University of Maiduguri Faculty of Engineering Seminar Series Volume 6, december 2015

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1 University of Maiduguri Faculty of Engineering Seminar Series Volume 6, december 2015 PROCESS HEAT INTEGRATION: A REVIEW U. A. Isah, A.L. Yaumi, M.M. Ahmed Department of Chemical Engineering, University of Maiduguri uaisah@unimaid.edu.ng; Abstract This work reviewed some of the research work done in the area of process heat integration. From the work review so far, the authors used uniform heat transfer coefficients for all the process streams and also used the same minimum approach temperature for all cold and hot streams in their energy and area targeting prior to the final heat exchanger network design. Since most of the chemical processes involve gasgas, gas-liquid or liquid-liquid heat exchange of streams with significant differences in heat transfer coefficients, their energy and area targets may not yield an optimal heat exchanger network design, hence, there is need to consider the use of individual stream heat transfer coefficient for energy and area targets, which will yield a cost effective heat exchanger network design. Key words: Process integration, heat exchanger network, energy target, area targeting, minimum approach temperature 1.0 Introduction Process design tools have seen rapid development and application in the chemical and manufacturing industries for heat exchanger networks (HENs), mass exchanger networks (MENs), waste water reduction and water conservation networks, waste interception networks, heat- and induced separation networks, and heat-and energyinduced waste minimization networks (Dunn and El-Halwagi, 2003). Pinch analysis has become a general approach for the design of processes in achieving minimum utilities requirement. The composite curves which is a graphical approach and the problem table algorithm (PTA), a numerical approach, are the most popular pinch analysis tools used in determining the minimum energy targets and the pinch points. The PTA developed by Linnhoff and Flower (1978) is mostly preferred than the composite curves for targeting the minimum external heating and cooling utilities, due to its advantages in speed and accuracy. On the other hand, the composites curves give better and clearer visualization (Smith, 2005). Energy saving in process plant design has essentially been a trial-and-error procedure between changes in structure and simulation until satisfactory reductions are achieved (Al-Kawari, 2000). Process design method, especially the graphical approach and the mathematical programming are the two techniques being used in the synthesis and design of heat exchanger network (HEN). The mathematical programming approach offers the advantage of accuracy and global optimality, problem dimensionality and computational effectiveness (Kravanja and Glavic, 1996). It is, however, less popular among engineering practitioners mainly because of the difficulty to master the technique and to set up the problem models. In contrast, the graphical techniques are typically easier to comprehend, apply and serve as a visualization tool for network targeting and design. However, it has limitations in terms of computational Seminar Series Volume 6, 2015 Page 88

2 effectiveness and often cannot guarantee a global optimal solution (Gundersen and Grossmann, 1990). The two approaches do complement each other and are widely used to provide better engineering understanding through visualization using graphical approache and to handle complex problems based on mathematical modeling (Wan Alwi and Manan, 2010). 2.0 Supertargeting Supertargeting is the process of a pre-design optimization for minimum approach temperature ( Tmin) based on the total cost (sum of the operating and the heat exchanger capital costs) of a network without specifying any piece of the heat exchange equipment (Linnhoff and Ahmad, 1990). Supertargeting also ensures that an initial design at an optimal Tmin that requires minimal evolution and further saves considerable efforts and time during the post-design optimization (Shenoy, 1995). Linnhoff and Ahmad (1990) introduced the Supertargeting procedure for the design of near-optimal heat exchanger network which systematically considers the energy-capital trade off. The method involves searching for the minimum temperature difference for heat exchange that yields the lowest total annual cost for a HEN. Ahmad et al. (1990) further extended the method by (Linnhoff and Ahmad, 1990) and (Ahmad, 1985) by proposing a more rigorous capital cost model. The model which includes a non-linear exchanger cost law can cater for different heat transfer coefficients, non-counter current heat exchangers, non-uniform materials of construction, a wide range of pressure and different types of exchangers in a network. Hall et al. (1990) introduced another method for dealing with mixed-exchanger specifications such as materials of construction, pressure ratings and equipment types in the capital cost targets using cost-weighting factors. They applied a simple modification to the existing capital and total cost targeting procedures that increased the accuracy of the targets. However, their approach requires the network to be designed using pinch design technique to determine exchanger flow arrangement and their optimisation approach also requires the use of linear programming. Hamidreza et al. (2011) optimized the energy and cost of plate and fin heat exchangers to trade-off between the total rate of heat transfer and the total annual cost using genetic algorithm. Genetic algorithm based on constructal theory was proposed and applied to shell and tube heat exchangers (Azad and Amidpour, 2011). These algorithms are difficult to understand by people with poor biological knowledge and also does not give a clear visualization of heat exchanger network design. 3.0 Heat Exchanger Network (HEN) Heat Pinch Analysis has been an established graphical approach for industrial practitioners to maximise energy efficiency of process systems via the identification of the thermodynamic bottleneck. Work by Heggs (1989) showed that, the minimum temperature difference approach used in heat exchanger network is related to the amount of energy lost in heat recovery systems, and in a normalized form to the ineffectiveness of a heat exchanger. This approach enables the network designer to Seminar Series, Volume 6, 2015 Page 89

3 eliminate all exchanger configurations that cannot meet the duty of a stream match at the network pinch. The goal of using the heat exchanger network synthesis is to design a cost-effective network that features minimum utility requirements, minimum heat transfer area and minimum number of units. However, trade-offs between these desired features are seldom necessary and as a result, the need for the optimization arises (Kemp, 2007). Furthermore, the total cost of an HEN is the sum of the operating cost and heat exchanger (HE) capital cost, both of which are functions of the heat exchanger minimum approach temperature (Shenoy, 1995). A lower value of Tmin gives a reduction in the energy usage, which is the operating cost but requires larger heat exchanger area, the capital cost. Therefore, cost is used as the basis in the trade-off between energy and capital cost reduction when Tmin is reduced. However, the balance will depend on the cost of heating and cooling, cost per unit area of heat exchangers and the period over which the capital cost is to be regained (Kemp, 2007). Profiles of continuous individual hot and cold streams known as Stream Temperature versus Enthalpy plot (STEP) being mapped on a shifted temperature and enthalpy diagram is a versatile graphical tool developed by Wan Alwi and Manan (2010), for simultaneous utility targeting and design of maximum energy recovery network. The STEP technique shows the hot and cold utility targets, pinch point, as well as maximum heat allocation (MHA) as opposed to the composites curves approach which can only provide minimum utility and pinch target. Wan Alwi and Manan (2010) further converted the MHA graphically to a maximum energy recovery network and represented it in terms of STEP s temperature and enthalpy on a Heat Allocation and Targeting (HEAT) diagram. The STEP technique was able to overcome the limitations of the grid diagram for heat exchanger network design and the composite curves for utility targeting by providing more realistic solutions for targeting multiple utilities, minimum network area based on individual as opposed to composite of hot and cold process streams matching, and multiple pinches. However, the use of uniform Tmin in their energy and area targets may not yield a cost effective heat exchanger network design. Sun et al. (2013) proposed a heat exchanger network cost optimization considering multiple utilities and different types of heat exchangers. There considered different levels of cold and hot utilities in order to reduce the operating costs, but used a uniform Tmin in their energy and area targets, which may not yield a cost effective heat exchanger network design. Suraya et al. (2015) developed a systematic technique to select the optimal design target for the HEN synthesis using a new trade-off plot which considers aspects of design, controllability in terms of steady state flexibility and sensitivity analysis, and cost. The proposed trade-off plot allows designers to choose the most suitable design target either for the purpose of improving a network s energy recovery and/or controllability. The designer is also able to predict the design, operability, and controllability of the designed HEN at the beginning of the synthesis stage. However, the use of uniform Tmin in their energy and area targets may not yield a cost effective heat exchanger network design. Seminar Series, Volume 6, 2015 Page 90

4 4.0 Conclusion In the synthesis of heat exchanger networks (HENs), the estimation of minimum energy and area requirement play a vital role for the prediction of operating and capital costs prior to design. However, Since most of the chemical processes involve gas-gas, gasliquid or liquid-liquid heat exchange of streams with significant differences in heat transfer coefficients, as a result, energy and area targets may not yield an optimal heat exchanger network design, hence, there is need to consider the use of the individual stream heat transfer coefficient for energy and area targets, which will yield a cost effective heat exchanger network design. Future work will focus on the concept of temperature difference contribution ( T cont ) for individual process stream by extending the work done on stream temperature versus enthalpy plot (STEP) developed by Wan Alwi and Manan (2010) for the targeting and design of minimum energy and area requirements of HENs. References Ahmad, S., Linnhoff, B. and Smith, R. (1990). Cost Optimum Heat Exchanger Network 2: Target and Design for Detailed capital cost Models. Computers and Chemical Engineering, 14 (7), Al-kawari, E. M. (2000). Pinch Technology: An Efficient Tool for Chemical- Plant Energy and Capital-cost Saving. Applied Energy, 65, Azad, A. V. and Amidpour, M. (2011). Economic Optimization of Shell and Tube Heat Exchanger based on Constructal Theory. Journal of Energy, 36 (2), Dunn, R. F. and El-Halwagi, M. M. (2003). Process Integration Technology Review: Background and Applications in the Chemical Process Industry. Journal of Chemical Technology and Biotechnology, 78 (9), Gundersen, T. and Grosmann, I. E. (1990). Improved Optimization Strategiesfor Automatic Heat Exchanger Synthesis through physical insight. Computers and Chemical Engineering, 14 (9), Hall, S. G., Ahmad, S., and Smith, R. (1990). Capital Cost Targets for Heat Exchanger Networks Comprising Mixed Materias of Construction, Pressure Ratings and Exchanger Types. Computers and Chemical Engineering, 14 (3), Hamidreza, N., Behzad, N., and Pooya, H. (2011). Energy and Cost Optimization of a Plate and Fin Heat Exchanger using Genetic Algorithm. Applied Thermal Engineering, 31 (10), Heggs, P. J. (1989). Minimum Temperature Difference Approach Concept in Heat Exchanger Networks. Heat Recovery Syetems and CHP, 9 (4), Kemp, I. C. (2007). Pinch Analysis and Process Integration: A user Guide on Process Integration for the Efficient Use of Energy. (2 nd ed.). Oxford: Butterworth- Heinemann, pp Kravanja, Z. and Glavic, P. (1996). Cost Targeting for HEN through Simultaneous Optimization Approach: A Unified Pinch Technology and Mathematical Programming Design of large HEN. Computers and Chemical Engineering, 21 (8), Seminar Series, Volume 6, 2015 Page 91

5 Linnhoff, B. and Ahmad, S. (1990). Cost Optimum Heat Exchanger Networks-1. Minimum Energy and Capital using Simple Models for Capital Cost. Computers and Chemical Engineerin,. 14, Linnhoff, B. and Flower, J. R. (1978). Synthesis of Heat Exchanger Networks: I. Systematic Generation of Energy Optimal Networks. AIChE Journal, 24 (4), Shenoy, V. U. (1995). Heat Exchanger Network Synthesis: Process Optimization by Energy and Resource Analysis. Houston and Texas: Gulf Publishing Company, pp Smith, R. (2005). Chemical Process Design and Integration. England: John Wiley and Sons Ltd. Sun, K. N., Wan Alwi, S. R. and Manan, Z. A. (2013). Heat exchanger network cost optimization considering multiple utilities and different types of heat exchangers. Computers and Chemical Engineering. 49, Suraya, H. A., Abd-Hamid, M. K., Wan-Alwi S. R.., and Manan, Z. A. (2015). Selection of minimum temperature difference ( Tmin) for heat exchanger network synthesis based on trade-off plot. Applied Energy, 162, Wan Alwi, S. R. and Manan, Z. A. (2010). STEP: A new graphical tool for Simultaneous Targeting and Design of a Heat Exchanger Network. Chemical Engineering Journal, 162, Seminar Series, Volume 6, 2015 Page 92