APPLICATION OF DYNAMIC SIMULATION FOR DESIGN AND COMMISSIONING OF LNG PLANTS (EXPERIENCE IN MLNG TIGA PROJECT)

Transcription

1 APPLICATION OF DYNAMIC SIMULATION FOR DESIGN AND COMMISSIONING OF LNG PLANTS (EXPERIENCE IN MLNG TIGA PROJECT) APPLICATION D UNE SIMULATION DYNAMIQUE POUR LA CONCEPTION ET LA COMMISSION D USINES DE GNL (EXPERIENCE DU PROJET DE MLNG TIGA) Encik Norrazak Hj. Ismail, General Manager Mohd Soffie Ariffin, Senior Engineering Manager Malaysia LNG Tiga Sdn Bhd Bintulu, Sarawak, Malaysia norraz@petronas.com.my Hidefumi Omori, Senior Deputy Manager Hitoshi Konishi, Chief Engineer JGC Corporation Yokohama, Japan omori.hidefumi@jgc.co.jp Scott A. Ray, Senior Process Engineer, LNG Charles A. Durr, Technology Vice President, LNG Kellogg Brown & Root, Inc. Houston, TX, U.S.A. scott.ray@halliburton.com ABSTRACT During the MLNG Tiga project, dynamic simulation was used by the EPC consortium of KBR and JGC working with project owner Malaysia LNG Tiga Sdn Bhd for several studies of plant design and verification of the plant performance. This approach proved to be very effective. Acceptance of Tested Performance of the Refrigerant Compressors The as-tested performance curves of the refrigerant compressors were used within dynamic simulations to verify that the refrigerant compressors, together with the actual performance of other equipment, would meet the requirements for LNG production. Unique Power Exchange Concept between Gas Turbines Both the MR compressor and propane compressor are powered by individual gas turbines. MLNG Tiga employs a unique power exchange concept between these two gas turbines. The excess power available from the propane compressor gas turbine is transferred to the MR compressor via synchronous electric motors/generators. Excess power can also be fed to the 50 Hz plant electrical distribution system from the 60 Hz circuit via a Load Commutated Inverter, and vice versa. Dynamic simulation was performed in order to ensure the robustness of these integrated electric and process systems during start-up/shutdown,. The simulation model included a full representation of the propane, MR and the natural gas circuits. The process model was linked to an electrical simulation of the turbines and synchronous machines. PS5-2.1

2 Plant Performance Verification During the plant performance test, dynamic simulation was used to demonstrate the performance of the plant. Furthermore, the simulations were used to demonstrate that specified margins are available and to demonstrate that alternate modes of operation are possible as designed. The data collected during the performance test was reconciled against the simulation then actual values of key parameters were estimated. These estimated key parameters, such as tray efficiencies and overall heat transfer coefficients, were then entered into the simulation and design/alternative cases simulated on a rating basis and benchmarked against the systems criteria for success. Through the use of dynamic simulation we can make future plants fit for purpose and more cost effective. RESUME Dans l exécution du Projet GNL de Tiga, Malaisie, une simulation dynamique a été retenue tant pour plusieurs études liées à la conception de l ensemble de l usine que pour la vérification de la bonne performance de l usine. Cette approche s est révélée très effective. Réception de la performance testée des compresseurs de réfrigérant sous l angle de la production de GNL exigée Les courbes de performance des compresseurs de réfrigérant, obtenues à l issue de l essai de performance sur ces machines, ont été utilisées telles quelles pour la mise en œuvre de simulations dynamiques avec les données de la performance réelle des autres appareils, afin de vérifier si les compresseurs satisfont ou non aux exigences imposées par la production de GNL. Concept d un échange de puissance de sortie unique entre turbines à gaz Le compresseur de réfrigérant mixte (MR) et le compresseur de propane sont entraînés respectivement par une turbine à gaz individuel. Tiga LNG en Malaisie adopte au projet précité un concept unique consistant à échanger de la puissance de sortie excédentaire de ces deux turbines à gaz entre elles. L excès de puissance, disponible, de la turbine à gaz entraînant le compresseur de propane est transféré au compresseur MR par moteurs/générateurs électriques synchrones interposés. L alimentation en cette puissance en excès du système distributeur de courant de 50 Hz dans l usine est également possible à travers le circuit de 60 Hz, grâce à un onduleur de charge ( Load Commutated Inverter ), et vice versa. Afin d assurer la bonne tenue de ces deux systèmes électrique et procédé ainsi intégrés, une simulation dynamique a été effectuée sur leur démarrage et arrêt. Le modèle de simulation couvre tous les circuits de propane, de MR, et de gaz naturel. Le modèle de procédé et le modèle électrique sur les turbines et sur les machines synchrones sont attelés l un à l autre dans la simulation dynamique. Vérification de la performance de l usine Lors de l essai de performance de l usine, une simulation dynamique a été effectuée pour démontrer la bonne performance de l usine, ainsi que pour démontrer que les marges de sécurité prescrites sont bien disponibles, mais aussi pour démonter qu un ou plusieurs modes d exploitation alternatifs sont possibles comme prévu dans l étude. Les données saisies tout au long de l essai de performance ont été entrées dans le simulateur afin PS5-2.2

3 d estimer les paramètres-clé tels qu en particulier l efficacité du plateau et le coefficient global de transfert thermique, pour simuler aussi bien l exploitation basée sur les conditions de calcul, que des cas d exploitation alternatifs en utilisant les données obtenues suite à la simulation de l exploitation nominale et par comparaison à celles-ci, résultats qui servent alors à base d établissement des critères de jugement pour les cas alternatifs. L introduction de la simulation dynamique nous encourage encore davantage à réaliser des usines plus pertinentes et économiques. INTRODUCTION The demand for natural gas throughout the world is rapidly increasing. Simultaneously, economies of the world are becoming more inter-dependent. Therefore it is important to maintain competitiveness in the global market place. To do so LNG owners are constantly looking for ways to remain competitive. An LNG facility enjoys economy of scale such that larger LNG facilities incur a lower annual cost of production. Therefore, to remain competitive, annual production capacities of new grassroots LNG facilities are trending upward at a strong pace. At the same time, innovative ideas have been applied in cost saving initiatives in order to lower both the capital expenditures and operating costs of these facilities while simultaneously focusing on health, safety and environmental issues. The MLNG Tiga project is an excellent example. With an annual capacity of 3.9 million tones per year each, the MLNG Tiga LNG trains are among the largest ever built. The application of several significant innovative ideas makes this project one of the most significant achievements in the LNG industry. The enabling technology for the implementation of these innovations is Dynamic Simulation. A recently developed set of Dynamic Simulation tools were applied to the MLNG Tiga project with the goal to reduce design margins, lower project costs, and visualize the plant operation while still in the design phase. BACKGROUND Process simulation of entire integrated systems is a pivotal technology for engineering designs. Almost a decade ago, it was stated I see modeling and simulation as a critical, enabling technology essential today to capture, test, integrate, transfer and institutionalize knowledge acquired along the value-adding and information supply chain to our customers and their customers. Those companies that use these tools effectively will provide increasing value to the marketplace. Those that do not will be pushed aside. [1] The statement was made in a general way regarding all process simulations while users were primarily focused on steady state simulations. At that time most desktop computers were not powerful enough to handle dynamic simulations of large integrated process systems. In spite of a lack of widely available powerful computers during the early 1990s, many studies were conducted with dynamic simulation. Used in the optimization of the control system in gas compressors, dynamic simulation was proven to be a cost-effective tool. [2] As the methods improved and desktop computers became more powerful, dynamic PS5-2.3

4 simulation was used successfully to minimize the investment for new and revamp designs. The gas processing industry used these tools to remain competitive and profitable as they focused on improving operational flexibility, unit availability and reliability, as well as on quality of products, tightening of performance guarantees and length of start-up and shutdown times. [3] Within the LNG industry in the late 1990 s the use of dynamic simulation became a standard part of the design. In certain studies the release of refrigerant to the flare was minimized through the use of these tools, thus reducing the flare size and capturing associated cost savings. Dynamic simulation was used to reduce the risk of damaging rotating equipment, as well as to give the owner/operator the confidence necessary to implement the next generation technologies. [4] An excellent example for study is both the high pressure MR and propane compressors operated by the same Frame 7 gas turbine on a single shaft at a constant speed. Dynamic simulation helps to ensure the operability of such new designs throughout upset conditions, start-up and shutdown. [5] Today a typical design philosophy of many LNG facilities is to use equipment with a minimum of two years proven experience. This is not always possible, particularly when innovative ideas are applied or single train capacities set new world-class standards. In these instances, new elements of risk are introduced and must be adequately managed throughout design, equipment acceptance testing, and plant commissioning and verification. Dynamic simulation is the best available method for the analysis of risks introduced by new designs and innovations. Many of the phenomena that must be understood occur during upset conditions. Additionally dynamic simulators typically use simultaneous solution methods and are capable of solving steady state pressure driven simulations, such as the multi-level refrigeration systems of the LNG plant. Because typical steady state simulators are popular, but cannot easily solve the pressure driven system, processes are often simulated with estimated parameters to simplify the system. However, simplifying the system introduces error, which can only be overcome by employing a design margin. [6]. The dynamic tools used on the MLNG Tiga project provide capabilities that are far superior to what is available from traditional process simulators. For instance, the use of these dynamic tools can allow the plant to be debottlenecked during the design phase, increasing the effectiveness and productivity of the installed equipment. Additionally, the enhanced capabilities allow the designer to analyze margins and design factors of the sized equipment and to minimize the combined effect, thereby optimizing the owners return on investment. MAIN FEATURES OF MLNG TIGA PLANT The turnkey engineering, procurement, construction and commissioning work of MLNG Tiga project and associated facilities was started in 1999 by the consortium of JGC Corporation and Kellogg Brown & Root. The project has two liquefaction trains, each with a design LNG production capacity of 3.9 million tones per year. Also included is a new LNG storage tank, with a capacity of 120,000 m 3 and an additional 3 rd LNG Ship Berthing Facility. The MLNG Tiga plant is located on a site adjacent to the two existing plants, MLNG and MLNG Dua, a total of 6 trains. After start of operation of Train 7 & 8, that is MLNG Tiga, the Petronas LNG complex in Bintulu will have a total LNG PS5-2.4

5 production capacity of 23 mtpa, and will be the largest LNG complex in the world in a single location. The utility facilities in MLNG Tiga have been designed independent from the existing MLNG and MLNG Dua plants, but are inter-connected with MLNG and MLNG Dua and act as a back-up for each other. The LNG storage and loading system is designed for all three LNG plants (total of 8 trains). [7] The Petronas LNG complex in Bintulu, consisting of MLNG, MLNG Dua and MLNG Tiga, looks like a museum of LNG plants where we can see almost all of the technologies adopted by LNG plants over the years. The major features of these three plants are identified in Table 1. [8] Table 1. Features of MLNG, MLNG Dua and MLNG Tiga MLNG MLNG Dua MLNG Tiga (Ea.)Train Capacity 2.8 MTPA x 3 (120% of design) 2.6 MTPA x 3 (100% of design) 3.9 MTPA x 2 (100% of design) Liquefaction Process C3-Precool MR C3-Precool MR C3-Precool MR Main Driver Steam Turbine Frame 6 & 7 Two Frame 7 Helper Driver - Steam Turbine Motor Liquid Expander No Yes Yes Cooling Media Sea Water Sea Water and Air Air Heating Media Steam Steam Heat Trans. Fluid The key equipment in the large LNG plant is the compressor and its driver. These key pieces of equipment have large impact on the overall facility s ability to produce the required LNG. Large Compressor Configuration The adopted liquefaction process in MLNG Tiga plant, i.e., propane pre-cooling MR process, consists of one four-stage centrifugal type propane compressor, one low-pressure axial type MR compressor and one high-pressure centrifugal type MR compressor. Only a few manufacturers may produce these large and complex compressors. In this case, Nuovo Pignone (GEO&G) supplied these machines. The arrangement of the compressors and its driver is shown in the Figure 1. A special 60 Hz electrical control system (termed as EPCF) is used as a power manager to interact the LCI units with the gas turbine Mark V control systems (termed as UCP) to load and unload the VSDS unit. The propane compressor is driven by General Electric Frame 7-EA gas turbine and a variable speed starter motor/generator on the common shaft string. The motor/generator serves a dual purpose, first in providing starting power to bring the compressor/turbine combination up to 99.5% speed. Second, the motor generates electricity from the surplus gas turbine power available during normal operation. That electric power is then supplied to the MR compressor starter/helper motor and any excess power is sent to the grid. PS5-2.5

6 MR M 60 Hz 50 Hz TRAIN 7 PROPANE G MR M TRAIN 8 PROPANE G 60 Hz 50 Hz Figure 1. Configuration of Refrigerant Compressors in Train 7 & 8 Gas Turbine and Helper Motor Control Using LCI Both LP and HP MR Compressors are driven by a common shaft string connected to a General Electric Frame 7-EA gas turbine and a variable speed starter/helper motor. The electric starter/helper motor serves a dual role. First the motor provides starter power to bring the compressor/turbine combination up to 99.5% speed. Second, the motor provides additional shaft power to the MR compressor set during normal operation. The required electric power is supplied by the generator coupled to the propane compressor train. There are three types of operation of the compressors as shown in following figures. LCI CONT'L Motor 0 MW Σ Pi = 0 Generator 10 MW MR COMP Σ Pi = 0 Σ Pi = 0 C3 COMP MR GT C3 GT Figure 2. Operation with LCI PS5-2.6

7 Motor 0 MW Σ Pi = 0 60 Hz Generator MR COMP Σ Pi = 0 Σ Pi = 0 C3 COMP MR GT C3 GT Figure 3. Operation in Island 60 Hz 60 Hz MR COMP Σ Pi = 0 Σ Pi = 0 C3 COMP MR GT C3 GT Figure 4. Independent Operation During start-up, the gas turbines for MR and propane are controlled in isochronous mode, this means that the control of gas turbines maintains a fixed speed whatever the load (Figure 4). At the end of the start-up procedure, the unit is switched to droop mode and synchronized to the load commutated inverter (LCI) that takes the frequency of 60 Hz. In case of a defective LCI the propane gas turbine will run in the isochronous mode setting the frequency of 60 Hz and the two compressor trains will work in island mode. Normally the two compressor trains are electrically coupled running at fixed speed of 3600 rpm. In case of droop mode a speed variation is permitted. The philosophy used for the electric power production is to maximize the export to the 50 Hz grid (Figure 2). This strategy is achieved by setting the propane gas turbine to produce sufficient power to achieve the maximum generator capability while simultaneously the MR gas turbine is set to unload the MR helper motor as much as possible. The electrical power generated by propane generator is supplied to MR helper motor and exported to 50 Hz grid. The load fluctuation will be absorbed by LCI and both gas turbines until they reach their temperature control limits, then the LCI will cover any lack of power increasing/decreasing the power imported or decreasing the power exported. The LCI also absorbs the power fluctuation during transient upsets because of its faster response. PS5-2.7

8 The control system was designed for maximum delivery of electric power to the 50 Hz grid. Therefore the gas turbines usually operate at the maximum limit that is either defined by: Gas turbine capacity Maximum stator current of the synchronous machine LCI capacity The first limitation is applied if the compressor torque is high and/or the ambient temperature is high so that the temperature controller of the gas turbine limits the fuel flow. When the gas turbine capacity is high and/or the compressor torque is low so that the maximum stator current of the connected synchronous machine would be exceeded, the gas turbine output must be limited by an active power controller regulating the electric power of the synchronous machine. In order to protect the LCI, frequency control is automatically taken over by the speed governors of the gas turbines if the LCI reaches its current limit. These power-controllers drive the system smoothly back to nominal frequency and reduce the gas turbines output. In island operation, when the LCI is out of service, power exchange with the 50 Hz grid is impossible (Figure 3). Therefore, the 60 Hz power balance must be established by the gas turbines only. In this case, the propane gas turbine speed governor regulates the frequency of the 60 Hz system by setting the speed governor to isochronous. If in island operation the gas turbine capacity is not sufficient to cover the compressor load, frequency is reduced until a new steady state is established. The new steady state depends on the speed-torque characteristics of the compressors. In this case, frequency support can only be achieved if the LNG production, and hence the compressor torque, is reduced. One LCI is provided in each liquefaction train. If one LCI is under maintenance, it is possible to operate one of the trains in island mode and the other one connected to LCI. It is also possible to operate all four compressors in parallel through one LCI by configuring the 60Hz breakers correspondingly. COMPRESSOR PERFORMANCE The refrigeration compressors are the driving force of the LNG process. Therefore their performance is critical to the overall performance of the plant. Relatively small variations between the compressor design expected and actual performance during the official witness testing of the equipment translates into changes in the overall plant operation and could affect LNG production. Acceptance Criteria The MR and propane compressor Power Test Code 10 test is a Class III test (ASME specified procedure). The tolerances for acceptance are : Rated head for centrifugal type: +3%/-0% Power at rated condition: +/- 1% In some cases it may be critical that the compressor performance strictly meets the acceptance criteria. But in other cases this is not actually true. Although process performance is affected by the differences between the design basis and the as-built PS5-2.8

9 performance of the compressor, dynamic simulation can often be used to adjust the process to slightly modified conditions and still meet the overall requirements. Example Consider the simple propane refrigeration system illustrated below. This simple system is not part of the MLNG Tiga plant, but is an example used to illustrate the use of dynamic simulation. The process flowrate and composition are arbitrarily chosen for this example. The propane temperatures, pressures and flows are resultant based on that arbitrary process chosen, the air cooled exchanger area and air flow, and the compressor performance curves for volumetric flowrate, head, and efficiency. Receiver Desuperheater Condenser Compressor Subcooler LIC Process Heat Exchanger Figure 5. Example of Simplified Propane Refrigeration Loop The compressor performance is illustrated in Figure 6 below. Compressor Performance Case 1 Head (meters) Polytropic Efficiency (%) Inlet Flow ACMH (1000 m3/hr) Figure 6. Compressor Performance for Process Design PS5-2.9

10 Paper PS5-2 For this example, we assume the compressor is built and the actual performance of the tested machine produces 15% more head than expected at the design inlet flow rate. Of course, if this were a real design, the compressor manufacturer can modify the compressor by trimming wheels to lower the head and achieve actual performance much closer to the expected performance. But, for illustration purposes, it is assumed that this compressor will be considered operating within the plant with 15% higher head and efficiency at the design operating point. The question is then how will the overall process respond with this new compressor? Head Increased by 15% at Operating Point Head (meters) Where is the New Operating Point???? Inlet Flow ACMH (1000 m3/hr) Figure 7. Questioning System Performance With all other parameters held constant, the head and efficiency curves for the compressor are increased within the simulation with the following result. PS5-2.10

11 Paper PS5-2 Compressor Performance Comparison Head (meters) Inlet Flow ACMH (1000 m3/hr) Figure 8. Resultant System Performance New Operating Point Table 2 below illustrates the process changes due to the shift in compressor operation. First notice that the increase in the head curve by 15% has resulted in only a 0.4% increase in the propane evaporator duty (Table 2, Row B). Therefore the process receives a relatively small benefit. The total compressor and propane duty, all of which must leave through the air cooled exchangers, experiences only a small increase of 0.1% (Table 2, Row C.) Even though the overall duty that must be handled by the air cooled heat exchangers has increased a small amount, the distribution of duty between the three air cooled exchangers is significantly changed. (Table 2, Rows E, F, G.) Table 2. Sample Results Comparison Process Differences Caused by Compressor Performance Shift ROW LABEL Difference Compressor & Power MW -1.0% A Process Duty Propane Evaporator MW 0.4% B TOTAL MW 0.1% C Air Cooled Heat Exchangers Compressor Inlet Compressor Outlet Desuperheater MW -12.5% E Condenser MW 1.46% F Subcooler MW -3.1% G Flow rate ACMH 3.6% H Flow Rate kg/s 1.75% I Temp C J Pressure Bar-a K Temp C L Pressure Bar-a 0.18 M D PS5-2.11

12 Along with slightly higher head produced, the compressor operates also at a slightly higher efficiency. In Table 2, Row A it can be seen that the compressor power was reduced by 1.0% because of this higher efficiency. The higher compressor efficiency also produces the lower compressor discharge temperature shown in Row L. The lower compressor discharge temperature and higher compressor discharge pressure (Row M) result in a lower Desuperheater duty (Row E) and lower Subcooler duty (Row G) but a higher Condenser duty (Row F). Some of these resultant changes are not intuitive but are the result of several interactions. The small differences shown in the example above illustrates that the change of the performance of the compressor does not adversely affect the process performance. Obviously the effects on a complete LNG refrigeration system are much more complicated than this simple example. But, this simple example illustrates the very basic and important responses of a propane refrigeration system. When this technology is used for a complete LNG refrigeration system, the system must be modeled carefully and the results studied. The results of the MLNG Tiga simulations are far too extensive to present here, but the example above provides an excellent illustration of the effects. From this example it can be concluded that many complex but subtle effects determine the final operating point and overall system effectiveness. Simulation of LNG Production The software package has the ability to simulate a system in steady state, and then also optimize the system, maximizing an objective function based on calculation within the simulation. For MLNG Tiga s simulation, the optimization objective was to maximize the LNG rundown rate within the limits of available compressor driver power. The search for maximum LNG production was also limited by constraints to keep the search within reasonable process conditions. The software finds the optimum through a series of steps, whereby: The process simulation is solved for steady state conditions The optimizer automatically changes the value of a few key predetermined variables The process simulation is solved again for the new steady state conditions The optimization software compares values of the two steady state runs. The comparison, along with state of the art intelligence, is used to make another step towards the optimum. This process is repeated until the LNG production has reached a maximum. The system simulation includes many detailed models of the various unit operations. Each piece of equipment is carefully modeled. For instance, every stage of compression uses vendor supplied polytropic head and efficiency curves, while solving temperature and pressure calculations, overall energy balance and density calculations. Each heat exchanger, valve, expander, and flash vessel are modeled to include mass and energy balances, flash calculations which use calls to rigorous physical properties, and pressureflow relationships. All of these equations must be satisfied in order to reach a steady state solution. For a complicated system, many of the equations within unit operations are interdependent and must be solved simultaneously. For instance, the propane system is dependent on the polytropic head curves. While the head curves remain constant, the PS5-2.12

13 head produced by a stage of compression is dependent on the inlet volumetric flow. The inlet volumetric flow is dependent on the previous stage of compression and the propane vapor flow from the propane vaporizers. The heat exchanger models use a fixed value for UA in the LMTD calculation, which must retrieve the physical property from the database. All these equations must be solved simultaneously to arrive at the steady state solution. In the optimization procedure the steady state solver first completely solves all the unit operations in the simulation. The optimizer uses first order derivatives with respect to the objective function for certain variables to determine the direction of the next step. The optimizer will then change the values of several predetermined variables and the steady state solver will again solve the system. Each step that the optimizer takes while searching for the maximum LNG production is a valid steady state solution for the entire liquefaction system. Each step taken is therefore on the feasible path. While searching for the maximum LNG production, the optimizer is permitted to manipulate: Inlet guide vane angle of LP MR compressor Inlet pressure of LP MR compressor Outlet pressure of heavy MR expander MR composition These variables are available for the optimizer to manipulate while attempting to maximize the objective function. The system is also constrained by the following: Refrigeration compressor power must be less than or equal to the maximum allowable power. Outlet pressure of heavy MR expander must be 3 bar above the bubble point. The angle of the inlet guide vane of the LP MR compressor must be between 10 and 20 degrees. All temperature approached in the MCHE must be greater than a predetermined minimum, typically 1 or 2 degrees Celsius. By manipulating the variables listed above, and adhering to the constraints, the optimizer searches for the settings that will produce maximum LNG from this system. When the compressor manufacturer provided the as-tested performance curves, these performance curves were used in the dynamic simulation of the MLNG Tiga plant. The simulator predicted the systems operation and response to the as-tested curves. Then the simulator was used to shift small amounts of the load between the MR and propane refrigeration loops in order to optimize the overall operation. A new benchmark operation was created that optimized LNG production. Although the head of the fourth stage of the propane compressor exceeded the specified acceptance figure, it was found that the expected LNG production would be more than the design and it had potential to produce more LNG than the case of re-wheeling of the impeller. Therefore it was decided that the as-built performance curves of the refrigerant compressor were fit for purpose and used without any further modification. POWER EXCHANGE BETWEEN GAS TURBINES The dynamic study, which included the propane and MR refrigeration compression systems and an integrated electrical model, was carried out to confirm the following points. PS5-2.13

14 Confirm the performance of the combined operation of the propane and MR compressor systems integrated with the electrical control system. The study considered the response of the system from the viewpoint of process, mechanical, control and electrical, under start-up, normal operation, turndown and upset conditions. Establish that the overall control systems and safety features employed in the combined propane and MR refrigeration compression system are capable of ensuring safe operation and machinery/equipment protection during a number of identified modes of operation including start-up, shutdown, turndown and upset scenarios. The verification study above has been performed using actual equipment and system design data. Key Aspects of Dynamic Simulation The study was based on an integrated dynamic simulation model of the combined propane and MR refrigeration compression system and electrical system including a simplified model for the Main Cryogenic Heat Exchanger (MCHE) and the LCI. Thus, the interaction between the two compressor trains and the electric system was determined by the model. The dynamic simulation software, OTISS by Aspen Tech and the software, Power Factory by DigSilent, were integrated together as shown in following scheme. The torque in the compressor trains is transferred from process system to electric system and the speed, i.e., the frequency, is transferred from electric system to process system. Aspen Tech OTISS Process System & Compressors Torque Speed DigSilent Power Factory Electric System GT & Motor The verification studies establish the following: Minimize the susceptibility of the process system to electrical disturbances on the 60 Hz system Verify the operability of the system at design and turndown conditions Verify the response of the anti-surge control systems and associated recycle piping, hot gas bypass valve sizes and stroke time, and instrument requirements to protect the compressors from surge or stonewall Verify the control system employed in the propane and MR refrigeration compression trains and confirmation of the minimum number of control loops, alarms and trips required PS5-2.14

15 Verify that control systems are capable of ensuring safe operation and equipment protection during major upset conditions such as gas turbine trip, helper motor or generator trips, blocked compressor suction/discharge, LCI trip and electrical faults. Verify that sufficient starter motor/lci torque capability exists to accelerate in accordance with the acceleration rate required by MARK V. Verify that compressors stay on line under total recycle in the event of an MCHE trip Verify equipment design conditions Failure Scenario In order to verify the above conditions, the following upset scenarios have been assumed in addition to start-up, shutdown and normal operation. Sudden blockage of suction or discharge valves Trip of starter/helper motor and starter/generator Trip of gas turbines MCHE trip Failure opening of anti-surge control valves or hot gas bypass valves Trip of LCI Electrical faults Results of Simulation The major findings of these test runs are: The electric control system can perfectly handle any electrical disturbance and weak or slow mechanical disturbances. In case of very strong and fast compressor-torque variations, for instance caused by a process disturbance, the corresponding synchronous machines must be tripped to ensure that stator limits are not exceeded, as well as to maintain synchronism with the other 60 Hz synchronous machines that are operated in parallel. For instance, in case the propane compressor torque was suddenly reduced due to a process disturbance, e.g., failure opening of the anti-surge control valve or hot gas bypass valve, depending on the initial conditions, the propane generator would be tripped by the over-current protection before the control system could reduce the propane gas turbine power. Or in case the MR compressor torque was suddenly increased due to a process disturbance, e.g., discharge blockage of MR compressors, the MR motor would be tripped by the over-current protection. A small minority of failure cases, e.g., discharge blockage of MR and propane compressors, would lead to subsequent trips of the turbines. PS5-2.15

16 The process control system responds well to the normal operation, upsets, including start-up and shutdown. For trip cases requiring a reduction in load on the MR compressor such as helper motor failure, generator and electric system failure, the IGV on the MR axial compressor should be closed to an angle of 20 degrees with a rate of 5%/second. This will reduce the load on the MR turbine, preventing low speed trips. In case of an LCI failure, a frequency drop was observed due to limited electric power generation from the propane generator. Frequency then reached a new steady state value that depends on the speed-torque characteristic of the compressors and the available electric power in the island. PLANT PERFORMANCE VERIFICATION In a typical LNG performance verification, the plant is subjected to a performance test to verify that the required LNG production can be met. During the test, plant data is taken at prevailing conditions and adjustments are made for variances between prevailing and design conditions in ambient conditions and feed gas composition. In this case, the MLNG Tiga project wanted to ensure that built in equipment and system design margins are available for owners future use. Therefore, in addition to a typical performance test, simulations were prepared for systems within the plant. Field Performance testing was performed for each system during the performance test. The data from the field performance testing was modeled using the computer simulation and benchmarked to accurately represent the performance of the as-built system. Then the computer simulation was run for the appropriate design cases to demonstrate that the system as a whole has the ability of turndown and alternative modes of operation include all design cases. Methodology of Verification Data taken from this, or any, performance test will have errors of measurement included in the data. Instruments that have drifted away from calibration or are faulty may cause these errors. That data will not match the equations within the simulation. For instance, if we know that A + B = 4, and one instrument reports that A = 2.1 and another instrument indicates that B = 1.8, it is easy to see that there is a problem between the data and the equation. In the case of MLNG Tiga, there were hundreds of instruments reporting data and thousands of equations representing the heat and mass balance, pressure-flow relationships, and equipment parameters and functions. This data was entered into the dynamic simulator, which was then run in a data-reconciliation mode. Using this type of analysis, the computer can determine which variables, if any, are grossly in error. All variables are forced to conform to the known equations that govern that system. But, the combined errors between variables and final values are minimized by the computer program. The resulting set of data looks very similar to the original test data, but with a small amount of shifting to ensure consistency with the process equations. That reconciled set of data is then used to evaluate the performance of the system. Equipment parameters throughout the system are estimated from the system performance simulation run in a rating case mode. Those equipment parameters can then be used in a simulation of the design cases for each system and compared against the benchmark simulation prepared PS5-2.16

17 early in the project or against the heat and material balance originally developed by the process licensor. Stating it with different words, the system s equipment parameters are estimated based on actual performance in the field. Those estimated parameters are then used in a simulation of the design cases to determine the performance of the system if the as-built system was operating with exactly the design ambient conditions and design feed gas. Results of Simulation These simulations performed for MLNG Tiga illustrated that the as-built systems have the required capability to maintain the specified owners margin. The overall system simulation illustrated that the equipment installed, while operating at the design ambient conditions with design feed gas composition, could produce an LNG rundown rate considerably higher than the guaranteed value. Additionally the simulations illustrated that the various subsystems met or exceeded their expected performance, while maintaining the owners margins. In the future this simulation will be a valuable tool. When the owner decides to further debottleneck the plant to achieve the next higher level of production, this simulation can be used to accurately determine what changes must be made to reach the owners goal. The simulation could also be used for additional studies, what-if scenarios, and troubleshooting. CONCLUSION Dynamic simulation is the best available method for the analysis of risks introduced by new designs and innovations. The dynamic tools used on the MLNG Tiga project provide capabilities that are far superior to what is available form traditional process simulators. For instance, the use of these dynamic tools can allow the plant to be debottlenecked during the design phase, increasing the effectiveness and productivity of the installed equipment. Additionally, the enhanced capabilities allow the designer to analyze margins of the sized equipment and to minimize the combined effect, thereby optimizing the owners return on investment. REFERENCES CITED 1. Chemical and Engineering News, 73, March 27, 1995, Process Simulation Seen as Pivotal in Corporate Information Flow by James H Krieger. Quote made by James A. Trainham, director of engineering research and development, DuPont. 2. SPEEDUP Users Meeting, Cambridge, UK, April 1991, SPEEDUP for Anti-Surge Control of Gas Compressors by Mary E. Gill, WS Atkins Engineering Sciences Ltd., Woodcote Grove, Ashley Road, Epsom, Surrey England. 3. Petroleum Technology Quarterly, Winter 1996/1997, Minimising Investment with Dynamic Simulation, by Gerbert van der Wal, et. al, Fluor Daniel. 4. LNG 12, Perth, Australia, May 4-7, 1998, Improved Plant Design and Cost Reduction through Engineering Development, by Charles Durr, et. al, KBR, Houston, TX. PS5-2.17

18 5. LNG 12, Perth, Australia, May 4-7, 1998, The 4.5 MMTPA Train A Cost Effective Design, by Victor Perez, et. al. 6. LNG 13, Seoul, Korea, May 14-17, 2001, A New Tool Efficient and Accurate for LNG Plant Design and Debottlenecking, by Hidefumi Omori, et. al. 7. LNG 12, Perth, Australia, May 4-7, 1998, The MLNG Project by Norrazak Hj. Ismail and Henk Grootjans. 8. LNG13, Seoul, Korea, May 14-17, 2001, The Malaysia LNG Complex-Sustainable Growth by Ahmad Adzha Kasmuni, Goh Ngiang Ann, and Jannes Regterschot. PS5-2.18