Sustainable Application of Model Predictive Control (MPC) to the minimization of Flaring from Fuel Gas supply networks

Transcription

1 Sustainable Application of Model Predictive Control (MPC) to the minimization of Flaring from Fuel Gas supply networks D.G.Lewis Invensys Process Systems Z.Liu, Invensys Process Systems S.M.Akhter, Abu Dhabi Gas Liquefaction Company (ADGAS) Summary LNG and refinery Fuel Gas systems can be subject to frequent disturbance and instability. This is typically due to the difficulties of dynamically matching supply with demand. On the supply side, as a consequence of the cycling of equipment operation and compositional variations, the quantities of gas available to the network may not be constant. On the demand side, there may be significant variation in consumption patterns. Reconciling these two facets of the problem in a dynamic fashion, so as to achieve a balanced Fuel Gas inventory, usually exceeds the capabilities of conventional process control methods. The multiple dependencies and time delays that exist in even a moderately complex Fuel Gas system mean that there will be times when Fuel Gas inventory can be controlled only by flaring or makeup. Both of these options have economic and environmental penalties. This paper will describe how advanced process control techniques have been used to dramatically improve the performance of a Fuel Gas network at a world-scale LNG facility. The project has made use of two complimentary technologies: Control Loop Performance Management (CLPM), using Expertune s PlantTriage technology. Model-Predictive Control (MPC), using Invensys Connoisseur technology. CLPM has been used to analyse and improve the performance of the basic regulatory control loops, while MPC has added high-performance dynamic control. The application has demonstrated a 75% reduction in the quantity of Fuel Gas flared from the network. -1-

2 Background The Das Island facilities of Abu Dhabi Gas Liquefaction Company (ADGAS) manufacture 5.1 MTA of LNG, using as feedstock the gas associated with oil production from the nearby fields in the Persian Gulf. LNG is produced in three separate Trains; Trains 1 and 2 are each of 1.2 MTA capacity and were commissioned in 1974, while Train 3 is of 2.5 MTA capacity and was commissioned in In order to satisfy the strong demand for compression horsepower that is characteristic of the LNG process, ADGAS operate a number of steam boilers. These generate 62 barg steam by burning Fuel Gas. The steam is used to drive turbines associated with the various compressors in the LNG process, as well as for the generation of electrical power. The Fuel Gas combusted in the boilers comes from a number of different sources: Boil-off Gas ( BOG ), arising from LNG storage and tanker loading. Flash Gas, arising from the final flash stage of the liquefaction process. Makeup Gas, which is sweet gas from the intake of the liquefaction process. Depressurisation Gas, arising from the intermittent depressurisation of the gas driers and treaters in the process. Trains 1 and 2 have a common Fuel Gas system, separate from that of Train 3. The application described in this paper is concerned only with the Train 3 Fuel Gas system, and the associated steam Boilers 5 and 6. The Figure below shows the principal flows in and out of the Train 3 Fuel Gas system. -2-

3 Boil-Off Gas (BOG) from storage and tanker loading (21 barg, 768 MJ/kmol) Fuel Gas to Flare 7 Flash Gas from Liquefaction Train (11 barg, 642 MJ/kmol) Train 3 Fuel Gas System 74 Fuel Gas to Boilers 5 and 6 (3.5 barg, 692 MJ/kmol) Makeup (sweet) gas from Train 3 (15 barg, 880 MJ/kmol) Figure 1:Fuel Gas flow balance (Gas flows expressed in KNm3/hour) Problem Statement The Fuel Gas system has long experienced excessive volumes of routine flaring, simultaneous with a constant inflow of Makeup Gas. This mode of operation is incompatible with ADGAS environmental commitments, and represents a significant loss of valuable gas reserves. A number of alternative solutions have been considered, including physical plant modifications and control system-based approaches. The objective of the project described in this paper has been to use Control Loop Performance Management (CLPM) and Model-Predictive Control (MPC) technologies to implement a control-based solution. This approach has, at relatively low cost, eliminated the requirement for extensive and costly plant modifications. -3-

4 Fuel Gas Header and Surge Drum Configuration The Train 3 Fuel Gas system collects gas from the sources described above into a common 14 pressure-controlled header. Fuel Gas from this header may be used for the regeneration of the liquefaction train s gas driers and treaters, after which it flows back to a Fuel Gas surge drum. Gas also flows directly to the drum from the header, if not required for regeneration purposes. The Figure below indicates the principal flow paths of the Fuel Gas. Header pressure is maintained at the setpoint value of 10.2 barg by the modulation of the valve that allows passage of Fuel Gas direct to the surge drum, indicated as 8CPC0001 in the Figure below. 5CFI " 9CFC0031 Flash Gas ex-train3 P=10.2 Treater Regeneration ~ ~ 3CFC0032 Boil-Off Gas ~ 49FC0103 ~ 8CPC0006 (SP=10.1) 8CFI0005 P= % 8CPC0001 (SP=10.2) Gas Drier Regeneration 0-50% 3CPC0055 8CPC0005 (SP=10.1) To Fuel Gas Drum P=15 Sweet Gas Makeup P=50 barg P=10.2 Sweet Gas Makeup to Fuel Gas Drum Figure 2: Fuel Gas Header arrangement -4-

5 The various inflows to the Fuel Gas header are as follows: Boil-off Gas Inflow. This gas arises in the LNG storage and tanker loading area, some 1 km distant from the process area. Traditionally, the flow to the Train 3 Fuel Gas network has been fixed by means of a flow control loop, at a value of approximately 25 knm3/hr. Any excess of BOG beyond this amount is diverted to the Train 1 and 2 Fuel Gas systems, where it displaces intake ( raw ) gas. Flash Gas Inflow. Flash gas arises from the final stage of the Train 3 liquefaction process, when the LNG is flashed to atmospheric pressure and a temperature of -162 deg C. The Flash Gas contains a significant amount of nitrogen (up to 20%), together with methane. The quantity of Flash Gas is not controlled, and varies depending on the intake gas composition and the manner in which the Main Cryogenic Heat Exchanger (MCHE) is operated. Typical flow is 52 knm3/h. Makeup Gas Inflow. This is gas taken from the front end of the Train 3 liquefaction process. The gas has been sweetened but is otherwise untreated. Makeup gas should enter the Fuel Gas system only when needed to maintain the header pressure. However, it has been common practice to operate the system with a constant bleed of Makeup Gas into the header. Typical flow is 4 knm3/h. Depressurisation Gas Inflow. The Train 3 liquefaction process includes gas driers (at the front end of the process) and C3 treaters (at the back end). These units are periodically taken off line and regenerated by the circulation of heated Fuel Gas. In the first stage of regeneration, the vessels are depressurised into the Fuel Gas system. This results in a sudden inflow (over a period of minutes) of additional gas. -5-

6 Fuel Gas Surge Drum The purpose of the Fuel Gas drum is to provide some surge capacity in the system, and particularly to absorb the sudden influx of material associated with the depressurisation of gas driers and treaters. The surge drum is of 32 m3 capacity. 8CPC002A % 0-50% PV002C, 16" PV002D, 6" Flare Fuel Gas from Header 8CPC0002 8C-301 Fuel Gas Drum 45PC % Plant 45 Boilers 5 and 6 PV002B, 8"" PV002A, 2" Makeup Sweet Gas from Plant % Figure 3: Fuel Gas Drum and Pressure Control Systems In order to stabilise the pressure of Fuel Gas going forward to the Boilers, the surge drum is pressure controlled as indicated in the Figure above. Two separate pressure control loops are provided, one actuating the flare valves (PV002C and PV002D) and the other the makeup valves (PV002A and PV002B). These two pressure control loops operate with different setpoints, typically 5.8 barg and 5.2 barg respectively, in an attempt to avoid overlap in makeup/flare operation. There is a further pressure control loop downstream of the drum (45PC0032) which regulates the pressure going forward to the boilers to a value of 3.5 barg. -6-

7 Operating Practices and Performance Historically, ADGAS have experienced severe difficulty in maintaining stable control of the Fuel Gas drum pressure. The variability has affected the operation of the boilers downstream. In practical terms, it has been possible to maintain a reasonably stable Fuel Gas condition only by operating in an excess-supply mode. That is, by ensuring that the inflow of gas to the Fuel Gas system has always exceeded the Boiler demand. This is achieved by operating with a constant bleed of Makeup Gas into the Fuel Gas header. This caused the surge drum pressure to rise to the point at which the flare valves remained consistently open under routine operation, in order to modulate the drum pressure. Based on the PlantTriage data analysis, the average flare valve opening over the period monitored was 34.7%. On average, approximately 7 knm3/hr of Fuel Gas were flared from the drum. As originally configured, the Fuel Gas system lacked any means of matching the supply of Fuel Gas with the demand from the boilers. All three inflows to the system (Boiloff Gas, Flash Gas and Makeup Gas) were operated in open-loop manner, without any correction for the actual pressure in the drum. An attempt has been made in the past to connect the BOG flow control loop in cascade with the Fuel Gas drum pressure control loop (as slave and master respectively). However, this implementation failed due to persistent oscillation and instability. This was due to the time delay existing between the adjustment of the BOG flow and the consequent impact on Drum pressure, a consequence of the 1 km transmission line. It proved to be impossible to establish appropriate tuning for all conditions, particularly the depressurisation events. -7-

8 Control Loop Performance Management (CLPM) Control Loop Performance Management is the application of advanced on-line statistical techniques to the monitoring of basic regulatory control loops; that is, PID loops in either single-loop or cascade configuration. CLPM allows the real-time comparison of regulatory control loop performance with pre-defined benchmarks, and assists in the detection and diagnosis of faults and problems (tuning, valve stiction, measurement noise, etc). For this purpose Invensys make use of the PlantTriage product from Expertune. In the case of the project under consideration in this paper, the PlantTriage software was installed on a standalone PC, interfaced to the Honeywell TDC3000 system by means of an OPC Client/Server connection. The PlantTriage system was configured to capture data from all of the control loops around the Fuel Gas system at high frequency (2 second sample). Sample rates such as this, and indeed faster, are required to capture properly the fast dynamic behaviour of some PID loops. Key Achievements The use of the tools provided by the PlantTriage software, together with the expert engineering capabilities of the Invensys consultant, allowed a number of very significant improvements to be made in the performance of the basic regulatory controls. These included: Retuning of the control loop (3CPC0032) that regulates the Fuel Gas flow to Gas Drier regeneration. This resulted in a 50% reduction in both valve travel and number of reversals, without compromising dynamic performance. Detection of the fact that the Makeup valve that modulates flow to the surge drum 8CPC0002 was passing even when apparently fully closed. The valve positioner was recalibrated, saving 2 KNm3/hour of otherwise wasted (flared) gas (see Figure below) and resulting in a very significant improvement in stability. -8-

9 8CPY000B not fully closed, sweet gas leaks to the fuel gas drum. Controller is oscillating -5% 8CPY000B fully closed, causing drum pressure dropping faster - 6.9% Figure 4: Pressure Control Loop Tuning Improvements The PlantTriage software was used for the analysis of the dynamic response of the surge drum pressure when exposed to sudden upstream depressurisation events. This highlighted the possibility of using a smaller upstream vessel as a further capacity to dampen the impact on the surge drum itself. A feedforward scheme was developed and was implemented in the Honeywell DCS to ensure that the capacity of the upstream vessel was used to the full, while also maintaining its original function. The implementation of this Advanced Regulatory Control function reduced the impact of the depressurisations on the boiler operation, by limiting the Fuel Gas pressure excursions. The before and after comparison is shown very clearly in the Figure below. Typically the standard deviation of the key boiler parameters is reduced by at least 50% as a result of the actions described above. It is important to emphasise that, although the primary objective of the control system modifications was to locally improve the regulation of the Fuel Gas surge drum pressure, the actions had a strongly positive benefit on all downstream operations. This is typical of the nature of control system improvements; the benefits usually extend well beyond the immediate area of concern. This was a highly beneficial result achieved at relatively low cost and in a short period of time. -9-

10 Before After basic control loop improvements Figure 5: Boiler standard deviations (from top: Boiler 5 drum level, Boiler 6 drum level, Steam header pressure) -10-

11 Model Predictive Control (MPC) The improvements in the basic regulatory control performance that have been described above make possible the deployment of higher level control functions. With the benefit of a stabilised base layer, these functions, including Model Predictive Control, can work properly and can deliver real value. The Connoisseur MPC software was installed on a standalone PC, interfaced with the Honeywell TDC3000 DCS by means of an OPC Client/Server connection. The objective of the MPC application was to achieve inventory control by matching the supply of gas into the Fuel Gas system with the demand from the boilers. Indication of the current inventory is provided by the surge drum pressure; the objective of the MPC controller is to continuously adjust the inflow of BOG and Makeup gas in order to keep this pressure at a particular setpoint value. In fact, the setpoint value chosen is the mid-point between the setpoints of the flare and the makeup control loops. If the pressure is stabilised at this point, then neither flaring or makeup will be required. Constraints and Limits MV#1 FV#1 CV#1 Total Boiler Fuel Gas Demand MV#2 APC Controller 8CPC002 B.PV + 8 CPC0005 8C-301 Plant-3 Makeup to Fuel Gas system Fuel Gas Drum BIGBOG 49FC0103 Plant-8 Fuel Gas Header Trains 1 and 2 Fuel Gas Systems ~ ~ BOG flow to Fuel Gas Header Figure 6: MPC Controller Structure -11-

12 The MPC controller includes dynamic models of the actual responses of the Fuel Gas system. Since the Surge Drum is a capacity, the models take the form of integrator models when considered as step responses, as shown below. Figure 7: Surge Drum Pressure Response Models The Figure shows the way in which the Surge Drum pressure (M480 8CPC0002.PV) responds to a one engineering unit change in the BOG flow (A2000 8CPC002B.OP), the Makeup Gas flow (A2001 8CPC0005.OP) and the total Boiler Fuel Gas consumption (M9000). Representation of this integrating behaviour can be problematic for many MPC technologies, due to the reliance on Finite Impulse Response (FIR) models that do not allow the representation of Controlled Variable dynamics which are independent of input (Manipulated) variables. Such technologies require the introduction of special tuning factors to compensate for the un-modelled behaviour. The Connoisseur technology used in the ADGAS project uses an alternative ARX model formulation, which allows the direct representation of such integrating responses. This unique capability permits much more effective controller configuration and higher performance. The MPC controller must cope with two distinct modes of operation: normal regulation. Here the objective is to adjust the BOG and Makeup inflows in order to keep the Fuel Gas Drum pressure at the correct value. depressurisation. In this case, the objective is to quickly reduce the inflow of BOG so that the pressure excursion of the drum, and the consequent flaring, is minimised. These two different modes require different dynamic behaviour from the controller. In the former case, the requirement is for a well-damped response that does not excite unstable modes. In the latter case, the requirement is for fast and aggressive action to quickly eliminate flaring. These two different requirements have been met by creating a gain-scheduling algorithm which automatically switches the tuning in response to the current plant condition. The algorithm has been implemented using Connoisseur s Director command language, -12-

13 which allows the creation of event-driven controller reconfiguration actions. Such capability is essential in order to cope with the sudden and severe changes in operating mode that are typical of gas plant operation. -13-

14 The following two Figures compare pre- and post-project performance, considering an identical period of time (3 hours) and scaling. Flare Valve opening (%) FG Drum Pressure (barg) BOG Flow (knm3/hr) Pre-project performance: the flare valve (top trend) is permanently open in the range 0 to 50%, drum pressure is controlled at the setpoint of the flare pressure controller (5.6 barg). The incoming BOG flow (bottom trend) is constant at 27 knm3/hr. Depressurisation of the gas drier causes a prolonged period of flaring; there is no compensatory change in the incoming BOG flow. Permanent high levels of flaring are experienced. Flare Valve opening (%) FG Drum Pressure (barg) BOG Flow (knm3/hr) Post-project performance: the flare valve opens only briefly at the time of the depressurisation. BOG flow is continuously modulated to maintain the Drum pressure within the range defined by the setpoints of the Flare and Makeup controllers. Flare valve is fully closed for 80% of operational hours. -14-

15 Results The complementary implementation of CLPM and MPC has given rise to a very clear twostage benefit profile. The implementation of the basic regulatory control improvements arising from the CLPM analysis caused a very significant initial reduction in daily flaring. This was a consequence of a general improvement in system stability, so that the existing controls were able to work better. The CLPM improvements also created the conditions that allowed the MPC systems to be implemented and to function correctly. The Figure below compares three periods of operation: Sept-Oct 2007 Sept-Oct 2008 Flare (MMSCFD) Basic Control Improvements MPC Implementation Day Figure 8: Daily Flaring for Plant-8 Fuel Gas system In summary, the quantified improvements are detailed in the Table below: Flare (MMSCFD) % improvement Pre-project Following regulatory tuning Following MPC implementation Table 1: Reductions in Fuel Gas Flaring -15-

16 Conclusions This project has demonstrated the synergistic benefits associated with the implementation of Control Loop Performance Management (CLPM) and Model Predictive Control (MPC). The former technology represents a vital first step. By making the best possible use of the capabilities of the regulatory (PID) control layer, many problems and inconsistencies can be ironed out close to source, resulting in much reduced variability. This allows the development of much more accurate MPC models, and results in strongly improved performance. It is common for MPC controllers to be deliberately detuned in order to compensate for high levels of variability in the basic regulatory control layer. While this leads to stability, a significant penalty may be imposed in relation to impaired dynamic performance. This fact is well known, and most MPC projects include an activity dedicated to the evaluation of regulatory control performance and retuning where necessary. However, the activity is time consuming and labour-intensive. Often, it is only the loops that are considered a priori the most critical that are examined in detail. There is usually no systematic and unit-wide program of evaluation and remedial action. Tools such as PlantTriage allow just such a fast, systematic and thorough examination of regulatory control performance. On the basis of no more data than that equivalent to ten system time constants, PlantTriage is able to highlight potentially troublesome control loops and to identify the necessary remedial action, including the derivation of alternative PID tuning constants. Furthermore, CLPM software supports the ongoing monitoring and further improvement of the regulatory controls. Turning to Model Predictive Control, the project has shown that a model of relatively simple structure can be the basis of an application that can realise very substantial benefits, when it is properly matched to the actual plant characteristics. The particular ARX form of the Connoisseur model was strongly beneficial in this case, allowing the direct representation of the integrating character of the Surge Drum pressure responses. -16-