network (HEN). For example, if the flow rate or temperature drop of one of the pump-arounds is increased, then there is more energy to recover in the preheat train. The furnace duty for preheating the crude oil is decreased. This improves the energy recovery in the atmospheric column, but at the same time reduces the reflux ratio in the distillation column, which reduces the separation performance of the distillation column. If the stripping steam at the bottom of the column is decreased, the temperature of the bottom product increases. Hence, the heat recovery from this product can increase. Thus, there is a need to consider the distillation column and HEN together in one framework, so that these interactions can be exploited for improving the overall performance of the system. Chen, L., Jobson, M., and Smith, R. (2008). Heat-integrated Crude Oil Distillation System Design. In PIRC Annual Research Meeting Centre for Process Integration.
19 The heat exchanger network (HEN) models of Rodriguez (2005) are modified and incorporated into the crude oil distillation system to account for detailed modelling of HEN. The HEN is represented by a set of unique nodes on each stream. The HEN consists of process heat exchangers, utility heat exchangers, streams bypass and stream splitters. Multi-segments stream data are implemented to consider varying heat capacities in design and analysis of HENs. All model equations are solved sequentially to calculate streams' node temperatures. Chen, L., Jobson, M., and Smith, R. (2008). Heat-integrated Crude Oil Distillation System Design. In PIRC Annual Research Meeting Centre for Process Integration. Rodriguez, C. A., Fouling mitigation strategies for heat exchanger networks, PhD Thesis, The University of Manchester, UK (2005)
20 The optimisation framework developed by Chen (2008) is shown in this slide, which employs simulated annealing as the optimisation algorithm and considers existing distillation system and HEN conditions, by adding product specification constraints, hydraulic constraints, maximum number of new exchangers etc. The atmospheric distillation column is simulated using simplified models. Chen, L. (2008). Heat-integrated Crude Oil Distillation Design. Ph. D. thesis, University of Manchester, Manchester.
21
22 Crude oil distillation units are complex structures with strong interactions between their components. Rigorous and simplified models have been employed to represent the separation performance of these structures and numerous applications for design and optimisation can be found in the literature. In general, rigorous and simplified models implement equilibrium, mass and energy equations to calculate the energy requirements and separation performance of the distillation column. A considerable number of equations need to be provided to calculate the distribution of each component in the complex distillation column, these equations are highly non-linear and solutions can be compromised. Statistical models have the advantages of overcoming converge problems presented in rigorous and simplified models, handling smaller number of variables and performing calculations in less time, at the expense of substituting physical principles for stochastic relations. The main advantage of statistical models, such as Artificial Neural Networks (ANNs) consists in their capability of capturing complex relationships between great number of variables. They allow the designer to easily model systems that are often nonlinear, with strong interactions between their elements, such as CDUs. Another advantage is that they can build models from real plant data and are self-adapting to new information. Nevertheless, because ANNs are constructed using stochastic relations, their performance is entirely dependent on the quality of the information supplied to build the model, that is, the ANN is as good as the data used to represent the system.
23 Artificial neural networks (ANN) are statistical data modelling tools inspired by the structure of biological neural networks, and have been widely used in modelling industrial processes (Beale et al., 2011). Artificial neural networks are adaptive nonlinear statistical data modelling tools consisting of a large group of interconnected neurons organised into layers. An ANN modify its structure depending on the information that is provided during the learning phase. The figure shows the structure of an ANN. The network comprises three elements, namely the inputs, outputs and hidden layers. Each layer contains nodes, represented as circles, the nodes of the hidden layer are also called neurons. Beale, M. H., M. T. Hagan, and H. B. Demuth (2011). Neural Network Toolbox Getting Started Guide. The MathWorks, Inc.
24 Motlaghi et al. (2008) used an ANNs model to simulate the crude oil distillation column. Product flow rates were optimised by their commercial importance with a genetic algorithm method. Only product flow rates were set as product quality specifications; properties such as product cut points and densities were not considered. No integration of the process streams was made, and hydraulic constraints were not considered. In the work of Liau et al. (2004), an ANN model was built to simulate a crude oil distillation column. An optimisation problem was solved to determine the operating conditions that produce better product yields under the required product specifications. The effect of the operating conditions on ASTM D86 product cut points was investigated using a design of experiments method. Only crude oil feed temperature and product flow rates were considered as degrees of freedom for optimisation. The energy efficiency of the column was not included in the optimisation frame. ASTM D86 cut points were used to specify product quality. Liau, L. C.-K., T. C.-K. Yang, and M.-T. Tsai (2004, February). Expert system of a crude oil distillation unit for process optimization using neural networks. Expert Systems with Applications 26(2), Motlaghi, S., F. Jalali, and M. Ahmadabadi (2008, November). An expert system design for a crude oil distillation column with the neural networks model and the process optimization using genetic algorithm framework. Expert Systems with Applications 35(4),
25 The figure illustrates the mathematical representation of these layers. p is a vector of R inputs; W is a matrix of weights that connects each input with each of the S neurons. The i-th neuron summates the weighted inputs and biases b to build the n(i) scalar output. Finally, the vector n is scaled to form the output vector a. Beale, M. H., M. T. Hagan, and H. B. Demuth (2011). Neural Network Toolbox Getting Started Guide. The MathWorks, Inc.
26 The weights W and biases b required to make a neural network predict the outputs for given inputs, are calculated by a learning algorithm, together with samples of how the system should operate. The learning algorithm is an optimisation problem where the weights and biases are calculated in order to minimise the error between the ANN model output a and the outputs from the supplied data. The optimisation process is also called training. Beale, M. H., M. T. Hagan, and H. B. Demuth (2011a). Neural Network Toolbox Getting Started Guide. The MathWorks, Inc.
27 The transfer function f converts the weighted input of a neuron to its output a. The transfer function is typically a step, linear or a sigmoid function The step function limits the output to be either one or zero, and is regularly used to make classification decisions. The linear transfer function is used as a linear approximator. On the other hand, the sigmoid transfer function is used when training the network using backpropagation methods (gradient descent optimisation training style). Beale, M. H., M. T. Hagan, and H. B. Demuth (2011a). Neural Network Toolbox Getting Started Guide. The MathWorks, Inc.
28 In this work, an ANN model for representing the crude oil distillation column is constructed using samples generated from rigorous model simulations. Then, the new model is implemented in the optimisation frame. The optimisation problem that considers the heat-integrated column is solved using a SA algorithm. The procedure for modelling the crude oil distillation column is presented below. 1. A representative number of samples is generated from rigorous model simulations. The independent variables, also called inputs, are the degrees of freedom for optimisation of the heat-integrated system. The inputs are randomly varied through different simulations from their upper and lower feasible values. The values of the dependent variables, also called outputs of the ANN, are determined and registered. 2.The transfer function and number of neurons of the ANN are defined. Also, the distribution of samples used for training, validating and testing the network must be supplied. Usually, the number of neurons is 10% the number of samples used to train the network (Beale et al., 2011). 3. Once the method for training the network is selected, the data generated from step 1 is used to train the ANN model. The values of the weights and biases are determined during this stage. The ANN toolbox embedded in MATLAB is used to perform such calculations. Beale, M. H., M. T. Hagan, and H. B. Demuth (2011). Neural Network Toolbox User s
29 This example shows how a simple ANN model can be constructed. First, it is necessary to identify the independent (inputs) and dependent (outputs) variables of the model to be constructed. For this simple case, the input variables are pumparound duties (Q PA ) and temperature drops (ΔT PA ). The output variables are the condenser and reboiler duties (Q COND, Q HN-REB, Q LN-REB ); and pump-around supply temperatures (T SPA )
30 The inputs (Q PA s, ΔT PA s) and outputs (Q COND, Q HN-REB, Q LN-REB, T SPA s) are considered to build the ANN structure. Thus, the ANN consists of six p inputs and six a outputs. For this example, five hundred samples are used to train the network, therefore, the number of neurons is set to fifty (S=50).
31 To obtain the ANN model, a number of five hundred samples were generated in ASPEN HYSYS. The inputs, pump-around duties and temperature drops were randomly varied within their maximum and minimum feasible values for every simulation performed. The outputs, that is, the conditions of the process streams that are used in the heat-integration and are affected by these changes, were calculated using the mentioned rigorous models. The ANN was defined in the ANN Toolbox in MATLAB. A neural network consisting of fifty neurons and a linear transfer function was trained using the samples previously obtained. Seventy per cent of the samples were used to train the network, fifteen per cent were used for validation, and the rest for testing the performance of the neural network. (See notes on Slide 28 for more information about the procedure)
32 The comparison of the ANN model predictions against the supplied data is illustrated in Slides 32 and 33. The correlation coefficient of the predicted outputs to the actual ones is R = 1. This means that the ANN model is in good agreement with the rigorous model.
33 The comparison of the ANN model predictions against the supplied data is illustrated in this slide. The correlation coefficient of the predicted outputs to the actual ones is R = 1.
34 An ANN model has been built to simulate the crude oil distillation column. This model will be employed to perform optimisation of the column operational variables to increase valuable product yield and reduce energy consumption. During the column optimisation, energy requirements will be determined using the Grand Composite Curve (GCC), to account for heat integration (see Section 4 and Case study 5.1). Later, new stream data resulting from the optimisation of the column is passed to its existing Heat Exchanger Network (HEN), the HEN is optimised separately (see Section 4 and Case study 5.2).
35
36 In this work, an ANN model for representing the crude oil distillation column is constructed using samples generated from rigorous model simulations. Then, the new model is implemented in the optimisation frame. The optimisation problem that considers the heatintegrated column is solved using a SA algorithm. Once the column optimisation is carried out, the process stream information is passed to the HEN, and the HEN is optimised separately also employing a SA algorithm.
37 Once the column optimisation is carried out, the process stream information is passed to the HEN, and the HEN is optimised separately using the methodology proposed by Rodriguez (2005) and Chen (2008). Chen, L., Jobson, M., and Smith, R. (2008). Heat-integrated Crude Oil Distillation System Design. In PIRC Annual Research Meeting Centre for Process Integration. Rodriguez, C. A. (2005), Fouling mitigation strategies for heat exchanger networks, PhD Thesis, The University of Manchester, UK.
38 This slide describes the optimisation approaches for the distillation column and HEN presented in this work. Chen, L., Jobson, M., and Smith, R. (2008). Heat-integrated Crude Oil Distillation System Design. In PIRC Annual Research Meeting Centre for Process Integration. Rodriguez, C. A. (2005), Fouling mitigation strategies for heat exchanger networks, PhD Thesis, The University of Manchester, UK.
39 This slide describes the optimisation approaches for the distillation column and HEN presented in this work.
40 This slide shows the data employed in the illustrative example. The objective of this example is to determine the best pump-around duties and temperature drops that reduce utilities costs for a fixed distillation column structure and product flow rates.
41 This example employs the ANN model previously built in the example from Section 3. The comparison of the ANN model predictions against the supplied data is illustrated in Slide 33. The correlation coefficient of the predicted outputs to the actual ones is R = 1. The new model was implemented in the optimisation procedure described in Slide 36. The objective function was the minimisation of hot and cold utility targets costs. Since product flow rates remain constant, no considerable variations in the TBP point temperatures or densities are expected; therefore, these properties are not included as constraints in the optimisation problem.
42 Results from the optimised example are shown in this slide. Although the operating costs calculated based on the GCC were considerably reduced from 7.45 MM$/y to 6.56 MM$/y, their impact to the total process economy is relatively small. Other elements involved in the calculation of overall profit, namely crude oil cost and product profit, are several orders of magnitude greater than the utilities costs determined in this example. If it is assumed that overall annual profit is equal to product profit minus crude oil costs and operating costs, then: Total profit (MM$/y) = This represents a 55% contribution of the product income to the overall profit equation, 45% for crude oil costs and only a 0.1% contribution for operating costs. This statement supports the decision of including product yields as optimisation variables in the new design methodology.
43
44
45 To illustrate the influence of modifying the products yields on the distillation process energy performance, consider an atmospheric crude oil distillation unit that processes 100,000 bbl/day (2610 kmol/h) of crude oil at 25 o C and 3 bar into five products: light naphtha (LN), heavy naphtha (HN), light distillate (LD), heavy distillate (HD), and residue (RES). Steam at 4.5 bar and 260 o C is used as a stripping agent. The crude oil distillation system is composed of the preheat train and the main tower, one condenser, three pump-arounds and three side strippers, as shown in this slide. The stages distribution of the column and pump-around specifications remain fixed and are presented in Slides 46 and 47. The crude oil to be processed is Tia Juana Light crude (Venezuela) (Watkins, 1979), the true boiling point curve is shown in this slide. The assay is cut in 25 pseudocomponents using the oil characterization technique embedded in Aspen HYSYS. Watkins, R. N. (1979). Petroleum Refinery Distillation (2 ed.). Texas: Gulf Publishing Company.
46 Distillation column configuration and number of stages.
47 Base case data Product flow rates and specifications, utility costs (Chen, 2008) Product prices based on crude oil price of 2010 ( and calculated using the procedure presented by Maples (2000) Chen, L. (2008). Heat-integrated Crude Oil Distillation Design. Ph. D. thesis, University of Manchester, Manchester. Maples, R. E. (2000). Petroleum Refining Process Economics, 2nd edition, Pennwell Corp.
48
49 The objective of Case Study 5.1 is to optimise product yields and operating conditions in order to improve overall profit while keeping product quality within specified limits. In this case study, product yields are allowed to change. Consequently, product properties, temperatures and heat capacities of more streams will be affected, compared to the illustrative example. The ANN model should be able to represent such trade-offs. The energy consumption is calculated using the Gran Composite Curve (GCC), no HEN details are taken into account yet, these will be considered in Case Study 5.2
50 This slide shows the optimisation variables for Case Study 5.1 and 5.2 and their minimum and maximum allowed values. These values were determined based on the feasible scenarios simulated in HYSYS.
51 The inputs of the ANN consist of pump-around duties, pump-around temperature drops and molar flow rates of LN, HN, LD, HD streams (10 inputs). The inputs are randomly varied through every sample and the effect on the outputs is registered. The outputs consist of temperatures, heat capacity flow rates of all process streams involved in the energy targets calculations; condenser and reboilers duties and finally, T5%, T50% and T95% temperatures of every distillation product (42 outputs). An ANN of sixty neurons and a linear transfer function is defined. The neural network is trained using the data previously generated. Seventy per cent of the samples were used to train the network, fifteen per cent were used for validation, and the rest for testing the performance of the neural network. The comparison of the ANN model predictions against the supplied data is illustrated in Slide 52. The correlation coefficient of the predicted outputs to the actual ones is R = 1.
52 This slide shows the ANN predictions compared to rigorous model calculations for some outputs. ANN model is in good agreement with rigorous model. The correlation coefficient of the overall predicted outputs to the actual ones is R = 1.
53 This slide shows the optimisation results for product flow rates and T5%, T50% and T95% specifications. The objective function for this Case Study is the maximisation of the overall profit, defined as product income minus crude oil costs and operating costs (calculated using the GCC). Constraints of ±10 o C are imposed to the product T5%, T50% and T95% temperatures. Upper and lower bounds of the optimisation variables are also included in the problem formulation. Results show that the flow rates of the three most valuable products are increased (LN, LD, HD) at the expense of the least valuable ones (HN, RES). The product specifications are within allowable limits.
54 This slide shows the results of the optimised Case Study 5.1. The values of the pumparound duties, temperature drops, minimum hot and cold utility consumption and their related costs are shown in this slide.
55 The summary of profit improvement is presented in this slide, results show an overall improvement of 17.6 MM$/y, which represents an increase of 144% from the base case. The major contribution is made by a 0.7% increase product income, followed by a 12% reduction in utility consumption. In this stage, the designer can identify the potential for economic benefits and the degree of modifications in the operating conditions of the column. However, since the HEN details are not considered in this case study, the economic investment necessary to adjust the HEN to new operating conditions is not included. Moreover, real utility consumption and its cost can not be determined if the HEN details are not taken into account.
56
57
58 This slide shows the base case HEN to be optimised.
59 Once the column optimisation is carried out, the process stream information is passed to the HEN, and the HEN is optimised separately using the methodology proposed by Rodriguez (2005) and Chen (2008), see Slide 36 for more information. Chen, L. (2008). Heat-integrated Crude Oil Distillation Design. Ph. D. thesis, University of Manchester, Manchester. Rodriguez, C. A., Fouling mitigation strategies for heat exchanger networks, PhD Thesis, The University of Manchester, UK (2005)
60 This slide shows details of the methodologies employed to optimise the column (first) and the HEN (after column optimisation)
61 Optimised distillation results from Case study 5.1 to be used in the HEN optimisation in Case study 5.2
62 Optimised HEN. Additional area of 144 m 2 is necessary to process streams for the column new operating conditions.
63 Summary of HEN modifications. Additional area of 144 m 2 is necessary to process streams for the column new operating conditions. Results show a small decrease in utility costs, but also a small investment in performing HEN modifications. The equations for calculating heat exchanger modification costs are taken from Chen (2008): Exchanger additional area ($): 1530 x (additional area) 0.63 New exchanger unit ($): x (exchanger area) 0.63 Exchanger repiping ($): Exchanger resequencing ($): year payback Chen, L. (2008). Heat-integrated Crude Oil Distillation Design. Ph. D. thesis, University of Manchester, Manchester.
64 Summary of results
65 This slide presents the comparison between results with and without HEN details consideration (Case 5.1 and 5.2, respectively). Compared to the base case, both optimised cases present improvements in overall distillation system profit. Nevertheless, the utility consumption calculated with the Grand Composite Curve (GCC) is considerably different from the utility consumption considering HEN details. For this reason, the optimisation of the distillation system should consider both the column and HEN details simultaneously.
66 This approach is considered to be developed in the future to avoid calculation differences in utility consumption.
67
68
69
70
71
OPTIMISATION OF EXISTING HEAT-INTEGRATED REFINERY DISTILLATION SYSTEMS
OPTIMISATION OF EXISTING HEAT-INTEGRATED REFINERY DISTILLATION SYSTEMS Mamdouh Gadalla, Megan Jobson and Robin Smith Department of Process Integration, UMIST, Manchester, UK ABSTRACT Existing refinery
More informationA New Optimisation-based Design Methodology for Energyefficient Crude Oil Distillation Systems with Preflash Units
A publication of CHEMICAL ENGINEERING TRANSACTIONS VOL. 69, 2018 Guest Editors: Elisabetta Brunazzi, Eva Sorensen Copyright 2018, AIDIC Servizi S.r.l. ISBN 978-88-95608-66-2; ISSN 2283-9216 The Italian
More informationA New Optimisation Based Retrofit Approach for Revamping an Egyptian Crude Oil Distillation Unit
Available online at www.sciencedirect.com ScienceDirect Energy Procedia 36 (2013 ) 454 464 TerraGreen 13 International Conference 2013 - Advancements in Renewable Energy and Clean Environment A New Optimisation
More informationThe Use of Reduced Models in the Optimisation of Energy Integrated Processes
A publication of CHEMICAL ENGINEERING TRANSACTIONS VOL. 35, 2013 Guest Editors: Petar Varbanov, Jiří Klemeš, Panos Seferlis, Athanasios I. Papadopoulos, Spyros Voutetakis Copyright 2013, AIDIC Servizi
More informationIndustrial Application of Surrogate Models to Optimize Crude Oil Distillation Units
A publication of CHEMICAL ENGINEERING TRANSACTIONS VOL. 69, 2018 Guest Editors: Elisabetta Brunazzi, Eva Sorensen Copyright 2018, AIDIC Servizi S.r.l. ISBN 978-88-95608-66-2; ISSN 2283-9216 The Italian
More informationInvestigation of Heat Exchanger Network Flexibility of Distillation Unit for Processing Different Types of Crude Oil
A publication of CHEMICAL ENGINEERING TRANSACTIONS VOL. 35, 2013 Guest Editors: Petar Varbanov, Jiří Klemeš, Panos Seferlis, Athanasios I. Papadopoulos, Spyros Voutetakis Copyright 2013, AIDIC Servizi
More informationHeat Exchanger Network Retrofit through Heat Transfer Enhancement
Heat Exchanger Network Retrofit through Heat Transfer Enhancement Yufei Wang, Robin Smith*, Jin-Kuk Kim Centre for Process Integration, School of Chemical Engineering and Analytical Science, The University
More informationGTC TECHNOLOGY. GT-UWC SM How a Uniting Wall Column Maximizes LPG Recovery. Engineered to Innovate WHITE PAPER
GTC TECHNOLOGY GT-UWC SM How a Uniting Wall Column Maximizes LPG Recovery WHITE PAPER Engineered to Innovate Maximizing LPG Recovery from Fuel Using a Uniting Wall Column Refiners have a challenge to recover
More informationRETROFIT DESIGN OF HEAT-INTEGRATED CRUDE OIL DISTILLATION SYSTEMS
RETROFIT DESIGN OF HEAT-INTEGRATED CRUDE OIL DISTILLATION SYSTEMS A thesis submitted to the University of Manchester Institute of Science and Technology for the degree of Doctor of Philosophy by Mamdouh
More informationSYNTHESIS AND OPTIMIZATION OF DEMETHANIZER FLOWSHEETS FOR LOW TEMPERATURE SEPARATION PROCESSES
Distillation Absorption 2010 A.B. de Haan, H. Kooijman and A. Górak (Editors) All rights reserved by authors as per DA2010 copyright notice SYNTHESIS AND OPTIMIZATION OF DEMETHANIZER FLOWSHEETS FOR LOW
More informationFlash Zone Optimization of Benzene-Toluene-Xylene Fractionation Unit
2 nd International Conference on Engineering Optimization September 6-9, 2010, Lisbon, Portugal Flash Zone Optimization of Benzene-Toluene-Xylene Fractionation Unit M. Arjmand 1, K. Motahari 2 1 School
More informationProcess Integration in Petroleum Refineries
Process Integration in Petroleum Refineries - A Perspective and Future Trends Robin Smith University of Manchester 1 Centre for Process Integration 2017 Outline 1. Background 2. Heat Recovery in Crude
More informationEnergy Saving in Atmospheric Distillation Unit by Retrofit Design of Heat Exchanger Networks of Al Basra Refinery
Energy Saving in Atmospheric Distillation Unit by Retrofit Design of Heat Exchanger Networks of Al Basra Refinery Adnan A. Ateeq Engineering Technical College Southern Technical University Basra, Iraq
More informationGT-LPG Max SM. Maximizing LPG Recovery from Fuel Gas Using a Dividing Wall Column. Engineered to Innovate
GTC Technology White Paper GT-LPG Max SM Maximizing LPG Recovery from Fuel Using a Dividing Wall Column Engineered to Innovate GT-LPG Max SM Maximizing LPG Recovery from Fuel Using a Dividing Wall Column
More informationOptimisation of Heat-integrated Distillation Schemes Based on Shortcut Analysis, Pinch Analysis and Rigorous Simulation. Abstract
Optimisation of Heat-integrated Distillation Schemes Based on Shortcut Analysis, Pinch Analysis and Rigorous Simulation Mansour Emtir* and Mansour Khalifa Libyan Petroleum Institute, P.O. Box 6431 Tripoli,
More informationDistillation DEPARTMENT OF CHEMICAL ENGINEERING
Distillation DEPARTMENT OF CHEMICAL ENGINEERING 2 3 Weeping in distillation column 4 Distillation. Introduction Unit operation Separation process A feed mixture of two or more components is separated into
More informationResearcher, 1(2), 2009, Energy Integration Of Crude Distillation Unit Using Pinch Analysis
Energy Integration Of Crude Distillation Unit Using Pinch Analysis K.R. AJAO (Ph.D) Department of Mechanical Engineering, University of Ilorin, Ilorin, Nigeria e-mail: ajaomech@unilorin.edu.ng H. F. Akande
More informationJournal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 4(5): (ISSN: )
Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 4(5): 731-736 Scholarlink Research Institute Journals, 2013 (ISSN: 2141-7016) jeteas.scholarlinkresearch.org Journal of Emerging
More informationModeling and Control of a Multi-Component Continuous Crude Distillation Column Using LabVIEW
Modeling and Control of a Multi-Component Continuous Crude Distillation Column Using LabVIEW CH. Suresh Kumar 1, Mohammed Wajid Ali 2 Assistant Professor, Dept. of EIE, VNR Vignana Jyothi Institute of
More informationInternational Journal of Pure and Applied Sciences and Technology
Int. J. Pure Appl. Sci. Technol., 12(2) (212), pp. 8-19 International Journal of Pure and Applied Sciences and Technology ISSN 2229-617 Available online at www.ijopaasat.in Research Paper Using Simulation
More informationRetrofit for a Gas Separation Plant by Pinch Technology
Retrofit for a Gas Separation Plant by Pinch Technology Napredakul, D. a, Siemanond, K.a, Sornchamni, T.b, Laorrattanasak, S.b a The Petroleum and Petrochemical College, Chulalongkorn University, Bangkok,
More informationRefining Scheduling of Crude Oil Unloading, Storing, and Processing Considering Production Level Cost
20 th European Symposium on Computer Aided Process Engineering ESCAPE20 S. Pierucci and G. Buzzi Ferraris (Editors) 2010 Elsevier B.V. All rights reserved. Refining Scheduling of Crude Oil Unloading, Storing,
More informationEmission-Reductive and Multi-Objective Coordinative Optimization of Binary Feed for Atmospheric and Vacuum Distillation Unit
Simulation and Optimization China Petroleum Processing and Petrochemical Technology 2017, Vol. 19, No. 4, pp 101-112 December 30, 2017 Emission-Reductive and Multi-Objective Coordinative Optimization of
More informationMulti-effect distillation applied to an industrial case study
Chemical Engineering and Processing 44 (2005) 819 826 Multi-effect distillation applied to an industrial case study Hilde K. Engelien, Sigurd Skogestad Norwegian University of Science and Technology (NTNU),
More informationCrude Tower Simulation HYSYS v10
Crude Tower Simulation HYSYS v10 Steps to set up a simulation in HYSYS v10 to model a crude tower system consisting of: Crude Oil Preheat Train Atmospheric Crude Tower Vacuum Crude Tower Debutanizer to
More informationNew Conceptual Design Methodology for a Concentric Heat Integrated Distillation Column (HIDiC)
A publication of CHEMICAL ENGINEERING TRANSACTIONS VOL. 69, 218 Guest Editors: Elisabetta Brunazzi, Eva Sorensen Copyright 218, AIDIC Servizi S.r.l. ISBN 978-88-9568-66-2; ISSN 2283-9216 The Italian Association
More informationDIVIDING WALL COLUMN REVAMP OPTIMISES MIXED XYLENES PRODUCTION
DIVIDING WALL COLUMN REVAMP OPTIMISES MIXED XYLENES PRODUCTION Bernie Slade 1, Berne Stober 1 and Dave Simpson 2 1 ExxonMobil, E-mail: bernie.slade@exxonmobil.com/berne.k.stober@exxonmobil.com 2 Koch-Glitsch,
More informationMemoranda On Front-end Crude Fractionation.
VtÜÜV{xÅ \ÇvA 718.325.3307Tel, 718.325.5225 Fax ADMIN@CARRCHEM.COM Memoranda On Front-end Crude Fractionation. ATMOSPHERIC STILL PETROLEUM SEPARATION GLOBAL MATERIAL BALANCE & OPTIMAL UTILITY (HEATER AND
More informationEvaluating the Potential of a Process Site for Waste Heat Recovery
1069 A publication of CHEMICAL ENGINEERING TRANSACTIONS VOL. 39, 2014 Guest Editors: Petar Sabev Varbanov, Jiří Jaromír Klemeš, Peng Yen Liew, Jun Yow Yong Copyright 2014, AIDIC Servizi S.r.l., ISBN 978-88-95608-30-3;
More informationEnergy Conservation and Optimization in Condensate Splitter Plant
A publication of CHEMICAL ENGINEERINGTRANSACTIONS VOL. 35, 2013 Guest Editors:PetarVarbanov, JiříKlemeš,PanosSeferlis, Athanasios I. Papadopoulos, Spyros Voutetakis Copyright 2013, AIDIC ServiziS.r.l.,
More informationOverview of pinch analysis and its application in hydrocarbon Industries
National Seminar on Awareness and Implementation of Energy Management System Overview of pinch analysis and its application in hydrocarbon Industries 19t h January- 2015 SCOPE Conversion centre, Lodhi
More informationModification of Preheating Heat Exchanger Network in Crude Distillation Unit of Arak Refinery Based on Pinch Technology
Modification of Preheating Heat Exchanger Network in Crude Distillation Unit of Arak Refinery Based on Pinch Technology Salomeh Chegini, Reza Dargahi, Afshin Mahdavi Abstract In this work, the Hint software
More informationCONTROL OF CRUDE FRACTIONATOR PRODUCT QUALITIES DURING FEEDSTOCK CHANGES BY USE OF A SIMPLIFIED HEAT BALANCE
Petrocontrol Advanced Control & Optimization CONTROL OF CRUDE FRACTIONATOR PRODUCT QUALITIES DURING FEEDSTOCK CHANGES BY USE OF A SIMPLIFIED HEAT BALANCE Y. Zak Friedman, PhD Principal Consultant Paper
More informationEnergy Optimisation Of Upstream Separation And Stabilisation Plant Using Pinch Technology
Energy Optimisation Of Upstream Separation And Stabilisation Plant Using Pinch Technology Ritesh Sojitra Srashti Dwivedi ITM University, Gwalior, India Abstract: Energy optimisation and process integration
More informationDynamics and Control Simulation of a Debutanizer Column using Aspen HYSYS
Dynamics and Control Simulation of a Debutanizer Column using Aspen HYSYS S. Karacan 1, F. Karacan 2 1 Ankara University, Engineering Faculty, Department of Chemical Engineering, Tandogan 06100, Ankara,
More informationAPPLYING THE HEAT INTEGRATION IN ORDER TO ENVIRONMENTAL POLLUTANTS MINIMIZATION IN DISTILLATION COLUMNS
Iran. J. Environ. Health. Sci. Eng., 6, Vol. 3, No. 4, pp. 73-84 APPLYING THE HEAT INTEGRATION IN ORDER TO ENVIRONMENTAL POLLUTANTS MINIMIZATION IN DISTILLATION COLUMNS * A. H. Javid, A. Emamzadeh, 3 A.
More informationRaymond A. Adomaitis. March 7, 2012
Raymond A. Adomaitis March 7, 2012 To be covered: Class syllabus (http://www.isr.umd.edu/ adomaiti/ench446), grading Team selection (4 members per team) Initial project description Approximate schedule
More informationA Simple Application of Murphree Tray Efficiency to Separation Processes
Page 1 of 8 A Simple Application of Murphree Tray Efficiency to Separation Processes J.J. VASQUEZ-ESPARRAGOZA, J.C. POLASEK, V.N. HERNANDEZ-VALENCIA, M.W. HLAVINKA, Bryan Research & Engineering, Inc.,
More informationTHE EFFECT OF PRESSURE ON DYNAMICS AND CONTROL OF SIDESTREAM DISTILLATION COLUMNS
Vol-2, Issue-3 PP. 63-612 ISSN: 2394-5788 THE EFFECT OF PRESSURE ON DYNAMICS AND CONTROL OF SIDESTREAM DISTILLATION COLUMNS S.R.Dantas, R.M.L.Oliveira, W.B.Ramos, G.W. Farias Neto & R. P. Brito Federal
More informationHeat Exchanger Network Optimization using integrated specialized software from ASPENTECH and GAMS Technology.
EngOpt 2012 3 rd International Conference on Engineering Optimization Rio de Janeiro, Brazil, 01-05 July 2012. Heat Exchanger Network Optimization using integrated specialized software from ASPENTECH and
More informationNEW RECYCLE PROCESS SCHEME FOR HIGH ETHANE RECOVERY NEW PROCESS SCHEME FOR HIGH NGL RECOVERY INTRODUCTION. Abstract PROCESS FUNDAMENTALS
Author: Jorge Foglietta, ABB Randall Corporation Tel (713) 821-4313, Fax (713) 821-3544 Mailing Address: Randall Division ABB Lummus Global Inc. P.O. Box 420087 Houston, Texas 77242-0087 NEW PROCESS SCHEME
More informationAchieving Process Energy Efficiency via Innovation Honeywell. All rights reserved.
Achieving Process Energy Efficiency via Innovation 2010 Honeywell. All rights reserved. Agenda Why focus on Refining/Petrochemical for reducing CO 2? How can innovation help to reduce energy/co 2? Real
More informationHeat Exchanger Network Retrofit Comparison. Trevor Hallberg and Sarah Scribner
Heat Exchanger Network Retrofit Comparison Trevor Hallberg and Sarah Scribner Table of Contents Executive Summary... 4 Introduction... 5 Paper Overview... 6 Example 1... 7 Example 2... 9 1. Mixed Integer
More informationIntroduction to Pinch Technology
Downloaded from orbit.dtu.dk on: Oct 07, 2018 Introduction to Pinch Technology Rokni, Masoud Publication date: 2016 Document Version Peer reviewed version Link back to DTU Orbit Citation (APA): Rokni,
More informationDesign of Crude Distillation Plants with Vacuum Units. II. Heat Exchanger Network Design
6100 Ind. Eng. Chem. Res. 2002, 41, 6100-6106 Design of Crude Distillation Plants with Vacuum Units. II. Heat Exchanger Network Design Shuncheng Ji and Miguel Bagajewicz* School of Chemical Engineering
More informationSteam balance optimisation strategies
Steam balance optimisation strategies Publicado en Chemical Engineering, Noviembre 2002 Background Optimising a steam balance in a plant with several steam mains pressures is not always a simple intuitive
More informationHYSYS WORKBOOK By: Eng. Ahmed Deyab Fares.
HYSYS WORKBOOK 2013 By: Eng. Ahmed Deyab Fares eng.a.deab@gmail.com adeyab@adeyab.com Mobile: 002-01227549943 - Email: adeyab@adeyab.com 1 Flash Separation We have a stream containing 15% ethane, 20% propane,
More informationImprovement of distillation column efficiency by integration with organic Rankine power generation cycle. Introduction
Improvement of distillation column efficiency by integration with organic Rankine power generation cycle Dmitriy A. Sladkovskiy, St.Petersburg State Institute of Technology (technical university), Saint-
More informationExercise 5. Simulation of HDA plant in UniSim
Process Systems Engineering Prof. Davide Manca Politecnico di Milano Exercise 5 Simulation of HDA plant in UniSim Lab assistant: Adriana Savoca Davide Manca Process Systems Engineering Politecnico di Milano
More informationRetrofit of Refinery Heat Exchanger Network under Different Kinds of Crude Oil by Pinch Design Method using Mathematical Programming
A publication of 1411 CHEMICAL ENGINEERING TRANSACTIONS VOL. 32, 2013 Chief Editors: Sauro Pierucci, Jiří J. Klemeš Copyright 2013, AIDIC Servizi S.r.l., ISBN 978-88-95608-23-5; ISSN 1974-9791 The Italian
More informationHydrogen Integration in Petroleum Refining
A publication of CHEMICAL ENGINEERING TRANSACTIONS VOL. 29, 2012 Guest Editors: Petar Sabev Varbanov, Hon Loong Lam, Jiří Jaromír Klemeš Copyright 2012, AIDIC Servizi S.r.l., ISBN 978-88-95608-20-4; ISSN
More informationTABLE OF CONTENT
Page : 1 of 28 Project Engineering Standard www.klmtechgroup.com KLM Technology #03-12 Block Aronia, Jalan Sri Perkasa 2 Taman Tampoi Utama 81200 Johor Bahru Malaysia TABLE OF CONTENT 1.0 INTRODUCTION
More informationDETERMINING THE MAXIMUM LNG PRODUCTION RATE BY PROCESS SIMULATION MODELLING OF LOW TEMPERATURE NATURAL GAS SEPARATION UNIT
DETERMINING THE MAXIMUM LNG PRODUCTION RATE BY PROCESS SIMULATION MODELLING OF LOW TEMPERATURE NATURAL GAS SEPARATION UNIT Ewa Ciesielczyk, Oil and Gas Institute, Kraków, Poland Jan Rudnicki, Branch of
More informationGrand Composite Curve Module 04 Lecture 12
Module 04: Targeting Lecture 12: Grand Composite Curve While composite curves provide overall energy targets, these do not indicate the amount of energy that should be supplied at different temperature
More informationMulti Stage Flash Desalination with Direct Mixing Condensation
Multi Stage Flash Desalination with Direct Mixing Condensation Andrea Cipollina*, Giorgio Micale, Salvatore Noto, Alberto Brucato Dipartimento di Ingegneria Chimica Gestionale Informatica Meccanica, Università
More informationTwo examples of steady state simulation with HYSYS at GALPenergia Sines Refinery
Two examples of steady state simulation with HYSYS at GALPenergia Sines Refinery José Egídio Fernandes Inverno 1*, Eurico Correia 2, Pablo Jiménez-Asenjo 3 and Josep A. Feliu 3 1 Galpenergia, Refinaria
More informationHeat Exchanger Network Retrofit Design by Eliminating Cross Pinch Heat Exchangers
American Journal of Engineering Research (AJER) e-issn : 2320-0847 p-issn : 2320-0936 Volume-02, Issue-05, pp-11-18 www.ajer.us Research Paper Open Access Heat Exchanger Network Retrofit Design by Eliminating
More informationEnergy conservation. Benefits from the new generation of Mass and Heat Transfer Components. Beijing, P.R. China April 2006
Energy conservation Benefits from the new generation of Mass and Heat Transfer Components Authors: Stefano Costanzo Sulzer Chemtech APA - Shanghai Md. Cao Zhen Hua - Sulzer Chemtech APA - Shanghai Presented
More informationIntroduction to Distillation. Binous - Introd. to Distillation
Introduction to Distillation 1 Exploits differences in boiling point, or volatility Requires the input of energy Handles a wide range of feed flow rates Separates a wide range of feed concentrations Produce
More informationLOR Crude unit 1 APC March 2012
LOR Crude unit 1 APC March 2012 Laurent Ferrari Sean Goodhart Barry Rutter Zak Friedman 1 Petrocontrol Agenda Process APC description and scope Multivariable predictive controller Inferential models Issues
More informationThe influence of rectification sharpness on the quality of motor fuels
Energy Production and Management in the 21st Century, Vol. 2 833 The influence of rectification sharpness on the quality of motor fuels M. S. Rogalev & R. Z. Magaril Department of Oil and Gas Processing,
More informationApplying genetic algorithm for Minimization Energy consumption in a distillation unit
Applying genetic algorithm for Minimization Energy consumption in a distillation unit M.Mamanpoush*, H.Amiri, I.Akbari, S.Ghesmati, M.R.Ehsani Department of Chemical Engineering, Isfahan University of
More informationAn Exergy Analysis on a Crude Oil Atmospheric Distillation Column
An Exergy Analysis on a Crude Oil Atmospheric Distillation Column Amir Hossein Tarighaleslami 1 *, Mohammad Reza Omidkhah 2, Soroush Younessi Sinaki 3 1 Chemical Engineering Faculty, Islamic Azad University,
More informationNOVEL DISTILLATION CONCEPTS USING ONE-SHELL COLUMNS
NOVEL DISTILLATION CONCEPTS USING ONE-SHELL COLUMNS ärbel Kolbe, Sascha Wenzel Krupp Uhde GmbH, Dortmund, Germany ASTRACT This presentation examines the procedures involved in implementing the divided-wall
More informationRigorous Optimisation of Refinery Hydrogen Networks
CHEMICAL ENGINEERING TRANSACTIONS Volume 21, 2010 Editor J. J. Klemeš, H. L. Lam, P. S. Varbanov Copyright 2010, AIDIC Servizi S.r.l., ISBN 978-88-95608-05-1 ISSN 1974-9791 DOI: 10.3303/CET102100154 319
More informationA Novel Synergistic 4-column Methanol Distillation Process
937 A publication of CHEMICAL ENGINEERING TRANSACTIONS VOL. 61, 2017 Guest Editors: Petar S Varbanov, Rongxin Su, Hon Loong Lam, Xia Liu, Jiří J Klemeš Copyright 2017, AIDIC Servizi S.r.l. ISBN 978-88-95608-51-8;
More informationADVANCED PROCESS CONTROL
CHAPTER-11 ADVANCED PROCESS CONTROL Chapter No 11 Page No 1 INTRODUCTION The traditional control philosophy, what is called instrumentation in the chemical industries, is based on single loop control (sometimes
More informationProcess and plant improvement using extended exergy analysis, a case study
Process and plant improvement using extended exergy analysis, a case study ALHASSAN STIJANI 1, NAVEED RAMZAN 1, WERNER WITT 1 Lehrstuhl Anlagen und Sicherheitstechnik Brandenburgische Technische Universität
More informationIntroduction. Objective
Introduction In this experiment, you will use thin-film evaporator (TFE) to separate a mixture of water and ethylene glycol (EG). In a TFE a mixture of two fluids runs down a heated inner wall of a cylindrical
More informationA DESIGN REVIEW OF STEAM STRIPPING COLUMNS FOR WASTEWATER SERVICE. Timothy M. Zygula. Huntsman Polymers 2504 South Grandview Ave Odessa, TX 79760
A DESIGN REVIEW OF STEAM STRIPPING COLUMNS FOR WASTEWATER SERVICE Paper 7A Timothy M. Zygula Huntsman Polymers 2504 South Grandview Ave Odessa, TX 79760 Prepared for Presentation at the The AIChE 2007
More informationQuiz Questions. For Process Integration. Fill in the blanks type Questions
Quiz Questions For Process Integration Fill in the blanks type Questions 1. is the key parameter used in the Pinch Technology. ( T min ) 2. In onion diagram pinch technology in applied at. (the boundary
More informationIMPLEMENTATION OF OPTIMAL OPERATION FOR HEAT INTEGRATED DISTILLATION COLUMNS
IMPLEMENTATION OF OPTIMAL OPERATION FOR HEAT INTEGRATED DISTILLATION COLUMNS Hilde K. Engelien, Truls Larsson and Sigurd Skogestad Department of Chemical Engineering, Norwegian University of Science and
More informationSalt deposition in FCC gas concentration
Salt Deposition in FCC Gas Concentration Units Michel Melin Director Technical Service Grace Davison Refining Technologies Europe, Middle East and Africa Colin Baillie Marketing Manager Grace Davison Refining
More informationAnalysis of Heat Exchanger Network of Distillation Unit of Shiraz Oil Refinery
Analysis of Heat Exchanger Network of Distillation Unit of Shiraz Oil Refinery J. Khorshidi, E. Zare, A.R. Khademi Abstract The reduction of energy consumption through improvements in energy efficiency
More informationOn-line Parameter Estimation and Control for a Pilot Scale Distillation Column
On-line Parameter Estimation and Control for a Pilot Scale Distillation Column Lina Rueda, Thomas F. Edgar and R. Bruce Eldridge Department of Chemical Engineering University of Texas at Austin Prepared
More informationFOULING MANAGEMENT IN CRUDE OIL PREHEAT TRAINS/DHP UNITS
FOULING MANAGEMENT IN CRUDE OIL PREHEAT TRAINS/DHP UNITS Presenter: Metin BECER Process Superintendent Turkish Petroleum Refineries Corporation 15/11/16 Lisbon-Portugal ERTC Turkey s Leading Industrial
More informationCanada. Pulp and Paper Industry PI Specifics. How can process integration help me?
How can process integration help me? Process integration (PI) is a very efficient approach to improving the energy efficiency of large and complex industrial facilities. PI refers to the application of
More informationCONTROL OF DISTILLATION COLUMN USING ASPEN DYNAMICS
CONTROL OF DISTILLATION COLUMN USING ASPEN DYNAMICS Abhishankar Kumar*, Basudeb Munshi** *M.Tech. Student, abhiengg05@gmail.com **Associate professor, basudeb@nitrkl.ac.in Department of Chemical Engineering,
More informationTABLE OF CONTENT
Page : 1 of 12 Project Engineering Standard www.klmtechgroup.com KLM Technology #03-12 Block Aronia, Jalan Sri Perkasa 2 Taman Tampoi Utama 81200 Johor Bahru Malaysia RECOVERY AND SPLITTER TABLE OF CONTENT
More informationSaturday 20 May C 180 C C 130 C C 60 C kw 50 C 30 C C 20 C
Page 1 of 10 NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY (NTNU) - TRONDHEIM DEPARTMENT OF ENERGY AND PROCESS ENGINEERING PROPOSED SOLUTION EXAMINATION IN COURSE TEP 4215 PROCESS INTEGRATION Saturday
More information1. Introduction. 2. Base Case Design
21st European Symposium on Computer Aided Process Engineering ESCAPE 21 E.N. Pistikopoulos, M.C. Georgiadis and A.C. Kokossis (Editors) 2011 Elsevier B.V. All rights reserved. Plantwide Control of a Cumene
More informationPINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen. PULP AND PAPER INDUSTRY Energy Recovery and Effluent Cooling at a TMP Plant
PINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen PULP AND PAPER INDUSTRY Energy Recovery and Effluent Cooling at a TMP Plant PINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen
More informationDebottlenecking and Retrofitting by Pinch Analysis in a Chemical Plant
American Journal of Energy Engineering 2017; 5(5): 39-49 http://www.sciencepublishinggroup.com/j/ajee doi: 10.11648/j.ajee.20170505.13 ISSN: 2329-1648 (Print); ISSN: 2329-163X (Online) Debottlenecking
More informationAtmospheric distillation of crude oil
2.2 Atmospheric distillation of crude oil The purpose of atmospheric distillation, which is carried out at slightly above atmospheric pressure, is to separate (fractionate) the feedstock (crude oil) into
More informationMTBE Production. Process Description. Possibility of Changing Process Feed Conditions
Production You work in a facility that produces about 100,000 tonne/y of methyl tertiary butyl ether (). is an oxygenated fuel additive that is blended with gasoline to promote CO 2 formation over CO formation
More informationExample SPC-2: Effect of Increasing Column P on a C3 splitter
Example SPC-2: Effect of Increasing Column P on a C3 splitter Consider the separation of a mixture of 50 mol/hr of propane C 3 H 8 (1) and 50 mol/hr propene, C 3 H 6 (2) at a pressure of 1.1 bar and a
More information3.17. PROCESS INTEGRATION AND PINCH TECHNOLOGY
FUNDAMENTALS OF ENERGY BALANCES 111 pressure is expanded over the throttle value and fed to the condenser, to provide cooling to condense the vapour from the column. The vapour from the condenser is compressed
More informationPINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen. PULP AND PAPER INDUSTRY Energy Recovery and Effluent Cooling at a TMP Plant
PINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen PULP AND PAPER INDUSTRY Energy Recovery and Effluent Cooling at a TMP Plant PINCH ANALYSIS: For the Efficient Use of Energy, Water & Hydrogen
More informationExercise 5. Simulation of HDA plant in UniSim
Process Systems Engineering Prof. Davide Manca Politecnico di Milano Exercise 5 Simulation of HDA plant in UniSim Lab assistants: Roberto Totaro Salman Nazir Davide Manca Process Systems Engineering Politecnico
More informationPinch analysis of Acrylic Acid Process Plant
International Journal of ChemTech Research CODEN (USA): IJCRGG, ISSN: 0974-4290, ISSN(Online):2455-9555 Vol.9, No.06 pp 432-439, 2016 Pinch analysis of Acrylic Acid Process Plant K. Nagamalleswara Rao*
More informationModule 05 Lecture 35 : Low temperature process design Key words: Refrigeration system
Refrigeration System Module 05 Lecture 35 : Low temperature process design Key words: Refrigeration system A refrigerator is simply a heat pump where heat is rejected to atmosphere( the sink). Fig.41.3(lecture
More informationAvailable online at Energy Procedia 1 (2009) (2008) GHGT-9. Sandra Heimel a *, Cliff Lowe a
Available online at www.sciencedirect.com Energy Procedia 1 (2009) (2008) 4039 4046 000 000 Energy Procedia www.elsevier.com/locate/procedia www.elsevier.com/locate/xxx GHGT-9 Technology Comparison of
More informationWater Conservation Initiatives Burnaby Refinery
Water Conservation Initiatives Burnaby Refinery CAP Meeting May 11 th, 2016 Mack Atkinson Process Engineer Kel Coulson Lead Process Engineer Outline Photo credit: waterbucket.ca 1. General Refinery Water
More informationPREDICTIVE MODELING FOR AN INDUSTRIAL NAPHTHA REFORMING PLANT USING ARTIFICIAL NEURAL NETWORK WITH RECURRENT LAYERS
International Journal of Technology (2013) 2: 102 111 ISSN 2086 9614 IJTech 2013 PREDICTIVE MODELING FOR AN INDUSTRIAL NAPHTHA REFORMING PLANT USING ARTIFICIAL NEURAL NETWORK WITH RECURRENT LAYERS Sepehr
More informationHybrid Membrane-Distillation Separation Processes
1075 A publication of CHEMICA ENGINEERING TRANSACTIONS VO. 39, 2014 Guest Editors: Petar Sabev Varbanov, Jiří Jaromír Klemeš, Peng Yen iew, Jun Yow Yong Copyright 2014, AIDIC Servizi S.r.l., ISBN 978-88-95608-30-3;
More informationSimple Dew Point Control HYSYS v8.6
Simple Dew Point Control HYSYS v8.6 Steps to set up a simulation in HYSYS v8.6 to model a simple dew point control system consisting of: Gas chiller Flash separator Liquid stabilizer with gas recycle &
More informationDESIGN OF MULTICOMPONENT HEAT INTEGRATED DISTILLATION SYSTEMS LIM RERN JERN
DESIGN OF MULTICOMPONENT HEAT INTEGRATED DISTILLATION SYSTEMS LIM RERN JERN A project report submitted in partial fulfilment of the requirements for the award of the degree of Bachelor of Engineering (Hons.)
More informationCN4205R Pinch Analysis and Process Integration
CN4205R Pinch Analysis and Process Integration Sachin V JANGAM Department of Chemical and Biomolecular Engineering National University of Singapore Singapore Email: chejsv@nus.edu.sg Office location: E4-05-46
More informationEnergy recovery prospects of a distillation sequence revamp in an Amines plant
Energy recovery prospects of a distillation sequence revamp in an Amines plant Master s Thesis within the Sustainable Energy Systems programme EXTENDED ABSTRACT JONAS ÅRSJÖ Department of Energy and Environment
More informationModel and Optimisation of a Multi-Effect Evaporator of Sugarcane Juice: Energy Consumption and Inversion Losses
Model and Optimisation of a Multi-Effect Evaporator of Sugarcane Juice: Energy Consumption and Inversion Losses Daniela Galatro*, Elisa Verruschi, Roberto Guillen Universidad Nacional Experimental Politécnica
More information