Heat Exchanger Network Optimization using integrated specialized software from ASPENTECH and GAMS Technology.

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1 EngOpt rd International Conference on Engineering Optimization Rio de Janeiro, Brazil, July Heat Exchanger Network Optimization using integrated specialized software from ASPENTECH and GAMS Technology. Andres Felipe Suarez Corredor Universidad Nacional de Colombia. Bogotá D.C. Colombia. afsuarezco@unal.edu.co 1. Abstract This article presents a generalized methodology of a heat exchanger network process optimization taking as an example a Natural Gas Processing Plant WDGC (Western Desert Gas Complex) of the Egypt National Natural Gas Company (GASCO) with the use of Process Engineering specialized software from AspenTech and GAMS Technology companies. To obtain the best design on energetic use, those designs are optimized in the heat exchanger surface area, rational use of utilities and economic costs. Several modifications on the heat exchanger train of the Natural Gas Processing Plant are proposed to have opportunities on energy conservation, as an economical and environmental solution. The steady-state simulation of the plant is made with HYSYS Software through the implementation of Pinch Technology; it is possible to calculate the minimum requirements of heating and cooling for the processing plant. Finally, using Aspen Energy Analyzer software from AspenTech Suite and the optimization software GAMS, a series of optimal HEN s are generated, in which is possible to recover a high quantity of heat at minimum total costs. These improve on energy performance and costs savings could be made only with the installation of two heat exchangers to the existing heat exchanger network. 2. Keywords: Energy Integration, Process Optimization, Pinch Technology. 3. Introduction Today in the industry, the design and optimization procedures have the trend to identify the configurations where the less energy consumption can be achieved. The possibilities for energy savings and the resulting environmental and economic saving for the various industrial applications can be diverse and very useful nowadays, when the search of new energy resources because the scarcity of traditional fuels and the instability in the global markets, demand that the industry maximize their efforts in the energy consumption optimization. The optimization of the Heat Exchanger Networks (HEN) requires a procedure, in which several models and algorithms have been proposed due to the complexity of the analyzed systems. The use of Pinch Technology allows to find the balance between energy and costs as well as the correct location of Utilities and Heat Exchangers. Through the technological advances and the software development, that has been carried out in the last years, let add other aspects to the analysis method of the Heat Exchangers Networks (HEN). These features can be: Utilities System, where all the utilities fluid system used in the plant can be specified on an independent way with their thermodynamic and economic data. Environmental consequences of the energetic integration evaluated, with the implementation of KPI s (Key Performance Indicators) as Carbon Footprint, Eco-Indicator 99, etc. Balance between the three main objectives that can be achieved in the energy integration process: Energy, Costs and Operation flexibility and reliability. With the development of optimization software, like GAMS Technology, is possible to apply MINLP (Mixed Integer No Linear Programming) to the Chemical Process Systematic Synthesis, which is the method used in the Energy Integration Software by AspenTech: Aspen Energy Analyzer. Although today, several new methods for the synthesis and optimization of Heat Exchanger Networks (HEN s) have been proposed, the Pinch Technology is the most complete and reliable thermodynamic method, in addition to allow modification to obtain a better description of the system. This method has been used in industrial applications across the world, resulting in energy savings of 15% to 45%. The incursion of Energy Integration methods have been realized in the petrochemical industry due to the diversity of conditions that can be present in the oil&gas processing and the large scale in which these plants are built. To demonstrate the advantage of the Energy Synthesis and optimization of Heat Exchanger Networks (HEN s) methods implementation through the Pinch Technology a Study Case to a Gas Processing Plant is implemented, using the simulation software suite from the AspenTech Company and the Optimization software from GAMS Technology. AspenTech software is used because its strength in the simulation of hydrocarbon processes and the peculiarities of the process that makes it suitable for the Energy Integration Process. 4. Background In the recent decades, the synthesis and optimization of Heat Exchanger Networks (HEN s) has progressed considerably, especially in the field of energy utilization, heat exchanger units and surface, key objectives to the Heat Exchanger Networks (HEN) Analysis. The selection method of the optimal Heat Exchanger Network (HEN) based in the optimization of the surface was demonstrated by Linnhoff and Townsend through the formulation of the Pinch Technology. Linnhoff was the pioneer who presents the theoretical

2 bases to allow today the creation of large Heat Exchanger Networks (HEN s) optimization algorithms applied in an industrial level. In the 1980 s, ICI was confronted with a great challenge in the crude distillation unit of one of its refineries. An expansion of 20% of its capacity was required but this expansion carried an increase of the plant energy demand. The most feasible solution was the installation of a furnace, but this solution was expensive and there wasn t enough space to locate the furnace in the plant. The process design team decided to calculate the first optimal Heat Exchanger Network (HEN) designs, demonstrating that the refinery could use less energy (discover a less energy consumption, even if with the expansion plan). With this fact, the team was hurried to make the practical designs of a Heat Exchanger Network (HEN) that could optimize the energy consumption of the refinery. As a result, an annual save of one million British pounds in energy was achieved and the capital cost in a new furnace was avoided. From this success and with the help of academic institutions, industrial applications have been reported in Union Carbide (USA) where a bigger saving than ICI were obtained; BASF (Germany) with more than 150 projects achieving an energetic saving and an increase in the profit in about 25% in their main plant in Ludwigshafen (Germany) and around a large amount of industries in 30 countries. Nowadays, the application of Heat Exchanger Network (HEN) Optimization methods has been become more sophisticated, with the use of process simulation software (AspenTech suite, PRO II, etc.) and algorithm oriented programming optimization software (GAMS Technology), so that allow to obtain an accurate description of the phenomena to optimize and let create algorithms that integrates systems of environmental, economic and energetic evaluation on a customize interface. 5. Theoretical Principles The algorithm of the Problem Table: Linnhoff et al. (1982) developed an algorithm as a math tool to replace the graphical method of composite curves to obtain a Heat Exchanger Network (HEN) with the less use of Utilities. As an energy balance, this method couldn t be related with the Heat Exchanger Surface and Costs. Figure 1. Heat Flow pattern at each temperature Interval. Mathematical formulation using Lineal Programming: The first step of the model is the partition in (k) temperature ranges (according to the temperatures of the process and utilities streams), keeping the hot limit higher than the cold limit by the Minimum Temperature Difference ( Tmin) selected and performing energy balances at each interval, where the lineal programming formulation gives an objective function, minimizing the cold and hot utilities as follows: o o Objective Function: Equations (Energy Balance): ( ) (1) (2) (3) (4) o Constraints: (5)

3 } (6) Where Q H is the minimum heat duty of hot utility, Q C is the minimum heat duty of cold utility, R k is the residual heat at the k interval, F m is the hot utility flow, F n is the cold utility flow at the k interval, h mk is the enthalpy change in the hot utility, h nk is the enthalpy change in the cold utility at the k interval, Q H ik is the heat duty of the hot stream i, Q C jk is the heat duty of the cold stream j, R 0 is the residual heat at the first interval and R K is the residual heat at the last interval. 5. Methodology The Gas Processing System (WDGC) is a typical turbo-expander plant of 1980 s, in which after the dehydration and precooling at - 37 C and 54 bar, the 100% of the separated gas is expanded at bar before the fractionation process at the demethanizer column with an operating temperature of -83 C as its coldest point. The ethane and heaviest hydrocarbons are separated and fractioned in the following equipment: Deethanizer that recovers a mixture of C2/C3 that is sent to a petrochemical products client of the region (Sidi Krir Petrochemicals Co. Sidpec.). Depropanizer that recovers the propane that can t be liquefied to LPG and is exported by the Alexandria s harbor. LPG and condensates from the debutanizer column. For the WDGC plant simulation, the AspenTech simulation suite Version 7.2 is used, specifically the HYSYS 7.2 software which is widely used by the petrochemical industry in the process simulation (Figure 1 and 2). For the Heat Exchanger Network optimization, the Energy Analyzer 7.2 and GAMS software is used. The process simulation is done with the following considerations: The current specifications of the feed and product streams. The design parameters for all the equipment as the real plant are used. Peng-Robinson as a thermodynamic model for the physical properties estimation is used. 6. Results Based on the process simulation done in Aspen HYSYS 7.2 software, the main results obtained for the streams are: Nombre Temperature ( C) Table 1. Specifications of the Main Streams of the WDGC Process Sales Gas Sales Gas Commercial Feed Gas C2/C3 to N.Grid to Dekhila Propane LPG Condensates Pressure (Bar) Mass Flow (kg/h) H2O N2 CO2 H2S Methane Ethane Propane i-butane n-butane i-pentane n-pentane n-hexane 5.64E E E E E E E

4 The Pinch Technology methods are implemented through the use of Aspen Energy Analyzer 7.2 and the optimization software GAMS. The network diagram to the current plant configuration is shown in the Figure 4. The software let choose automatically the utilities that have less costs, so it chose as cold utilities the air and Refrigerant 1 (Freon22), while as hot utilities it chose Low and Middle Pressure Vapor. Figure 2. PFD WDGC Plant with Main Specifications. Figure 3. PFD Cryogenic Section of WDGC Plant with Main Specifications The optimal Heat Exchanger Networks (HEN s) are obtained taking a Tmin of 10, 15, 20 and 25 C. With the use of the AspenTech suite software, the optimal designs are obtained, where a reduction in the utilities consumption is achieved, saving operating costs, getting a balance between operative and capital costs with economical KPI s (Key Performance Indicators) as return over investments (ROI) and Equipment Index Costs, etc.

5 Figure 4. Network Design for the Current Configuration of the WDGC Plant. The results obtained are summarized in the following tables and figures: Table 2. Comparison between the obtained Heat Exchanger Networks (HEN s) at different Tmin. HEN with HEN with HEN with HEN with HEN Specifications Current HEN of 10 C of 15 C of 20 C of 25 C Units Quantity Heaters Duty (GJ/hr) Heaters Surface (m2) Heaters Capital Costs ($/year) Coolers Duty (GJ/hr) Coolers Surface (m2) Coolers Capital Costs ($/year) Propane Cooler Duty (GJ/hr) Propane Cooler Capital Costs ($/year) Operating Costs ($/year) Heat Exchanger Surface (m2) Heat Exchanger Capital Costs ($/year) Total Capital Costs ($/year) Total Costs ($/year)

6 (Millions US$ / Year) C 15 C 20 C 25 C Current Figure 5. Costs Behavior at different HEN s Heat Exchanger Capital Costs Operating Costs Propane Cooler Capital Costs Coolers Capital Costs Heaters Capital Costs C 15 C 20 C 25 C Current Figure 6. Total Heat Exchanger Surface Heat Exchanger Surface (m2) Coolers Surface (m2) Heaters Surface (m2) 7. Conclusion Through the Aspen Energy Analyzer software and optimization software GAMS use is possible to find alternatives to obtain large energy consumption savings for a Natural Gas Processing Plant. This software let implement a methodology for Heat Exchanger Network (HEN) synthesis with the use of Pinch Technology. Several Heat Exchanger Networks (HEN s) are designed with different Tmin and the total annualized costs are compared to obtain the optimal design. The Heat Exchanger Network (HEN) with a Tmin of 10 C is the most optimal where the largest energy savings are obtained with the appropriate use of utilities (Save 42% for hot utilities and 21% for cold utilities compared with the current plant configuration), with less total costs. This save could be done through a plant revamp, with the addition of two heat exchangers. Additionally it is possible to realize a detailed study with a rigorous design methodology of Heat Exchanger Network, and that let to quantify the environmental impact with the modules implementation in the algorithm done in GAMS. 7. References 1. Ahmad, S., & Linnhoff, B. (1989). Super Target different Process Structures for different Economics. Journal of Energy Resources Technology, Ahmad, S., & Smith, R. (1989). Targets and design for Minimum Number of Shells in HENs. Journal of Chemical Engineering Resources, El-Temtamy, S., Hamid, I., Gabr, E., & El-Rahman Sayed, A. (2010). The Use of Pinch Technology to Reduce Utility Consumption in a Natural Gas Processing Plant. Petroleum Science and Technology, Flower, J., & Linnhoff, B. (1980). A Thermodynamic combinatorial approach to the design of optimum heat exchangers networks. AICHE Journal, Kemp, I. (2007). Pinch Analysis and Process Integration. Oxford: El Sevier. 6. Linnhoff, B., & Ahmad, S. (1990). Cost Optimum Heat Exchanger Networks - I Minimum energy and capital using simple models for Capital Cost. Computers and Chemical Engineering, Linnhoff, B., & Ahmad, S. (1990). Cost Optimum Heat Exchanger Networks - II Targets and design for detailed Capital Cost Models. Computers & Chemical Engineering, Linnhoff, B., & Hindmarsh, E. (1983). The Pinch Design method of Heat Exchanger Networks. Chemical Engineering Science, Nilsson, K., & Sunden, B. (1994). Optimizing a Refinery using the Pinch Technology and the MIND Method. Heat Recovery Systems & CHP, Reddy, B., & Venkata Seshaiah, P. (1997). Basic Concepts of Heat Exchanger Design. Chemical Engineering World,