Dynamic Simulation for Emissions Regulation
Existing pressure relief and flare system capacity is sometimes challenged following unit upgrades and expansions, addition of new process units, or the re-routing of atmospheric vents to the existing flare system. Traditional relief load estimation methodologies are known to be overly conservative and can lead to the overdesign of flare systems or to the determination that such plant upgrades ...
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Existing pressure relief and flare system capacity is sometimes challenged following unit upgrades and expansions, addition of new process units, or the re-routing of atmospheric vents to the existing flare system. Traditional relief load estimation methodologies are known to be overly conservative and can lead to the overdesign of flare systems or to the determination that such plant upgrades now require a flare capacity expansion.
In addressing these situations, dynamic simulation has become an accepted methodology to determine relief loads more accurately when traditional conservative methodologies indicate the existing flare is at or over capacity. Depew and Dessing reported significant reductions in peak relief load using dynamic simulation instead of traditional methods. However, the reductions from dynamic simulation are sometimes still not enough to offset the increased flare capacity requirements from the plant upgrade.
API 521 and AMSE Section VII Code Case 2211-1 provide an alternative to pressure relief devices, whereby a safety instrumented system (SIS) can be used to protect against over pressure. Traditional relief devices achieve pressure protection through controlled removal of the contents causing the over pressure, while the SIS approach focuses on removal of the cause of the over pressure itself. Since the SIS in this type of application involves substantial risk in the event of failure, it must be of high integrity and is thus often referred to as being a high integrity protection system (HIPS). Installing a HIPS can lead to large capital savings by eliminating the need for costly upgrades to an existing relief/flare system when even the dynamic simulation model indicates that additional flare capacity is needed.
This model was developed using Invensys’ Dynsim software. The relief devices on the two towers discharge to a common flare header.
To illustrate the benefit of a HIPS, this article details a project performed to evaluate the peak relief rate for an integrated de-isobutanizer and de-butanizer, considering:
Traditional unbalanced heat load approach;
Rigorous dynamic simulation adhering to API 521 practices; and
Rigorous dynamic simulation considering a HIPS on the re-boiler steam.
This type of analysis shows how the different approaches complement each other and how the model can be used to determine the appropriate set point of the HIPS system to avoid nuisance trips of the plant, while ensuring a significant reduction in relief load. This information can be used to compare the cost of installing and maintaining a HIPS versus expanding the flare system. Such a decision also needs to factor in the growing requirements of public and regulatory authorities to reduce flaring due to air quality and global warming concerns.
Over the past decade, dynamic simulation has become a mature and recommended method for validating the design of chemical processes. Its benefits are cited in recent literature regarding the design of relief systems for complex distillation columns and the evaluation of compressor and other control systems. Benefits include:
Greater accuracy in the calculation of column relief rates;
Controls validation for optimal plant performance;
Optimization of the normal start-up/shutdown procedures before plant commissioning; and
Validation of operating strategies under abnormal conditions such as an emergency shutdown or trip.
Dynamic simulation can be applied to establish the effectiveness of HIPS to protect equipment and reduce the risk of a process exceeding its design limits. As the HIPS operates near the critical limit of a process and its integrity is vital to the safe operation of the plant, testing it on the plant can involve a great deal of risk. A dynamic simulation study can be used effectively to help validate the effectiveness of the HIPS by simulating its behavior, safely, on a computer.
This graphic shows the non-linear variation of peak relief load changing with the HIPS set point. In this particular case, the dynamic simulation model was configured to run the governing scenarios repeatedly with changing set points to come up with an optimum value for the set point.
Peak relief load calculations
The use of dynamic simulation for the analysis of HIPS can be further extended to evaluating HIPS on fired heater re-boilers and furnaces where the impact of residual heat capacitance in these equipments can be modeled to study their impact on flare loads. It can also be used to understand the behavior of extremely exothermic reactors where faster pressure and temperature transients become critical and where traditional relief devices may not work properly.
The application detailed in this article involved the use of a dynamic simulation study to predict the relief load of an integrated de-isobutanizer tower and a debutanizer tower in the alkylation unit of a refinery without any safety instrumentation and with a HIPS that cut off the supply of steam to the column re-boilers when the pressures in the columns reached a pre-determined set-point.
The de-isobutanizer and debutanizer towers each produce a distillate and a bottoms product, with each tower’s overhead vapor passing through a single drum overhead system and each having a single thermo-siphon steam heated re-boiler. The condensing duty on each tower is provided by cold water. The liquid feed to the de-isobutanizer primarily consists of i-butane, butane, and heaviers, while the vapor feed is a mixture of butane and i-butane. The feed to the de-butanizer is the bottoms of the de-isobutanizer. This flow is pressure driven since the de-isobutanizer operates at a higher pressure and elevation.
Two scenarios were tested on the dynamic simulation model to estimate the peak relief loads:
Total power failure: Causes the feed to trip, the electrically driven pumps to trip and loss of condensing duty. However, the supply of steam to the reboilers is assumed to continue.
Loss of cooling water: Causes loss of condensing duty while maintaining the feed into the towers and steam to the re-boilers.
As per API 521 recommendations, the simulation model was run for 30 minutes beyond the start of the upset. As shown in the “Dynamic simulation study results” graphic, the total peak relief rate determined by the rigorous dynamic simulation was 20% lower than the values estimated using the conventional unbalanced heat load calculations. The results also show that the HIPS system substantially reduced the peak relief loads for these columns and even eliminated the relief load from the de-isobutanizer.
Determination of the HIPS set point was also an important part of the solution delivered to the client. Setting it too high could have led to there not being a significant reduction in the relief load; setting it too low could have led to an increased rate of nuisance trips of the re-boiler when there are normal disturbances to the process. The response of the combined relief rate from both the towers to changing HIPS set points is not a linear problem with an easy solution.
This work was critical to helping plant management eliminate the need for an expensive re-design of the flare piping network for this unit. Dynamic simulation can also be used to model more complex and integrated processing units to determine the optimum configuration of multiple HIPS for safety shut down systems or for pressure relief load reduction as implemented here.
The dynamic simulation models were also effectively used to identify the optimum set point for the HIPS on this fairly straightforward unit. For more complex integrated processing units where equipments and units interact with each other, determination of optimum HIPS set points can be a difficult challenge. In such cases, dynamic modeling of the process and careful sensitivity analysis can be used to help make this determination.
It is also worth noting that the decision to proceed with using safety instrumented systems requires careful examination of applicable regulations and standards. These may include local body regulations and insurer’s requirements.
Dynamic simulation study results
Cooling water failure
Total power failure
Dynamic simulation with HIPS
Dynamic simulation with HIPS
Peak flows shown in this table are calculated in kg/hr.
Abhilash Nair is principal consultant, and Ian Willetts is director of process modeling and simulation, Invensys Operations Management, Plano, TX.
Alan Wade, is a faculty member of the Department of Engineering Science, University of Oxford, England.
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